Search Results (57)

The increasing presence of high-rise buildings with curved and convex facades poses significant challenges for facade-cleaning robots, particularly in terms of mobility and anchoring. To address this, we propose a rope-riding mobile anchor (RMA) system capable of repositioning the anchor point of a cleaning robot on convex building surfaces. The RMA travels horizontally along a roof-mounted nylon rope using caterpillar tracks with U-shaped grooves, and employs a four-bar linkage mechanism to fix its position securely by increasing rope contact friction. This structural principle was selected for its simplicity, stability under heavy loads, and efficient actuation. Experimental results show that the RMA can support a payload of 50.5 kg without slippage under tensions up to 495.24 N, and contributes to reducing the power consumption of the cleaning robot during operation. These findings demonstrate the RMA’s effectiveness in extending the robot’s working range and enhancing safety and stability in facade-cleaning tasks on complex curved surfaces. Full article

Accurate estimation of available rooftop areas for PV power generation at the city scale is critical for sustainable energy planning and policy development. In this study, using publicly available high-resolution satellite imagery, rooftop solar energy potential in urban, rural, and industrial areas is estimated using deep learning models. In order to identify roof areas, high-resolution open-source images were manually labeled, and the training dataset was trained with DeepLabv3+ architecture. The developed model performed roof area detection with high accuracy. Model outputs are integrated with a user-friendly interface for economic analysis such as cost, profitability, and amortization period. This interface automatically detects roof regions in the bird’s-eye -view images uploaded by users, calculates the total roof area, and classifies according to the potential of the area. The system, which is applied in 81 provinces of Turkey, provides sustainable energy projections such as PV installed capacity, installation cost, annual energy production, energy sales revenue, and amortization period depending on the panel type and region selection. This integrated system consists of a deep learning model that can extract the rooftop area with high accuracy and a user interface that automatically calculates all parameters related to PV installation for energy users. The results show that the DeepLabv3+ architecture and the Adam optimization algorithm provide superior performance in roof area estimation with accuracy between 67.21% and 99.27% and loss rates between 0.6% and 0.025%. Tests on 100 different regions yielded a maximum roof estimation accuracy IoU of 84.84% and an average of 77.11%. In the economic analysis, the amortization period reaches the lowest value of 4.5 years in high-density roof regions where polycrystalline panels are used, while this period increases up to 7.8 years for thin-film panels. In conclusion, this study presents an interactive user interface integrated with a deep learning model capable of high-accuracy rooftop area detection, enabling the assessment of sustainable PV energy potential at the city scale and easy economic analysis. This approach is a valuable tool for planning and decision support systems in the integration of renewable energy sources. Full article

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article

Motor vehicles in transport, as one of the important sectors of the economy, emit a significant amount of carbon dioxide and other products in the form of exhaust gases, which are harmful to human health. The emission of exhaust gases from motor vehicles is limited by appropriate regulations in accordance with environmental goals, such as the Paris Climate Agreement. Reduced emissions and fuel (energy) consumption is mainly achieved by applying modern technologies for the production of internal combustion engines; transitioning to cleaner fuels, such as renewable natural gas or biomethane; and using alternative propulsion systems. Biomethane stored in a liquid state in on-board reservoirs has advantages in truck transport, ships, and air traffic. The reason for this is due to the higher concentration of energy per unit volume of the reservoirs and the lower storage pressure and thus higher safety compared to the high-pressure storage option (compressed biomethane). The presented research is related to a proposition regarding the design of drive systems of city buses using biomethane as fuel in cases when fuel is stored on-board the vehicle as gas in a compressed aggregate state. In this study, the results of a calculation method regarding the roof-supporting structure of an experimental bus with gas reservoirs under higher pressure are discussed as well. This study also presents the possibility of reducing harmful emissions if biomethane is used instead of conventional fuels as a transitional solution to electric-powered vehicles. For the sake of comparison, it is suggested that the engaged energy and the amount of produced carbon dioxide emissions within the drive systems of different fuels are calculated according to the recommendations of the standard EN16258:2012. Full article

Indoor Internet of Things (IoT) is considered as a crucial component of Industry 4.0, enabling devices and machine to communicate and share sensed data leading to increased efficiency, productivity, and automation. Increased energy efficiency is a significant focus within Industry 4.0, as it offers numerous benefits. To support this focus, we developed a hybrid switching mechanism to switch between energy harvesting techniques, ambient backscattering and Simultaneous Wireless Information and Power Transfer (SWIPT), which can be utilized within cooperative communications. To implement the proposed switching mechanism, we consider an indoor warehouse environment, where the moving sensor node transmits sensed data to the fixed relay located on the roof, which is then transmitted to an IoT gateway. The relay is equipped with the proposed switch to energize its communication capabilities while maintaining the expected quality of service at the IoT gateway. Simulation results illustrate the improved energy efficiency within the indoor communication setup while maintaining QoS at varying signal-to-noise (SNR) conditions. Full article

A powered roof support in a mining complex comprises a set of sections positioned side by side. Thus, it creates space for the mining longwall shearer and the excavated material haulage conveyor. The main role of the powered roof support is to secure the machinery and equipment, as well as the working crew. This roof support also takes over the load from the rock mass during operation. The loads and phenomena that cause damage to the powered roof support construction in real conditions became the basis for conducting a series of studies and analyses of the stresses and strains that occur. This study aimed to obtain the results of research and analysis on the damage to the floor base, which is the most important part of the entire powered roof support construction. The actual pressure measurements carried out in the space under the piston leg of the powered roof support under real conditions indicated an excessive load on the powered roof support construction. This load was mainly due to the ceiling conditions, while the floor conditions for providing the construction were difficult to determine due to the too-soft floor substrate. The Finite Element Method (FEM) was used to solve the problem. The construction of the two powered roof support bases was subjected to numerical analysis in order to propose structural changes. The obtained numerical test results indicated a solution to the problem of damage and significant structural changes. Full article

The article discusses laboratory methods and the corresponding computational methods verifying compliance with the normative requirements regarding the lateral correction force of the powered roof support. The currently used flat model only allows for checking the normative requirement in relation to the sum of active forces of the correction cylinders installed in the roof support. Determining the required value of the active force of each cylinder is possible due to the simplified FEM model of a powered roof support, described in the research work, treated as a uniform weightless elastic body loaded with a concentrated force recreating the weight of the roof support located on an inclined longwall panel. The third analysed computational method involves determining the reaction in the four correction cylinders of the roof support, creating a spatial, statically indeterminate system of forces. It enables determining the range of variability of the response in the correction cylinders as a function of the distribution of floor pressure on the roof support base. The discussed computational methods were used to determine, for example, the lateral correction force of one of the types of powered supports used in a longwall panel inclined at an angle of 35°. The usefulness of the discussed calculation methods at various stages of the designing process of the powered support and its certification has been confirmed. Full article

Rising fossil fuel costs and environmental concerns are driving the search for new energy sources, particularly renewable energy. Among these sources, solar photovoltaic (PV) is the most promising in southern European countries, mainly through the use of decentralised PV systems designed to produce electricity close to the point of demand and primarily to meet local energy needs. In an urban scenario, a decentralised energy system usually operates in parallel with the grid, allowing excess power generated to be injected into the grid. Solar carports and rooftop systems are excellent examples of distributed photovoltaic systems, which are far more sustainable than large centralised systems because they do not compete for land use. Despite their operational advantages, these decentralised photovoltaic production plants, which are in most cases financed by specific energy efficiency programs, present challenges in a regulated market where the injection of energy into the electricity grid is restricted by law and support programs. The aim of this work is to integrate two different photovoltaic systems within an academic campus where the only PV source currently available is a solar car park, a solution designed both to provide shaded space for vehicles and to produce energy to be consumed within the facilities. Due to legal restrictions, surplus electricity cannot be sold to the national grid, and solar batteries to store the generated energy are expensive and have a short lifespan. Therefore, since the campus has two different grid connections and a 102.37 kWp PV system, the newly designed system to be installed on the library roof must be calculated to support the installed electricity system during the most critical working hours, determining the specific angle and orientation of the solar panels. On this basis, the energy management of a school campus is fundamental to creating a collective self-consumption system, the basis of a local energy community that can meet energy, environmental, and social objectives. Full article

Energy efficiency is a critical aspect of engineering due to the associated monetary and environmental benefits it can bring. One aspect in particular, namely, the prediction of heating and cooling loads, plays a significant role in reducing energy use costs and in minimising the risks associated with climate change. Recently, data-driven approaches, such as artificial intelligence (AI) and machine learning (ML), have provided cost-effective and high-quality solutions for the prediction of heating and cooling loads. However, few studies have focused on interpretable classifiers that can generate not only reliable predictive systems but are also easy to understand for the stakeholders. This research investigates the applicability of ML techniques (classification) in the prediction of the heating and cooling loads of residential buildings using a dataset consisting of various variables such as roof area, building height, orientation, surface area, wall area, and glassing area distribution. Specifically, we sought to determine whether models that derive rules are competitive in terms of performance when compared with other classification techniques for assessing the energy efficiency of buildings, in particular the associated heating and cooling loads. To achieve this aim, several ML techniques including k-nearest neighbor (kNN), Decision Tree (DT)-C4.5, naive Bayes (NB), Neural Network (Nnet), Support Vector Machine (SVM), and Rule Induction (RI)- Repeated Incremental Pruning to Produce Error (RIPPER) were modelled and then evaluated based on residential data using a range of model evaluation parameters such as recall, precision, and accuracy. The results show that most classification techniques generate models with good predictive power with respect to the heating or cooling loads, with better results achieved with interpretable classifiers such as Rule Induction (RI), and Decision Trees (DT). Full article

This paper presents a concept of a routing algorithm for a network of sensors monitoring the condition of machinery and equipment operating in areas at risk of methane and/or coal dust explosion. It was assumed that the proposed algorithm would find application in sensor networks monitoring, among other things, oil pressure in powered roof supports and the position of powered roof support elements. The results of a literature analysis were presented, which included the simulation of sensor network routing algorithms, including, among others, reactive algorithms, proactive algorithms and algorithms based on so-called swarm intelligence (SI). As a result of the analyses, several algorithms were selected and implemented in a prototype sensor network. The characteristics of each of these algorithms are described. The article includes a description of the commissioning work of the network, which consisted of between 3 and 30 nodes. An analysis of the collected measurement data obtained for each criterion of the performance evaluation of the routing algorithms is presented. Full article

The underground mining environment is currently based on technology that uses mainly analogue sensors in machine and equipment control systems. The primary machine performing the most important functions in a mining system is the powered roof support. In order for it to work properly, it is important that it achieves the required power. To ensure this, it is necessary to continuously and precisely monitor the pressure in the under-piston space of the prop. Due to the extreme environmental conditions, pressure sensors should have high sensitivity, large transmission capacity, small size and light weight. To achieve these requirements, the authors of the article propose to implement a monitoring system based on photonics technology. To achieve this goal, several studies were carried out. The range of these studies included simulations, bench tests and tests under real conditions. The obtained test results showed the possibility of developing the control system for the powered roof support, the additional function to supercharge power. Based on the analysis of the obtained test results, assumptions were developed for the development of a power charging system with monitoring sensors. Based on the guidelines obtained from the research results, thedevelopment of the above prototype based on photonics technology is proposed. Full article

This paper presents a system for measuring the geometry of powered roof support sections (Shield Support Monitoring System, SSMS). The problem of measuring the geometry of powered roof support sections for the purpose of predicting geological hazards during the rock excavation process is presented. Information on the construction and implementation of the SSMS and research at the Budryk Mine is included. The research aimed to evaluate both the precision and accuracy of the measurement apparatus created, as well as to examine how operating conditions affect the system’s usability. An analysis of inclinometer measurement errors in the prototype system was conducted during in situ tests, demonstrating minimal scattering and high sensor accuracy according to the provided data. Full article

The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high. In this study, an extreme point extraction method was developed for the determination of the characteristic parameters of safety valves using roof pressure data, and a safety valve state monitoring module was constructed. Using the longwall face of 0116³06 with top coal caving in the Mindong Mine as an example, the characteristic parameters of the safety valves were extracted, including the peak, reseating, and blowdown pressures, as well as the recovery and unloading durations. The results of the field tests showed the following: (1) The amplitude threshold method based on extreme points can be used to accurately extract characteristic parameters, and the distribution of the characteristic parameters of the safety valves follows either a Gaussian or an exponential distribution. (2) The mining pressure analysis results, derived from the characteristic parameters, closely align with the in situ mining pressure observations. This method can be used for the online monitoring of safety valve conditions, increasing the operational efficiency and quality of safety valve inspections. Full article

The powered roof support in a mining complex protects machines and people from the harmful effects of the rockmass. The design of the powered roof support should be strictly prepared for adverse working conditions. This especially applies to the construction of the hydraulic actuator, which is designed to transfer uncontrolled load relief. The hydraulic actuators and an adequately selected safety valve determine the requirements for safe work. The study analyses the hydraulic actuators based on the signal obtained from the dynamic impact. The signal obtained from the load of the powered roof support in the bench tests allowed us to determine the opening time of the safety valve, which is not much different than the time of the pressure increase. Until now, the valve’s operation has been primarily analysed regarding pressure increase. This research was intended to determine whether introducing the sound power method for developing powered roof support research in the near future would be helpful. The sub-piston pressure increased during bench testing, generating a dynamic impact signal. The analysed results of the sound power tests in terms of their suitability for the development of standards related to powered roof support. This paper describes a new approach to research on powered roof support. Determining the acoustic power based on bench tests for the hydraulic actuator of a powered longwall support is ground-breaking research. The research results pave the way for new technologies based on acoustic information. Full article

To study the deformation and failure mechanisms of soft rock mining roadways, the 1506 return airway of Anyang Coal Mine is taken as the engineering background. Based on limit analysis theory, a failure model based on a rigid slider system is constructed to assess the failure of the soft rock surrounding a roadway. The formulas for calculating the self-weight power of the slider in the velocity discontinuity line of the rock surrounding the roadway, the work power of the surrounding rock pressure, and the energy dissipation rate of the velocity discontinuity line are derived, and the upper limit objective function of the velocity discontinuity line height is obtained. The failure characteristics and fracture evolution process of the surrounding rock under different mining stresses are analyzed by means of physical similarity simulations. The simulation results show that shear failure occurs first on the roadway side due to stress concentration. The fissures expand along the bottom angle of the roadway to the blind support area and the low-intensity support area. The cracks weaken the support strength of the angled anchor cable and bolt in the roadway shoulder. Under the action of roof pressure, the status of the rock mass inside and outside the shear slip zone changes from static to dynamic. This causes deformation and failure of the roadway roof, side, and floor. Full article