Search Results (75)

Water towers are historically significant hydraulic infrastructures that evolved from simple masonry structures to technologically advanced and architecturally expressive forms. This study presents a typological and material analysis of water towers, focusing on their construction techniques, durability, and potential for adaptive reuse. The research combines visual inspection, archival and bibliographic research, and photographic documentation, of selected European and Italian examples for comparative insights on design and materials choices. Data were collected and organized according to parameters such as construction materials, structural type, tank and roof form, access system, and current function. Assessments were conducted following the UNI EN 16096, providing a structured framework to evaluate heritage value, material conditions, and adaptive reuse potential. Main results demonstrate that water towers, beyond their original hydraulic function, retain significant technical, architectural, and cultural value, offering opportunities for adaptive reuse as cultural, educational, residential, or community spaces. Key findings identify material vulnerabilities, structural challenges (including wind, seismic, and thermo-hygrometric effects), and possibilities for sustainable interventions that respect historical authenticity. The study highlights how systematic typological assessment and documentation can guide evidence-based conservation and support innovative reuse strategies, integrating heritage preservation with urban regeneration and community engagement. Water towers exemplify the intersection of engineering, architecture, and cultural heritage, and their conservation requires a multidisciplinary approach between technical performance, material preservation, and socio-cultural significance. Finally, the implemented procedure is proposed as a methodological framework replicable and scalable for assessing similar infrastructures in other contexts. Full article

The chicken farm is a specific type of agricultural site with high electricity and heat consumption, which makes it ideal for the implementation of green energy. The specificity of the farm (need for continuous ventilation, lighting, and heating) allows achieving energy independence and reducing costs. Small farms can meet their own electricity needs using clean energy through the application of photovoltaics and converting waste biomass to usable energy. These two ways of power production could also reduce carbon footprints. In this study, the feasibility of using renewable energy for energy management in a poultry farm by consecutively involving solar and biomass energy was revealed. A biotechnological process for the production of biogas from chicken litter in a continuously stirred system of tank bioreactors was performed. It was supplied by electricity from a photovoltaic system. To obtain the maximum amount of solar energy, a photovoltaic system consisting of four panels, invertor and a battery with smart control was designed to collect, store, and bring energy to the reactor system collector and connected to the laboratory bioreactor, conveying the biogas production process. Several hydraulic retention times (HRT) were tested for optimizing biogas (biomethane) production, reaching a maximum of 575.49 NmL CH₄/dm³ at an HRT of 13.3 days for the first bioreactor and 278.7 NmL CH₄/g VS_add at an HRT of 120 days for the whole system. The energy balance made, reporting meteorological data, showed the economic feasibility for small farms to meet their own electricity needs. Involving renewable energy technologies could solve the problem of fossil fuel dependency and waste management for environmental protection and profit increase. It would permit a transition toward sustainable energy practices in agriculture and food production. Full article

Anaerobic digestion (AD) is a proven and promising technology for recovering energy from biowastes, such as pig slurry (PS) from the fattening/finishing phase. The mechanisms of AD are widely studied, and nowadays, it is of the utmost importance to investigate strategies that give end-users the confidence to choose this technology and to adapt it to their reality, promoting the energy transition and circular economy. This study investigated how collection and storage period affect PS samples, and how hydraulic retention time (HRT) (15 versus 20 days) influences AD performance and stability. Seasonality was the primary factor influencing feedstock characteristics. Samples presented no significant differences during the storage period. A 20-day HRT led to higher digestate pH, total ammonia nitrogen (TAN), and free ammonia nitrogen (FAN) concentrations, which can cause process instability and methanogenesis inhibition. However, 20-day HRT led to a specific methane production that was 7% higher and to a methane quality (expressed in % v/v CH₄) that was 6% higher than 15-day HRT. Overall, methane quality, digestate pH, TAN, and FAN values may be considered key points that need to be monitored to prevent the AD system from being compromised. Nevertheless, these results provide the operational freedom to choose either HRT, allowing reduced reactor volume and investment. Full article

To address the technical challenge where traditional high-pressure, large-flow emulsion pump stations cannot adapt to the drastic flow rate changes in hydraulic supports due to the fixed displacement of their quantitative pumps—leading to frequent system unloading, severe impacts, and damage—this study proposes an intelligent flow control method based on the digital flow distribution principle for actively perceiving and matching support demands. Building on this method, a compact, electro-hydraulically separated prototype with stepless flow regulation was developed. The system integrates high-speed switching solenoid valves, a piston push rod, a plunger pump, sensors, and a controller. By monitoring piston position in real time, the controller employs an optimized combined regulation strategy that integrates adjustable duty cycles across single, dual, and multiple cycles. This dynamically adjusts the switching timing of the pilot solenoid valve, thereby precisely controlling the closure of the inlet valve. As a result, part of the fluid can return to the suction line during the compression phase, fundamentally achieving accurate and smooth matching between the pump output flow and support demand, while significantly reducing system fluctuations and impacts. This research adopts a combined approach of co-simulation and experimental validation to deeply investigate the dynamic coupling relationship between the piston’s extreme position and delayed valve closure. It further establishes a comprehensive dynamic coupling model covering the response of the pilot valve, actuator motion, and backflow control characteristics. By analyzing key parameters such as reset spring stiffness, piston cylinder diameter, and actuator load, the system reliability is optimized. Evaluation of the backflow strategy and delay phase verifies the effectiveness of the multi-mode composite regulation strategy based on digital displacement pump technology, which extends the effective flow range of the pump to 20–100% of its rated flow. Experimental results show that the system achieves a flow regulation range of 83% under load and 57% without load, with energy efficiency improved by 15–20% due to a significant reduction in overflow losses. Compared with traditional unloading methods, this approach demonstrates markedly higher control precision and stability, with substantial reductions in both flow root mean square error (53.4 L/min vs. 357.2 L/min) and fluctuation amplitude (±3.5 L/min vs. ±12.8 L/min). The system can intelligently respond to support conditions, providing high pressure with small flow during the lowering stage and low pressure with large flow during the lifting stage, effectively achieving on-demand and precise supply of dynamic flow and pressure. The proposed “demand feedforward–flow coordination” control architecture, the innovative electro-hydraulically separated structure, and the multi-cycle optimized regulation strategy collectively provide a practical and feasible solution for upgrading the fluid supply system in fully mechanized mining faces toward fast response, high energy efficiency, and intelligent operation. Full article

The exploitation of hydrokinetic resources represents a sustainable and efficient alternative for renewable energy generation. This study presents the design and real-world implementation of a compact hydrokinetic system capable of converting rainwater runoff into electricity within smart homes. Unlike conventional large-scale hydrokinetic technologies, this system was specifically engineered for intermittent, low-flow conditions typical of residential rainwater collection networks. The turbine was manufactured using 3D-printed biodegradable materials to promote environmental sustainability and facilitate rapid prototyping. Through CFD simulations and laboratory testing, the system’s hydraulic behaviour and energy conversion efficiency were validated across different flow scenarios. The complete system, consisting of four turbines rated at 120 W each, was integrated into a real smart home without structural modifications. From an academic perspective, this study contributes a quantitatively validated hybrid hydrokinetic–low-head framework for residential rainwater energy recovery, addressing intermittent and low-flow urban conditions insufficiently explored in existing literature. Field tests demonstrated that the hydrokinetic system provides complementary energy during rainfall events, generating up to 6000 Wh per day and enhancing household energy resilience, particularly during periods of low solar availability. The results confirm the technical feasibility, sustainability, and practical viability of decentralized hydrokinetic energy generation for residential applications. Full article

The distribution of water in urban areas involves several challenges, such as maintaining pipelines, controlling pressure and flow, and monitoring water quality. In particular, the measurement of the flow rate and pressure in pipelines is essential for optimizing water distribution in cities. In recent decades, new technologies have been used to address these challenges, such as hydraulic modeling systems with software, smart sensors, and automated control systems. Among the new possibilities, the use of wireless sensor networks has been highlighted. In this sense, IoT-based nodes have been proposed as a low-cost alternative, with the ability to communicate over the Internet with low energy consumption. Thus, this work describes the necessary steps, challenges, and solutions for the development of an autonomous IoT node applicable to monitoring pressure and flow in a water supply network. In the second part of the work, the data collected by the IoT nodes was processed to eliminate outliers and used to train a model based on artificial neural networks that are capable of predicting the flow in the system under monitoring. The results show that, based on the data measured by the proposed IoT node, it is possible to predict the flow in distribution systems operating in real time. Full article

Total knee replacement (TKR) is a reliable treatment for end-stage degenerative conditions of the knee. Patient-reported outcome measures (PROMs) are central to assessing TKR outcomes, but they have limitations. Activities of daily living (ADLs) in the early post-operative period complement PROMs for holistic patient assessment. This study presents a method for capturing ADL parameters from data generated by inertial measurement unit (IMU) devices embedded in TKR prosthesis. A conventional posterior stabilized TKR was modified to create chambers in the femoral and tibial components. The prosthesis was implanted into a cadaver knee and movement was simulated using a hydraulic actuated knee simulator (AMTI, VIVO, MA, USA). A powered IMU device was placed in each of the chambers. The simulator was activated for various ADLs and the generated data was collected wirelessly. The pre-processed data was fed into a novel multimodal deep learning artificial intelligence model created to recognize specific ADL (trained on 70% of the data, with 30% reserved for validation and testing). The model achieved 95.68% overall accuracy, with 100% for sitting, standing, stance, and knee bending. Walking, stair navigation, and jogging showed F1 scores of 0.98, 0.92, 0.91, and 0.89, respectively. This technology enables seamless knee activity recognition and reporting with positive implications for patient-specific rehabilitation protocols. Full article

Anaerobic digestion (AD) technology is universally acknowledged as the most economically viable and efficient approach for energy recovery from livestock manure. To validate the efficacy of riboflavin-functionalized carbon-based conductive materials (CCM-RF) in enhancing methane production at pilot scale, three pilot-scale upflow anaerobic sludge blanket (UASB) reactors were constructed and separately supplemented with carbon cloth (CC), granular activated carbon (GAC), and a combination of CC and GAC. During reactor initialization, riboflavin and a concentrated inoculum of Methanosarcina barkeri (M. barkeri) were introduced to investigate the mechanistic role of CCM-RF in promoting direct interspecies electron transfer (DIET) and optimizing treatment efficiency during anaerobic digestion of cattle manure wastewater. The results showed that all reactors improved AD performance and maintained stable operation at the OLR of 15.66 ± 1.95 kg COD/(m³·d), with a maximum OLR of 20 kg COD/(m³·d) and the HRT as short as 5 days. Among the configurations, the CC reactor outperformed the others, achieving a methane volumetric yield of 6.42 m³/(m³·d), which represents an eight-fold increase compared to conventional AD systems. Microbial community analysis revealed that, although M. barkeri was initially inoculated in large quantities, Methanothrix—a methanogen with DIET capability—eventually became the dominant species. The enrichment of Methanothrix and the simultaneous enhancement in sludge conductivity collectively verified the mechanistic role of CCM-RF in promoting CO₂-reductive methanogenesis through strengthened DIET pathways. Notably, M. barkeri showed progressive proliferation under conditions of high organic loading rates (OLR) and short hydraulic retention time (HRT). This phenomenon provides a critical theoretical basis for the development of future strategies aimed at the targeted enrichment of Methanosarcina-dominant microbial consortia. Full article

A high-precision coal seam model is crucial to improving the adaptability of unmanned mining technology to geological conditions. However, the accuracy of a coal seam model constructed with boreholes and geophysical data is far from the required accuracy of unmanned mining (sub-decimeter level). Therefore, it is necessary to collect geological data revealed by mining and to update the coal seam model dynamically. As a solution to this problem, this paper proposes a new method for conducting off-site geological surveying of longwall faces by integrating multi-source monitoring data. The spatial attitudes of hydraulic supports are monitored to estimate the local dip angles of longwall face. A roof line calculation model was established, which integrates the local inclination angle of the longwall face, the number of hydraulic supports, and the roof elevation of the two roadways. Meanwhile, the local coal–rock columns at the camera observation point are extracted automatically using image segmentation and a proportional relationship between the picture and the actual scene. Coal and rock walls and a support guarding plate in the longwall face image are identified accurately using the coal-rock support segmentation model trained with U-net. Then, the height of the coal (or rock) wall above the coal–rock interface is estimated automatically according to the image segmentation and the similar proportion equation of actual longwall face and longwall face image. Combined with mining height information, the local coal–rock column can be extracted. Finally, the geological surveying profile of longwall face can be obtained by integrating the estimated roof line and local coal–rock columns. The field test demonstrated the efficacy of the method. This study helps to address a long-standing limitation of insufficient geological adaptability of intelligent mining technology. Full article

The development of unconventional oil and gas resources highly relies on hydraulic fracturing technology, and the fracturing effect directly affects the level of oil and gas recovery. Carrying out fracturing evaluation is the main way to understand the fracturing effect. However, the current fracturing evaluation methods are usually carried out after the completion of fracturing operations, making it difficult to achieve real-time monitoring and dynamic regulation of the fracturing process. In order to solve this problem, an intelligent prediction method for fracture propagation based on the attention mechanism and Long Short-Term Memory (LSTM) neural network was proposed to improve the fracturing effect. Firstly, the GOHFER software was used to simulate the fracturing process to generate 12,000 groups of fracture geometric parameters. Then, through parameter sensitivity analysis, the key factors affecting fracture geometric parameters are identified. Next, the time-series data generated during the fracturing process were collected. Missing values were filled using the K-nearest neighbor algorithm. Outliers were identified by applying the 3-sigma method. Features were combined through the binomial feature transformation method. The wavelet transform method was adopted to extract the time-series features of the data. Subsequently, an LSTM model integrated with an attention mechanism was constructed, and it was trained using the fracture geometric parameters generated by GOHFER software, forming a surrogate model for fracture propagation. Finally, the surrogate model was applied to an actual fracturing well in Block Ma 2 of the Mabei Oilfield to verify the model performance. The results show that by correlating the pumping process with the fracture propagation process, the model achieves the prediction of changes in fracture geometric parameters and Stimulated Reservoir Volume (SRV) throughout the entire fracturing process. The model’s prediction accuracy exceeds 75%, and its response time is less than 0.1 s, which is more than 1000 times faster than that of GOHFER software. The model can accurately capture the dynamic propagation of fractures during fracturing operations, providing reliable guidance and decision-making basis for on-site fracturing operations. Full article

Vertical low-permeability barriers are widely used to improve the stability and seepage resistance of flood embankments. The present study evaluates three barrier technologies—vibrating beam slurry walls (VBSWs), deep soil mixing (DSM), and low-pressure grout injection (LPG)—through a series of consolidated drained triaxial tests and permeability coefficient tests on soil samples collected from the sites where different barrier installation technologies were used. All three barrier installation methods produced substantial improvements in both mechanical and hydraulic performance: the effective angle of internal friction (φ′) increased by 3–6° in samples with a plasticity index near 3.5%, and coefficients of permeability dropped from 10⁻⁸–10⁻⁷ m/s in untreated soils to below 10⁻⁹ m/s in treated specimens. The key finding of the study is that the barrier performance varies by the technology and the soil type. According to the result, DSM is the most effective technology used in clay-rich soils (φ′ increased up to 4°); LPG achieved the lowest permeability (7 × 10⁻¹¹ m/s) in granular soils; and VBSWs balanced strength and impermeability, most effective in silty sands. Flow-pump tests further demonstrated that treated soils required much longer to stabilize under a constant flow rate and could sustain higher hydraulic gradients before reaching equilibrium. These findings show the importance of matching barrier technology to soil plasticity and liquidity characteristics and highlight saturation as essential for reliable laboratory evaluation. The results provide a scientific basis for selecting and designing vertical barriers in flood-preventing infrastructure, offering performance benchmarks for improving hydraulic and geotechnical structures. Full article

Effective water resource management plays a crucial role in achieving sustainability in agriculture, hydrology, and environmental protection, particularly under growing water scarcity and climate-related challenges. Soil moisture (θ), matric potential (h), and hydraulic conductivity (K) are critical parameters influencing water availability for crops and regulating hydrological, environmental, and ecological processes. To address the need for accurate, real-time soil monitoring in both laboratory and open-field conditions, we proposed an innovative IoT-based monitoring system called SHYPROM (Soil HYdraulic PROperties Meter), designed for the simultaneous estimation of parameters θ, h, and K at different soil depths. The system integrates capacitive soil moisture and matric potential sensors with wireless communication modules and a cloud-based data processing platform, providing continuous, high-resolution measurements. SHYPROM is intended for use in both environmental and agricultural contexts, where it can support precision irrigation management, optimize water resource allocation, and contribute to hydrological and environmental monitoring. This study presents recent technological upgrades to the proposed monitoring system. To improve the accuracy and robustness of θ estimates, the capacitive module was enhanced with an integrated oscillator circuit operating at 60 MHz, an upgrade from the previous version, which operated at 600 kHz. The new system was tested (i.e., calibrated and validated) through a series of laboratory experiments on soils with varying textures, demonstrating its improved ability to capture dynamic soil moisture changes with greater accuracy compared to the earlier SHYPROM version. During calibration and validation tests, soil water content data were collected across a θ range from 0 to 0.40 cm³/cm³. These measurements were compared to reference θ values obtained using the thermo-gravimetric method. The results show that the proposed monitoring system can be used to obtain predictions of θ values with acceptable accuracy (R² values range between 0.91 and 0.96). To further validate the performance of the upgraded SHYPROM system, evaporation experiments were also conducted, and the θ(h) and K(θ) relationships were determined among soils. Retention and conductivity data were fitted using the van Genuchten and van Genuchten–Mualem models, respectively, confirming that the device accurately captures the temporal evolution of soil water status (R² values range from 0.97 to 0.99). Full article

The heritage of public works is composed of networks that are strongly linked to the territory where they are built. With the aim of deepening our knowledge of the appearance and subsequent development of the transport and supply systems in Madrid, we present a study of the main hydraulic works, bridges and railway stations. Based on historical and technological documentation, works and networks are analysed and georeferenced in order to relate their traces and evolution to the city. These built elements define recognisable physical and cultural traces in the form and identity of the city. The documentation and technological and social analysis work was completed with a dissemination and heritage education process. The results show that the physiographic and lithological reality of Madrid, characterised by its intense link with water, has determined the configuration of the urban network and the expansion of the city. Bridges span obstacles and set milestones. Stations are spaces for exchange and connection. The water supply network feeds the urban grid. The city changes, but the traces remain. Urban growth has smoothed, absorbed or hidden the original relief and watercourses, but they are still present in public works and even in the collective memory of the citizens through the force of their cultural and social values. Full article

Hydraulic fracturing technology has been extensively applied for the efficient development of unconventional reservoirs. Influenced by geological discontinuities such as naturally fractured weak planes, the complex interaction behaviors between hydraulic fractures and natural fractures significantly challenge the prediction of hydraulic fracture propagation paths. Establishing interaction discrimination models to predict these behaviors proves crucial for characterizing post-stimulation fracture complexity. This study develops a discrimination model for hydraulic-natural fracture interactions based on fracture mechanics theory and energy balance principles. The critical conditions of hydraulic fracture crossing, natural fracture opening, and slippage are quantified, and the interaction propagation behavior of hydraulic fracture and natural fracture under different geological parameters is analyzed. Key findings reveal three interaction modes after fracture intersection: direct hydraulic fracture crossing, natural fracture opening, and natural fracture slippage. However, continuous fluid injection-induced pressure buildup within fractures ultimately drives hydraulic fracture crossing through natural fractures. Threshold effects emerge at specific hydraulic fracture lengths (0.5 m) and fracture toughness values (2 MPa·m^0.5), governing the transition between direct crossing and natural fracture opening behaviors. Horizontal stress difference directly modulates the threshold values of natural fracture cohesion, friction coefficient, and approach angle. These three parameters collectively control the temporal sequence of hydraulic fracture crossing behaviors through natural fractures. The interaction discrimination model established in this study provides theoretical guidance for optimizing fracturing parameter design in fractured reservoirs. Full article

The hydraulic support is one of the most crucial pieces of equipment at the working face. To achieve the intelligentization of the attitude-monitoring system, we have designed and developed a Fiber Bragg Grating (FBG) inclinometer for the hydraulic support. This innovation offers a brand-new monitoring tool and approach for measuring the attitude angle of the hydraulic support. The FBG inclinometer for the hydraulic support integrates passive grating sensing technology with an inclination force element. It not only fulfills the inclination measurement function but also employs passive sensing technology, rendering it safer and more reliable compared to electromagnetic inclinometers. First, we delved into the sensing principle of the grating based on its structure, and investigated its sensing characteristics under uniform axial stress and temperature variations. We analyzed the strain–temperature cross-sensitivity issue and applied a temperature compensation technique. Second, we carried out a novel structural design and proposed two design alternatives: the cantilever beam type was selected after a comprehensive comparison. Subsequently, we deduced the corresponding theoretical formulas and ultimately adopted the temperature compensation method using an unstressed reference grating. Finally, on-site verification was conducted on the hydraulic support in the general mining face of Delong Mine, and the FBG inclinometer successfully passed the test. Finally, an actual test was carried out at the Delong Coal Mine site, and the subsequent use yielded quite satisfactory results. An analysis of the data collected on-site by the FBG inclinometer for the hydraulic support revealed that the newly developed FBG inclinometer for the hydraulic support can be effectively applied in the field of intelligent monitoring in underground coal mines. The monitoring data can serve as a reliable data foundation for assessing the operating attitude of the hydraulic support. This indicates that the FBG inclinometer is highly suitable for wide-scale industrial applications. Full article