Search Results (52,130)

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies. Full article

Enhancing the understanding of the behavior, optimizing the design, and improving the predictability and reliability of manufactured unidirectional (UD) FRP plies, which serve as primary building blocks for structural FRP laminates and components, are crucial to achieving a safe and cost-effective design. This research investigated the influence of fiber volume fraction ($v_f$) on the predictability and reliability of the homogenized elastic properties and damage initiation strengths of two different types of UD FRP plies using validated micromechanical virtual testing for representative volume element (RVE) models. Several sources of uncertainties were included in the RVE models. This study also proposed a modified algorithm for microstructure generation and explored the effect of $v_f$ on the optimal sizes of the RVE in terms of fiber number. Virtual tests were systematically conducted using full factorial DOE coupled with Monte Carlo simulation. The modified algorithm demonstrated exceptional performance in terms of convergence speed and jamming limit, significantly reducing the time required to generate microstructures. The developed RVE models accurately predicted failure modes, loci, homogenized elastic properties, and damage initiation strengths with a mean error of less than $5\%$. Also, it was found that increasing $v_f$ led to a concurrent increase in the optimal size of the RVE. While it was found that the $v_f$ had a direct influence on homogenized elastic properties and damage initiation strengths, it did not significantly affect the reliability and predictability of these properties, as indicated by low correlation coefficients and fluctuations in the coefficient of variation of normalized properties. Full article

Following the operational success of the Hywind Scotland, Kincardine, WindFloat Atlantic, and Hywind Tampen floating wind farms, the floating offshore wind industry is expected to play a critical role in the global clean energy transition. However, there is still significant work needed in optimizing the design and implementation of floating offshore wind turbines (FOWTs) to justify the widespread adoption of this technology and ensure that it is commercially viable compared to other more-established renewable energy technologies. The present review explores the application of fully coupled computational fluid dynamics (CFD) modeling approaches for achieving the cost reductions and design confidence necessary for floating wind to fully establish itself as a reliable and practical renewable energy technology. In particular, using these models to better understand and predict the highly nonlinear and integrated environmental loading on FOWT systems and the resulting dynamic responses prior to full-scale implementation is of increased importance. Full article

In modern cloud environments, container orchestration tools are essential for effectively managing diverse workloads and services, and Kubernetes has become the de facto standard tool for automating the deployment, scaling, and operation of containerized applications. While Kubernetes plays an important role in optimizing and managing the deployment of diverse services and applications, its default scheduling approach, which is not optimized for all types of workloads, can often result in poor performance and wasted resources. This is particularly true in environments with complex interactions between services, such as microservice architectures. The traditional Kubernetes scheduler makes scheduling decisions based on CPU and memory usage, but the limitation of this arrangement is that it does not fully account for the performance and resource efficiency of the application. As a result, the communication latency between services increases, and the overall system performance suffers. Therefore, a more sophisticated and adaptive scheduling method is required. In this work, we propose an adaptive pod placement optimization technique using multi-tier inspection to address these issues. The proposed technique collects and analyzes multi-tier data to improve application performance and resource efficiency, which are overlooked by the default Kubernetes scheduler. It derives optimal placements based on the coupling and dependencies between pods, resulting in more efficient resource usage and better performance. To validate the performance of the proposed method, we configured a Kubernetes cluster in a virtualized environment and conducted experiments using a benchmark application with a microservice architecture. The experimental results show that the proposed method outperforms the existing Kubernetes scheduler, reducing the average response time by up to 11.5% and increasing the number of requests processed per second by up to 10.04%. This indicates that the proposed method minimizes the inter-pod communication delay and improves the system-wide resource utilization. This research aims to optimize application performance and increase resource efficiency in cloud-native environments, and the proposed technique can be applied to different cloud environments and workloads in the future to provide more generalized optimizations. This is expected to contribute to increasing the operational efficiency of cloud infrastructure and improving the quality of service. Full article

The Zonguldak coal basin is the area with the most important hard coal reserves in Turkey. This study focuses on coal samples extracted from three seams of the Kozlu Formation, specifically from the Kozlu underground mine, to assess the coals’ organic geochemical and petrographic properties. Analytical methods, including TOC-pyrolysis, biomarker analysis, and maceral distribution studies, were employed. Based on these analyses, the paleoenvironmental conditions and hydrocarbon generation potential of the coals were evaluated. The results reveal that the coals, characterized by high TOC, high HI, and low OI, contain type II–III kerogen. These findings, coupled with the high QI and low BI values, suggest the presence of oil–gas prone source rocks. Elevated Tmax (457–466 °C) and Rr (0.89%–1.17%) values indicate a maturity level ranging from mature to overmature stages. High GI and GWI values suggest a significant degree of gelification and wet conditions during formation. The high Pr/Ph (1–6.58), C₃₁R/C₃₀ hopane (<0.25), and low DBT/P (0.27–0.50) ratios show that the Acılık seam was formed in a lacustrine environment under anoxic–suboxic conditions, whereas the Büyük and Domuzcu seams were formed in a fluvial/deltaic environment under oxic conditions. The findings of this study suggest that the paleovegetation in coal-forming environments consisted of aquatic and herbaceous plants. Full article

Biogeochemical redox cycling of iron (Fe) essentially governs various geochemical processes in nature. However, the mechanistic underpinnings of Fe-redox cycling in deep-sea sediments remain poorly understood, due to the limited access to the deep-sea environment. Here, abyssal sediment collected from a depth of 5800 m in the Pacific Ocean was characterized for its elemental, mineralogical, and biological properties. The sedimentary environment was determined to be oligotrophic with limited nutrition, yet contained a considerable amount of trace elements. Fe-redox reactions in sediment progressed through an initial lag phase, followed by a fast Fe(II) reduction and an extended period of Fe(III) oxidation before achieving equilibrium after 58 days. The presence of an external H₂ electron donor significantly increased the extent of Fe(III) bio-reduction by 7.73% relative to an amendment-free control under high pressure of 58 MPa. A similar enhancement of 11.20% was observed following lactate amendment under atmospheric pressure. Fe(II) bio-oxidation occurred after 16 days’ anaerobic culturing, coupled with nitrate reduction. During Fe bio-redox reactions, microbial community composition was significantly shaped by the presence/absence of an electron donor, while the hydrostatic pressure levels were the controlling factor. Shewanella spp. emerged as the primary Fe(III)-reducing microorganisms, and were stimulated by supplemented lactate. Marinobacter hydrocarbonoclasticus was the predominant Fe(II)-oxidizing microorganism across all conditions. Our findings illustrate continuous Fe-redox reactions occurring in the deep-sea environment, with coexisting Fe-redox microorganisms determining the oscillation of Fe valence states within the abyssal sediment. Full article

In this paper, a coupled model is built to research the space-fractional magnetohydrodynamic (MHD) flow and heat transfer problem. The fractional coupled model is solved numerically by combining the matrix function vector products method in the temporal direction with the spectral method in the spatial direction. A fast method based on the numerical scheme is established to reduce the computational time. With the help of the Bayesian method, the space-fractional orders of the coupled model are estimated, and the problem of multi-parameter estimation in the coupled model is solved. Finally, a numerical example is carried out to verify the stability of the numerical methods and the effectiveness of the parameter estimation method. Results show that the numerical method is stable, which converges with an accuracy of $O({\tau }^2+N^{-r})$. The fast method is efficient in reducing the computational time, and the parameter estimation method can effectively estimate parameters in the space-fractional coupled model. The numerical solutions are discussed to describe the effects of several important parameters on the velocity and the temperature. Results indicate that the Lorentz force produced by the MHD flow blocks the movement of the fluid and prolongs the time for the fluid to reach a stable state. But the Hall parameter m weakens this hindrance. The Joule heating effects play a negative role in heat transfer. Full article

Phase change energy storage technology enhances the integration of renewable resources into low-carbon energy systems for grassland pastoral settlements, further addressing the balance between energy needs and environmental sustainability. This study examines a heating system using an experimental platform in an environmental chamber, where the thermal storage and release processes of phase change energy storage flooring were monitored. The results revealed that phase change energy storage flooring exhibits higher heat transfer efficiency and faster heating rates. Under 40 °C heating conditions, the heating rate of the thermal storage layer increased by 12.5% within 1 h. The flooring also demonstrated superior heat release performance, with the peak heat flux of the thermal storage layer delayed by 15 min. Higher heating temperatures shortened the heating time and extended the heat release duration of the phase change energy storage flooring. Under 45 °C heating conditions, the heat transfer efficiency of the surface temperature of the thermal storage layer increased by 38% within 1 hour and by 24.7% over 4 h. In addition, energy consumption in different tests was analyzed, and thermal conductivity was discussed according to the heat transfer model. Phase change energy storage flooring, when coupled with the abundant solar energy resources available in grassland pastoral areas, presents a viable option for the construction of low-carbon energy systems in grassland pastoral settlements. Full article

The effectiveness of repair work relies on whether the interface substrate can achieve sufficient bond strength when subjected to numerous stresses. This study investigated the bond properties of repaired normal concrete (NC-to-NC) elements, including cube, beam, and U-shaped specimens, after undergoing natural fracture due to flexural and tensile stresses. The specimens were repaired using a polyurethane (PU) matrix by gluing the two parts and applying compression, splitting, and drop-weight impact (DWI) tests to evaluate the bond strength properties. The results revealed that the PU matrix effectively repairs NC substrate with adequate bond strength, which exceeds the minimum allowable bond strength specified in the ASTM ACI 546-06 to rehabilitate damage concrete structures. The reference beams exhibit a peak applied load capacity of 15.6 kN with less deflection than the repaired samples. The compressive strength of the NC-to-NC repaired specimens loaded along and parallel to the interface plane revealed a decrease in compressive strength of 47.3% and 31.5% compared to the NC-R samples, respectively. The mean number of blows at the cracking stages appeared nearly equal for reference and repaired NC-to-NC specimens. The reference specimens exhibited an average number of 24 and 31 blows at the initial and failure stages, respectively, which were higher by 9.1% and 5.2% than the NC-to-NC repaired specimens. The PU binder showed promising results in achieving adequate interfacial bond strength under static and impact loads. Full article

Pro-regenerative lipid mediator 1 (PreM1) is a specialized pro-resolving lipid mediator that promotes wound healing and regenerative functions of mesenchymal stem cells (MSCs), endothelial cells, and macrophages. The healing of third-degree (3°) burns and regenerative functions of MSCs are enhanced by ACgel1, an arginine-and-chitosan-based protein-mimic hybrid hydrogel. Adipose-tissue derived microvascular fragments (MVFs) are native vascularization units and a rich source of MSCs, endothelial cells, and perivascular cells for tissue regeneration. Here we describe an innovative PreM1-MVFs-ACgel1 construct that incorporated PreM1 and MVFs into ACgel1 via optimal design and fabrication. This construct delivered PreM1 to 3°-burn wounds at least up to 7 days-post-burn (dpb), and scaffolded and delivered MVFs. PreM1-MVFs-ACgel1 promoted the healing of 3°-burns in mice, including vascularization and collagen formation. The re-epithelization and closure of 3° burn wounds were promoted by ACgel1, MVFs, PreM1, MVFs-ACgel1, PreM1-ACgel1, or PreM1-MVFs-ACgel1 at certain time-point(s), while PreM1-MVFs-ACgel1 was most effective with 97% closure and 4.69% relative epithelial gap at 13 dpb compared to saline control. The PreM1-ACgel1 and MVFs-ACgel1 also promoted blood vessel regeneration of 3°-burns although PreM1-MVFs-ACgel1 is significantly more effective. These PreM1- and/or MVF-functionalized ACgel1 have nonexistent or minimal graft-donor requirements and are promising adjuvant therapeutic candidates for treating deep burns. Full article

Evaluating the performance of multifunctionality is a necessary foundation for forest multifunctionality management. This study aims to comprehensively adopt multiple methods to construct a multifunctional evaluation system for natural spruce–fir forests and explore the impact of thinning intensity on the multifunctional management effect of spruce–fir. This article combines subjective and objective evaluation methods and selects three methods to construct an evaluation system: the Analytic Hierarchy Process, the combined entropy weight method, and the CRITIC method. The results showed that the consistency of the three evaluation methods is good, and according to the score based on the evaluation results, the multifunctional performance of the sample plot with a thinning intensity of 20% (average score of AHP method is 75.5; EWM is 91; CRITIC is 96.5) is significantly better than that of the sample plot with a thinning intensity of 40% (AHP is 65.3; EWM is 51; CRITIC is 48), both of which were significantly better than those of the untreated sample plot (AHP is 12.7; EWM is 18.7; CRITIC is 17.3). A coupling relationship model between multifunctional values and different functions, as well as a coupling relationship model between different functions and various indicators, were constructed based on the evaluation system. Finally, the forest stand with the highest multifunctional comprehensive value was selected as the reference for the target structure to construct the target structure system, which is convenient for actual management. This study found that there is a nurturing intensity (20%) that can best utilize the multiple functions of forests, which has practical significance for promoting forest multifunctionality in forest management. In addition, this study scientifically constructed and compared several evaluation systems for the multifunctional performance of forests, laying a certain foundation for forest multifunctional evaluation and future forest multifunctional management. Full article

The current study aims to develop isolation protocols for several contaminants of emerging concern (i.e., microplastics (MPs), polycyclic aromatic hydrocarbons (PAHs), and heavy metals (HMs)) from different commercial brands and raw milk samples and also to quantify and characterize the risks of these contaminants pose to human health. The quantification, shape, color, and chemical composition of MPs were achieved using optical microscopy, micro-Fourier transform infrared spectroscopy, and scanning electron microscopy coupled with energy-dispersive spectroscopy. Based on the MP dimensions highlighted by the aforementioned techniques, it can be stated that their length ranges between tens of micrometers and a few centimeters; plus, the thickness in some cases reaches more than 15 µm, and the structure of the MPs can be mostly described as a fibriform with a glossy/matte aspect. The polymeric structures identified were polyamides, poly(methyl methacrylate), polyurethane, polyester, and polyethylene. Chemical investigations (PAHs and HMs concentrations) were performed by high-performance liquid chromatography with fluorescence detection and inductively coupled plasma mass spectrometry, respectively. The pollution load index (1.091–7.676) and daily intake of MPs for adults (0.021–1.061 n·kg⁻¹·d⁻¹) and children (0.089–4.420 n·kg⁻¹·d⁻¹) were calculated. It can be concluded that the presence of MPs in milk supports the hypothesis that microplastics can act as carriers for other contaminants (HMs and PAHs), thus increasing the threat to health. Full article

Integration of heat pumps combined with thermal energy storage provides a key pathway to decarbonizing the energy supply in the industry when the processes are not operated continuously. Yet, this integration of such novel systems introduces control challenges due to added dependencies between different process streams. This work investigates the control problem of heat pumps coupled to stratified thermal energy storage that is integrated into non-continuous industrial processes. A two-layer control strategy is proposed, where, in the higher level, a model predictive controller is developed for energy management using a linear model of the non-linear process. The resulting optimization problem is a mixed integer quadratic program. The low-level control layer is defined with standard industry controllers. The overall system is tested using a dynamic simulation model for the entire process, demonstrating its performance in three different cases. The control strategy optimizes heat recovery while ensuring system operability. The study demonstrates successful disturbance rejection and cold starts, wherein 100% of the targeted heat recovery can be confirmed under nominal conditions. Further evaluation in laboratory or field trials is recommended, and alternative, yet-to-be-defined, control concepts may be compared to the proposed approach. Full article

This study presents a comprehensive model for ultrasonic energy transfer (UET) using a 33-mode piezoelectric transducer to advance wireless sensor powering in challenging environments. One of the advantages of UET is that it is not stoppable by electromagnetic shielding and can penetrate metal. Existing models focus on feasibility and numerical analysis but lack an effective link between input and output power in different media applications. The proposed model fills this gap by incorporating key factors of link loss, including resonant frequency, impedance matching, acoustic coupling, and boundary conditions, to predict energy transfer efficiency more accurately. The model is validated through numerical simulations and experimental tests in air, metal, and underwater environments. An error analysis has shown that the maximum error between theoretical and experimental responses is 3.11% (air), 27.37% (water), and 1.76% (aluminum). This research provides valuable insights into UET dynamics and offers practical guidelines for developing efficient wireless powering solutions for sensors in difficult-to-access or electromagnetically shielded conditions. Full article

African swine fever (ASF) is an acute, highly hemorrhagic viral disease in domestic pigs and wild boars. The disease is caused by African swine fever virus, a double stranded DNA virus of the Asfarviridae family. ASF can be classified into 25 different genotypes, based on a 478 bp fragment corresponding to the C-terminal sequence of the B646L gene, which is highly conserved among strains and encodes the major capsid protein p72. The C-terminal end of p72 has been used as a PCR target for quick diagnosis of ASF, and its characterization remains the first approach for epidemiological tracking and identification of the origin of ASF in outbreak investigations. Recently, a new classification of ASF, based on the complete sequence of p72, reduced the 25 genotypes into only six genotypes; therefore, it is necessary to have the capability to sequence the full-length B646L gene (p72) in a rapid manner for quick genotype characterization. Here, we evaluate the use of an amplicon approach targeting the whole B646L gene, coupled with nanopore sequencing in a multiplex format using Flongle flow cells, as an easy, low cost, and rapid method for the characterization and genotyping of ASF in real-time. Full article