Search Results (103)

Ultrasonic inspection of welded steel components remains challenging due to weld-scale material gradients, local anisotropy, attenuation, and aperture limitations. These factors severely distort both the first-arrival wavefield and the late-arriving scattered wavefield. To address this, this study presents a numerical proof of concept for three-dimensional cross-weld virtual-array coda-wave tomography (VACWT). The “virtual array” utilizes a synthetic aperture created by re-indexing sequential source–receiver records from two opposing line scans into midpoint–angle–depth coordinates. This approach enables line-based data acquisition to achieve multi-angle volumetric coverage without requiring a two-dimensional matrix array. A parameterized welded-solid benchmark model was developed, incorporating effective longitudinal and shear wave velocities, attenuation, and out-of-plane tilt fields. Four defect scenarios were evaluated: a cylindrical void, a lack-of-fusion ribbon, a porosity cluster, and an interference case. For each source–receiver path, four observables were extracted from the synthetic records: first-arrival travel time perturbations, coda wave stretching, coda decorrelation, and late-window energy ratios. These observables were then coupled into a volumetric inverse problem to separate smooth slowness variations, distributed scattering strength, and compact defect occupancy. Under the current simulation conditions, VACWT achieved smaller recovered support volumes and higher volumetric overlap compared to the delay-and-sum total focusing method (DAS-TFM), background-corrected TFM, and reverse time migration (RTM). In the interference case, applying a fixed defect-free calibration threshold yielded a centroid error of 0.48 mm, a volumetric intersection over union (IoU) of 0.856, and a false-positive volume fraction of 0.0%. While these findings serve as benchmark results rather than generalized experimental validation, the study demonstrates that late scattered wave observables provide valuable constraints for volumetric support recovery in a controlled welded-solid model. Future experimental verification on welded steel specimens with known defects remains necessary. Full article

The transition toward renewable energy sources has become a critical global objective. For developing nations facing the dual challenges of inefficient waste management and limited energy access, waste-to-energy (WTE) technologies offer a transformative solution to mitigate environmental concerns while enhancing power grid stability. This paper presents a detailed performance analysis of a proposed WTE thermal power plant for Dire Dawa City, Ethiopia, utilizing municipal solid waste (MSW) as a sustainable feedstock. The primary objective of this study is to estimate the power generation potential of the city’s MSW through thermal incineration integrated with a Rankine Vapor Cycle. Field data collection reveals that Dire Dawa City produces an average of 237.2 tons of waste daily, with a per capita generation rate of 0.49 kg. Laboratory characterization indicates that the waste possesses high energy potential, featuring an average calorific value of 18.20 MJ/kg (18.20 × 10³ kJ/kg), a volatile matter content of 73.50%, and fixed carbon at 19.18%. Thermodynamic modeling and energy-flow simulations demonstrate that the facility can achieve a power output ranging from 7.64 MW to 22.80 MW, providing a nearly constant total energy yield of approximately 183,360 kWh per day. These results confirm that Dire Dawa City’s waste stream is a potent strategic resource for renewable energy. Ultimately, this research provides a technical roadmap for stakeholders, facilitating informed investment decisions and resource planning to ensure the successful implementation of sustainable thermal energy infrastructure in the region. Full article

Agriculture currently faces multiple challenges associated with climate change, the reduction in arable land, and the need to produce food more efficiently in terms of water and nutrient use. This study evaluated an Internet of Things (IoT)-based hydroponic monitoring system with threshold-controlled recirculation for lettuce (Lactuca sativa) under open-field thermal stress conditions, comparing it with a conventional closed recirculating PVC pipe-based hydroponic system operated using fixed pump timing. The architecture integrated an ESP32 microcontroller, sensors for nutrient solution temperature, pH, total dissolved solids (TDS), turbidity voltage, dissolved oxygen (DO), and electrical conductivity (EC), Wi-Fi/HTTPS connectivity, a PHP–MySQL server, and a web interface for near-real-time monitoring. During the growing period, 241,797 readings were recorded between 21 January and 13 February 2026. The threshold-based logic activated the pump mainly according to nutrient solution temperature and DO, while pH, EC, TDS, and relative turbidity voltage were monitored as operational indicators. The sensor-instrumented system operated with pump activation during approximately 28.5% of the monitoring period, while temperature exhibited high variability and peaks of 40.19 °C. Visual crop monitoring showed greater canopy uniformity in the sensor-instrumented system, supporting the technical feasibility of low-cost IoT-based monitoring and threshold-controlled recirculation for open-field hydroponic production of lettuce. Full article

With the large-scale integration of offshore wind farms (OWFs), harmonic issues caused by the interaction between high-frequency switching of converters and complex network impedances pose severe challenges to power quality. Traditional harmonic monitoring heavily relies on post-event fixed-threshold alarm mechanisms, which struggle to achieve early warning during the low-distortion sub-health operation stage and lack the capability for multi-dimensional tracing of harmonic degradation sources. To address these limitations, this paper proposes a deep warning network for grid harmonics combining multi-step regression and multi-dimensional tracing within a unified multi-task learning (MTL) architecture. First, a deep shared feature encoder, integrating a bi-directional long short-term memory (Bi-LSTM) network with a multi-head self-attention (MHSA) mechanism, is utilized to extract high-order temporal coupling features between meteorological evolution and multi-node electrical states. Subsequently, the main task branch executes a k-step-ahead multivariate time-series regression to accurately predict the evolution trend of total harmonic distortion (THD) at both the point of common coupling (PCC) and the turbine terminal. Simultaneously, the auxiliary task branch performs multi-label micro-state classification based on relative degradation thresholds, achieving fine-grained multi-dimensional tracing covering spatial nodes, electrical attributes, and their joint micro-states. Experimental results on real-world OWF operational data demonstrate that through the joint optimization of regression and tracing tasks, the proposed MultiDimKStepMTL model significantly improves time-series prediction accuracy, achieving a $10.3\%$ relative improvement over single-task baselines, while substantially reducing computational overhead. This research successfully advances grid harmonic monitoring from passive response to proactive micro-state early warning, providing a solid, highly interpretable data-driven foundation for active filter control of offshore wind clusters. Full article

This study evaluated spatial and seasonal patterns of physicochemical water quality in the Chiriquí Viejo River basin (western Panama), a tropical watershed characterized by strong seasonal variability. A total of 90 water samples were collected at ten stations during the rainy season (May to October 2024) and dry season (January to March 2025). Dissolved oxygen (DO), turbidity, potential of hydrogen (pH), apparent color, total dissolved solids (TDS), and electrical conductivity (EC) were analyzed following ISO/IEC 17025:2017 accredited methods, and precipitation patterns were characterized using spatial interpolation of meteorological data. Spatio-temporal variability was assessed using linear mixed-effects models, with season and basin position as fixed effects and sampling site as a random factor. Results showed a spatial and seasonal structuring of water quality, with the upper basin exhibiting high and stable DO concentrations and low turbidity and apparent color. In contrast, the middle and lower basin showed rainy-season increases in turbidity and apparent color, supported by a significant season × basin interaction, indicating that precipitation driven impacts are heterogeneous along the basin. EC and TDS displayed spatial gradients, while DO remained relatively stable across seasons and basin levels. These findings highlight turbidity and apparent color as sensitive indicators of precipitation-driven impacts. Full article

Background/Objectives: For hyperlipidemic patients with statin resistance, a fixed-dose combination of a non-statin drug such as ezetimibe (EZT) and bempedoic acid (BA) provides a significant benefit. Although both drugs exhibit poor aqueous solubility, the oral bioavailability of EZT is more critically limited by dissolution, whereas BA maintains adequate absorption due to its high intestinal permeability. With regard to the reference product, Nexlizet^® (180/10 mg), our study focused on developing a novel tablet with superior in vitro performance without incorporating sodium lauryl sulfate (SLS), as it may potentially alter BA absorption. Methods: The solid dispersion technique (co-precipitation) was applied using the Kollidon^® VA64 polymer, and the solid state was characterized through differential scanning colorimetry (DSC), X-ray powder diffraction (XRPD), and Fourier transform infrared spectroscopy (FTIR). The prepared solid dispersions (SDs) were formulated into film-coated tablets (FCTs) and were characterized physically and for drug performance, and an animal model study was also conducted. Results: The solid-state analysis of the optimized SD formula (S30) revealed reduced drug crystallinity with no drug–carrier chemical interaction. The optimized formula (F30), a film-coated tablet, successfully achieved comparative in vitro dissolution versus Nexlizet^® and passed the accelerated stability study. Furthermore, in vivo evaluation revealed that F30 significantly reduced serum total cholesterol (TC), triglycerides (TG), and low-density lipoprotein (LDL), with an increase in high-density lipoprotein (HDL), in an animal model. Conclusions: These findings confirm that the SD technique is an effective one-step approach to co-formulating both APIs, simplifying manufacturing processes and optimizing the batch size. Full article

Southern New Jersey faces increasing flood risk due to several factors including rapid development, climate change, and aging infrastructure. This study evaluated the flood vulnerability of two municipal solid waste landfills located in Gloucester and Cumberland Counties. These sites are located near rural communities that rely on shallow groundwater for drinking water, which may be contaminated by floods. To assess these challenges, this research applies a hydrologic–hydraulic model to evaluate future flood vulnerability at the Cumberland County Improvement Authority (CCIA) landfill and the Gloucester County Solid Waste Complex (GCSWC) landfill. The method uses HEC-HMS and HEC-RAS 2D model simulations with climate-adjusted precipitation data derived from global climate models. Model performance was evaluated using Hurricane Ida (31 August–2 September 2021) by comparing HEC-RAS-simulated inundation extents with independently derived Sentinel-1 SAR flood maps generated in Google Earth Engine. Climate forcing was developed by deriving climate-adjusted 24 h precipitation–frequency (PF) design depths for 50-year and 100-year design storms under the Shared Socioeconomic Pathway (SSP) emissions pathways SSP2-4.5 (moderate) and SSP5-8.5 (high) for mid-century (2025–2050) and late-century (2070–2100) periods. These PF storm totals were converted to rainfall hyetographs using a fixed alternating variability method (AVM) temporal pattern within the coupled HEC-HMS/HEC-RAS modeling chain. Hazard amplification was primarily expressed through lateral inundation expansion and longer persistence of shallow flooding in low-relief operational zones, rather than uniform increases in peak depth across landfill interiors. Across both facilities, the landfill toe and adjacent access corridors were consistently identified as the most sensitive operational areas. Full article

Rootstock strongly influences citrus tree performance, but information remains limited for some regionally important cultivars. ‘IAPAR 73’, an early-season sweet orange commonly grown in Paraná, Brazil, has not been previously evaluated for rootstock responses. This study assessed the long-term effects of nine rootstocks, including ‘Rangpur’ lime, ‘Swingle’ citrumelo, ‘Volkamer’ lemon, ‘Caipira DAC’ and ‘Trifoliate’ oranges, ‘Cleopatra’ and ‘Sunki’ mandarins, ‘Carrizo’ and ‘Fepagro C-13’ citranges, on vegetative growth, yield, production stability, and fruit quality under Brazilian subtropical conditions. Tree growth was monitored annually for 10 years (2003–2013) and analyzed at establishment (5 years) and full production (10 years) phases of the orchard. Yield and fruit quality were evaluated across multiple harvests, and total soluble solids (TSS) stability was quantified using the coefficient of variation. Rootstock effects were analyzed using linear mixed-effects models in a randomized complete block design, considering rootstock and year as fixed effects and blocks as random effects. Rootstock significantly influenced all evaluated traits. ‘Carrizo’, ‘Cleopatra’, ‘Sunki’, and ‘Caipira DAC’ induced vigorous canopy growth and higher cumulative yields to the scion, while ‘Volkamer’ showed high yield efficiency and production stability. ‘Swingle’ and ‘Trifoliate’ enhanced TSS, TSS/TA ratios, and juice quality stability but induced lower vigor and yield, similar to ‘Rangpur’. This study provides the first evidence-based guidance for ‘IAPAR 73’ production, demonstrating that rootstock diversification can maximize productivity, stability, and sustainability in citrus orchards. Full article

Industrial synthetic and natural fibers play an indispensable role in modern manufacturing, aerospace, automotive, and textile engineering. However, the enhanced mechanical performance of advanced industrial fibers has introduced significant challenges in cutting processes, since brittle, high-tensile, and viscoelastic fibers exhibit totally different fracture behaviors from conventional solid materials. At present, the complex motion coupling mechanisms between fibers and cutting tools under free-form conditions are insufficient; there is no unified framework for understanding the mechanisms of fiber cutting; it is difficult to effectively link the microscopic fracture physics of different fiber types with their macroscopic cutting properties. Furthermore, research into the dynamic interaction between the cutting tool and the fiber, cross-scale cutting characteristics, and tool wear mechanisms has not been sufficiently systematic, and non-contact cutting methods have not yet been the subject of systematic study. Through a systematic review, this review identified three primary categories of difficult-to-cut industrial fibers and summarized the distinctions in their fundamental material properties. The static, kinematic, and dynamic characteristics of fiber cutting under both free and fixed forms were discussed. The fracture mechanisms of fibers under diverse loading scenarios were also systematically revealed. Furthermore, this review summarizes the effects of cutting tool wear characteristics, geometric parameters, and material types on cutting performance. Finally, non-contact methods for cutting fiber were listed. Based on the above analysis, three critical directions for future research were proposed to bridge the existing knowledge gaps in the literature. This review of the interdisciplinary interactions among mechanics, materials science, and textile engineering provides a theoretical foundation and research directions for achieving high efficiency and a long tool life during cutting industrial fibers. Full article

Intermittently operated, tankless reverse osmosis (RO) systems are widely used in decentralized and point-of-use applications, yet water stagnation during idle periods remains a critical challenge, leading to degraded water quality, accelerated fouling, and performance loss. This study presents an experimentally validated engineering solution that eliminates stagnant water in intermittently operated RO systems. A dual-membrane RO configuration with flexible series–parallel switching was developed, enabling membranes to alternate between production and flushing modes. An adaptive control strategy, integrated into the system hardware, regulates membrane switching and flushing based on real-time feed-water quality. The proposed configuration and control framework was evaluated under representative intermittent operating conditions. Experimental results show that the zero-stagnant-water strategy effectively prevents residual water accumulation during shutdown and maintains stable permeate quality, with total dissolved solids consistently below 10 mg/L. Long-term testing further demonstrates reduced membrane fouling and slower performance degradation compared with conventional fixed-operation schemes, resulting in enhanced desalination efficiency and operational stability. Owing to its modular design and simple control logic, the proposed approach is readily transferable to decentralized and point-of-use membrane water treatment systems requiring reliable, high-quality water under intermittent operation. Full article

Ion-exchange-based wastewater treatment processes exhibit nonlinear and time-varying dynamics, making the control of total dissolved solids (TDS) and water hardness a complex task. Conventional Proportional–Integral–Derivative (PID) controllers often show limited performance under such conditions due to fixed tuning parameters and linear assumptions. To address these limitations, this study presents a comparative evaluation of traditional and intelligent control strategies for regulating TDS and water hardness through influent flow control. A classical PID controller is compared with fuzzy logic and Adaptive neuro-fuzzy inference system (ANFIS) controllers using a unified MATLAB/Simulink simulation framework. The control performance is evaluated based on dynamic response characteristics, including rise time, settling time, and overshoot. For TDS control, the PID controller exhibits a rise time of 15.9 s and a settling time of 50.9 s, while the fuzzy logic controller improves the response with a rise time of 13.6 s and settling time of 44.1 s. The ANFIS controller achieves the fastest response, with a rise time of 8.31 s and a settling time of 27.1 s. Similar trends are observed for water hardness control, where the PID controller shows a rise time of 17.0 s and settling time of 55.8 s, the fuzzy logic controller reduces these values to 12.3 s and 40.4 s, respectively, and the ANFIS controller further improves performance with a rise time of 9.23 s and settling time of 30.3 s. The overshoot values for all controllers remain comparable, within the range of approximately 4.4–5.0%. The results clearly demonstrate that intelligent control strategies, particularly ANFIS, provide significantly faster convergence and improved dynamic performance compared to conventional PID control. The reduced settling time implies lower control effort and decreased energy consumption, highlighting the potential of intelligent controllers for efficient and reliable industrial wastewater treatment applications. Full article

The expansion of unconventional hydrocarbon extraction in the Vaca Muerta Formation (Argentina) has increased the generation of oil-based drill cuttings (OBDCs), a hazardous waste containing up to 20 wt% total petroleum hydrocarbons (TPHs) and trace metals. These characteristics pose risks to soil and groundwater, highlighting the need for sustainable treatment technologies that minimize environmental impacts and enable resource recovery. This study evaluates slow pyrolysis as a thermochemical route for OBDC stabilization and valorization. Representative samples were characterized through proximate, ultimate, and metal analyses, confirming a complex hydrocarbon–mineral matrix with 78.1 wt% ash, 15.9 wt% volatile matter, and 12.5 wt% TPH. Thermogravimetric analysis (10–20 °C min⁻¹), combined with isoconversional methods, identified three pseudo-components with activation energies ranging from 41.9 to 104.5 kJ mol⁻¹. Slow pyrolysis experiments in a fixed bed (400–650 °C) reduced residual TPH to below 1 wt% at temperatures ≥ 400 °C, meeting Argentine criteria for non-hazardous solids. The process also produced a condensed liquid organic fraction, supporting its potential within circular-economy strategies. Overall, the results show that slow pyrolysis is a viable and sustainable technology for reducing environmental risks from OBDC while enabling resource and energy recovery, contributing to a broader understanding of their thermochemical treatment. Full article

Organophilic acidic magadiites were prepared after an acidic magadiite (A-Mgd) reaction with cetyltrimethylammonium solutions containing different anions, such as cetyltrimethylammonium bromide (C16TMABr), cetyltrimethylammonium chloride (C16TMACl), and cetyltrimethylammonium hydroxide (C16TMAOH). The resulting materials were studied as adsorbents for Eosin Y removal from artificially contaminated solution. Successful preparation of oganophilic A-Mgd was achieved using C16TMAOH solution with an increased basal spacing from 1.21 nm to 3.15 nm and uptake C16TMA amount of 1.16 mmol/g. Meanwhile, no variation in the basal spacing of 1.20 nm occurred using C16TMACl and C16TMA Br solutions with an uptake mount of 0.07 to 0.09 mmol/g, respectively. Other techniques supported the behavior of the counteranion of surfactant solution on the synthesis of organophilic A-Mgd samples. 13C CP/MAS NMR data revealed that C16TMA cations displayed all-trans conformation comparable to C16TMABr solid, and ²⁹Si MAS NMR confirmed the stability of the host silicate layers during the reaction. The specific surface area of A-Mgd was reduced after the intercalation of C16TMA cations from 38 m²/g to 11 m²/g. The removal properties of organophilic samples were investigated under different conditions, including the Eosin Y pH solution, initial concentration, dosage mass, and content of C16TMA cations. The maximum removal amount was 70 mg/g at acidic pH and using A-Mgd prepared from C16TMAOH solution, while the other organophilic A-Mgds exhibited low removal amounts of 3 to 5 mg/g. The regeneration tests indicated that the efficiency was maintained after four reuse tests with a drop of 30 to 50% from the initial value after seven cycles. The adsorber batch design was employed to estimate theoretically the required masses of used samples to treat an effluent volume of 10 L at a removal percentage of 95% at a fixed initial concentration of 200 mg/L. In total, 20 g of organophilic prepared from A-Mgd and C16TMAOH solution was needed, while 243 g of sample prepared from C16TMABr solution was required. This study proposes the development of a cost-effective, sustainable solution for dye-contaminated wastewater treatment. Full article

Deep and ultra-deep drilling operations commonly encounter fractured and fracture-vuggy formations, where weak wellbore strength and well-developed fracture networks lead to frequent lost circulation, presenting a key challenge to safe and efficient drilling. Existing diagnostic practices mostly rely on drilling fluid loss dynamic models of single fractures or simplified discrete fractures to invert fracture geometry, which cannot capture the spatiotemporal evolution of loss in complex fracture networks, resulting in limited inversion accuracy and a lack of quantitative, fracture-network-based loss-dynamics support for bridge-plugging design. In this study, a geologically realistic wellbore–fracture-network coupled loss dynamic model is constructed to overcome the limitations of single- or simplified-fracture descriptions. Within a unified computational fluid dynamics (CFD) framework, solid–liquid two-phase flow and Herschel–Bulkley rheology are incorporated to quantitatively characterise fracture connectivity. This approach reveals how instantaneous and steady losses are controlled by key geometrical factors, thereby providing a computable physical basis for loss-zone inversion and bridge-plugging design. Validation against experiments shows a maximum relative error of 7.26% in pressure and loss rate, indicating that the model can reasonably reproduce actual loss behaviour. Different encounter positions and node types lead to systematic variations in loss intensity and flow partitioning. Compared with a single fracture, a fracture network significantly amplifies loss intensity through branch-induced capacity enhancement, superposition of shortest paths, and shortening of loss paths. In a typical network, the shortest path accounts for only about 20% of the total length, but contributes 40–55% of the total loss, while extending branch length from 300 mm to 1500 mm reduces the steady loss rate by 40–60%. Correlation analysis shows that the instantaneous loss rate is mainly controlled by the maximum width and height of fractures connected to the wellbore, whereas the steady loss rate has a correlation coefficient of about 0.7 with minimum width and effective path length, and decreases monotonically with the number of connected fractures under a fixed total width, indicating that the shortest path and bottleneck width are the key geometrical factors governing long-term loss in complex fracture networks. This work refines the understanding of fractured-loss dynamics and proposes the concept of coupling hydraulic deviation codes with deep learning to build a mapping model from mud-logging curves to fracture geometrical parameters, thereby providing support for lost-circulation diagnosis and bridge-plugging optimisation in complex fractured formations. Full article

The treatment of polychlorinated dibenzodioxins and polychlorinated dibenzofurans (PCDD/Fs) in incineration fly ash presents a significant challenge in solid hazardous waste management. This study systematically analyzed the influence mechanisms of multiple factors on the removal efficiency of PCDD/Fs during fly ash pyrolysis. It integrated 4068 datasets conducted between 2010 and 2025 through meta-analysis. Results show that Al₂O₃, CaO, SiO₂, and Cl in fly ash components enhance the removal efficiency by 14.0%, while Fe₂O₃ (Content greater than 5.7%) exhibits inhibitory effects. Cd and Cr demonstrate a bimodal response pattern: low/high concentrations promote removal, while medium concentrations inhibit it. Process optimization identified the optimal parameter combination as pyrolysis temperatures of 500–900 °C, residence time of 50–90 min, and a gas flow rate greater than or equal to 400 mL/min. A significant negative correlation was observed between the initial dioxin concentration and removal efficiency. This study established a structural equation modeling (SEM) model to describe how metallic and nonmetallic components, fly ash components, and pyrolysis conditions determine removal efficiency. Fly ash composition was confirmed as the most influential factor (total effect = 0.3194), with fixed carbon and ash content being the most reliable indicators. Among pyrolysis conditions, gas conditions (flow rate, gas type) also significantly affected removal efficiency (total effect = 0.2357). Conversely, nonmetallic components and excessively prolonged pyrolysis time (beyond the window) consistently reduced removal efficiency. These findings provide theoretical support for upgrading fly ash pyrolysis processes toward low-carbon and resource-efficient operations. Full article