Search Results (18,387)

Operation time and variability in structural, thermal, and environmental loads are important factors affecting the operational safety of power plant structures. Although conventional testing techniques are usually used to assess the level of damage introduced to a structure due to prolonged service, most of them are destructive and time- and cost-intensive. Therefore, in this paper, a novel approach consisting of Rayleigh optic strain sensors for deformation monitoring under creep conditions is proposed. The suitability of this methodology was assessed during quasi-static loading tests at room temperature, as well as during a long-term creep test at 540 °C under constant stress of 130 MPa, which was performed on a specimen made of 13HMF power engineering steel. The sensor attached to the specimen’s surface was used to monitor strain evolution during 678 days of high-temperature exposure under creep conditions. It was confirmed that the methodology proposed could be successfully used to monitor strain changes under quasi-static and creep conditions, as an excellent agreement between the fiber optic strain sensors and conventional strain recorders was achieved. Full article

The rapid growth of the automobile industry has intensified the demand for accurate price prediction models in the used car market. Buyers often struggle to determine fair market value due to the complexity of factors such as mileage, brand, model, transmission type, accident history, and overall condition. This study presents a comparative analysis of machine learning models for used car price prediction, with a strong emphasis on the impact of feature engineering. We begin by evaluating multiple models, including Linear Regression, Decision Trees, Random Forest, Support Vector Regression (SVR), XGBoost, Stacking Regressor, and Keras-based neural networks, on raw, unprocessed data. We then apply a comprehensive feature engineering pipeline that includes categorical encoding, outlier removal, data standardization, and extraction of hidden features (e.g., vehicle age, horsepower). The results demonstrate that advanced preprocessing significantly improves predictive performance across all models. For instance, the Stacking Regressor’s R² score increased from 0.14 to 0.8899 after feature engineering. Ensemble methods, such as CatBoost and XGBoost, also showed strong gains. This research not only benchmarks models for this task but also serves as a practical tutorial illustrating how engineered features enhance performance in structured ML pipelines for the fellow researchers. The proposed workflow offers a reproducible template for building high-accuracy pricing tools in the automotive domain, fostering transparency and informed decision making. Full article

The rational design of advanced functional materials with tailored fluorescence hinges on a profound understanding of the complex interplay between a molecule’s intrinsic structure and its local solid-state environment. This work systematically investigates these factors by employing a dual approach that combines targeted molecular synthesis with the subsequent modulation of the fluorophore’s properties within polymer matrices. First, a series of phenylhydrazone derivatives was synthesized, providing compounds with intense, solid-state fluorescence in the blue spectrum (421–494 nm). It was demonstrated that their photophysical properties were intricately linked to the substituent’s nature, which simultaneously modulated their intramolecular electron density and conformational rigidity while also governing their specific intermolecular packing in the solid state. Subsequently, we investigated the role of the supramolecular environment by embedding two fluorophores with distinct electronic profiles into electrospun poly (N-vinylpyrrolidone) (PVP) and polystyrene (PS) matrices. Our results reveal that the polymer matrix is not a passive host but an active component; it governs dye aggregation, induces significant blue shifts, and most critically, can impart exceptional thermal stability. Specifically, the PVP matrix shielded the embedded dyes from thermal quenching, maintaining robust fluorescence up to 100 °C. By combining molecular-level synthesis with matrix-level engineering, this work demonstrates a powerful strategy for the rational design of emissive materials, where properties like color and operational stability can be deliberately tuned for demanding applications in optoelectronics and sensing. Full article

Expansive soils are clayey soils that undergo significant volume changes due to moisture content variations which can severely affect the stability of foundations and infrastructure. This study investigates the use of talcum powder as a novel stabilizing additive to reduce the swelling potential of expansive soils with particular focus on the behavior of the treated soil under curing conditions. Talcum powder concentrations of 5%, 10%, 15%, 20% and 25% by dry weight of soil was considered. A comprehensive series of laboratory tests were conducted, including swelling pressure, Atterberg limits, modified Proctor compaction and unconfined compressive strength at 4 curing times: 0 days, 7 days, 14 days and 28 days. In addition, mineralogical and microstructural analyses were carried out using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Experimental results revealed that incorporating talcum powder at a content of 25% by dry weight effectively reduced the swelling pressure by 37.5%. The compression index decreases with the increase in the talcum powder content. The results highlight the material’s significant capability to enhance the engineering properties of expansive soils, particularly under curing conditions and offer a cost-effective and readily available solution for soil stabilization applications. Full article

Resource utilization of water treatment residuals (WTRs) has emerged as a significant focus in environmental engineering research. In this study, waste iron sludge from a groundwater de-ironing plant was used as the raw material. Ferric salts were recovered via sulfuric acid leaching and subsequently polymerized into polyferric sulfate (PFS) with varying basicity (B = 0.1–0.4) using the alkalization–aging method. The optimal leaching conditions were determined as a liquid–solid ratio of 10:1, a sulfuric acid concentration of 3 mol·L⁻¹, a reaction temperature of 70 °C, and a reaction time of 30 min, yielding a ferric leaching amount of 0.45 g Fe/g dry sludge. Characterization results revealed that the synthesized PFS exhibited similar ferric polymer species, functional group structures, and polymeric crystal structures to those of commercial PFS (CPFS). Coagulation performance tests demonstrated that at a dosage of 30 mg Fe/L, the prepared PFS achieved turbidity and UV₂₅₄ removal efficiencies of 96.88% and 81.87%, respectively, outperforming CPFS. In domestic wastewater treatment, combining the synthesized PFS with magnetic nanoparticles Fe₃O₄@C yielded a magnetic coagulant that further enhanced the removal of turbidity, chemical oxygen demand (COD), and total phosphorus (TP) to maximum efficiencies of 94.66%, 81.97%, and 98.08%, respectively. This study confirms the technical feasibility and environmental–economic benefits of preparing magnetic PFS coagulants from waste iron sludge for wastewater treatment. Full article

In this paper, the problem of aero-engines ensemble modeling under sparse data is addressed. Firstly, the Makima method is used to interpolate and complement the sparse data by analyzing the experimental data of a specific real aero-engine. In this way, the data sparsity problem due to sampling or transmission is solved equally well. Secondly, the Nonlinear Auto-Regressive with Exogenous Inputs (NARX) neural network is brought in as the computational structure of the model. Based on the Automatic Neural Network Architecture Search (ANAS) method, the hyperparameters of the model can be searched efficiently, and the performance is improved. Third, a novel ensemble modeling method based on the Makima method, the NARX model, and the ANAS method is proposed to realize high-precision modeling throughout the entire operation process of the aero-engine from the idle state to the full throttle state. Finally, the proposed method is validated by simulations and experiments, and the results illustrate the innovation and correctness. Full article

The rapid shift toward electric vehicles (EVs) has underscored the critical importance of battery pack crashworthiness, creating a demand for lightweight, energy-absorbing protective systems. This review systematically explores bio-inspired cellular structures as promising solutions for improving the impact resistance of EV battery packs. Inspired by natural geometries, these designs exhibit superior energy absorption, controlled deformation behavior, and high structural efficiency compared to conventional configurations. A comprehensive analysis of experimental, numerical, and theoretical studies published up to mid-2025 was conducted, with emphasis on design strategies, optimization techniques, and performance under diverse loading conditions. Findings show that auxetic, honeycomb, and hierarchical multi-cell architectures can markedly enhance specific energy absorption and deformation control, with improvements often exceeding 100% over traditional structures. Finite element analyses highlight their ability to achieve controlled deformation and efficient energy dissipation, while optimization strategies, including machine learning, genetic algorithms, and multi-objective approaches, enable effective trade-offs between energy absorption, weight reduction, and manufacturability. Persistent challenges remain in structural optimization, overreliance on numerical simulations with limited experimental validation, and narrow focus on a few bio-inspired geometries and thermo-electro-mechanical coupling, for which engineering solutions are proposed. The review concludes with future research directions focused on geometric optimization, multi-physics modeling, and industrial integration strategies. Collectively, this work provides a comprehensive framework for advancing next-generation crashworthy battery pack designs that integrate safety, performance, and sustainability in electric mobility. Full article

To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and finite element simulations, achieving effective vibration isolation within confined spaces. The dynamic performance of the isolator was experimentally evaluated using a hydraulic testing system under varying excitation amplitudes, frequencies, initial positions, and magnetic fields. Experimental results indicate that the isolator achieves a static stiffness of 3 × 10⁶ N/m and a maximum adjustable compression load range of 105.4%. In light of the asymmetric nonlinear dynamic behavior of the isolator, an improved nine-parameter Bouc–Wen model is proposed. Parameter identification performed via a genetic algorithm demonstrates a model accuracy of 95.0%, with a minimum error reduction of 28.8% compared to the conventional Bouc–Wen model. Full article

This review emphasizes the latest developments in bioprinted scaffolds in tissue engineering, with a focus on their biomimetic applications. The accelerated pace of development of 3D bioprinting technologies has transformed the ability to fabricate scaffolds with the potential to replicate the structure and function of native tissues. Bioprinting methods such as inkjet, extrusion-based, laser-assisted, and digital light processing (DLP) approaches have the potential to fabricate complex, multi-material structures with high precision in geometry, material composition, and cellular microenvironments. Incorporating biomimetic design principles to replicate the mechanical and biological behaviors of native tissues has been of major research interest. Scaffold geometries that support cell adhesion, growth, and differentiation essential for tissue regeneration are mainly of particular interest. The review also deals with the development of bioink, with an emphasis on the utilization of natural, synthetic, and composite materials for enhanced scaffold stability, printability, and biocompatibility. Rheological characteristics, cell viability, and the utilization of stimuli-responsive bioinks are also discussed in detail. Their utilization in bone, cartilage, skin, neural, and cardiovascular tissue engineering demonstrates the versatility of bioprinted scaffolds. Despite the significant advancements, there are still challenges that include achieving efficient vascularization, long-term integration with host tissues, and scalability. The review concludes by underlining future trends such as 4D bioprinting, artificial intelligence-augmented scaffold design, and the regulatory and ethical implications involved in clinical translation. By considering these challenges in detail, this review provides insight into the future of bioprinted scaffolds in regenerative medicine. Full article

Electromagnetic field (EMF) exposure mapping is increasingly important for ensuring compliance with safety regulations, supporting the deployment of next-generation wireless networks, and addressing public health concerns. While numerous surveys have addressed specific aspects of radio propagation or radio environment maps, a comprehensive and unified overview of EMF mapping methodologies has been lacking. This review bridges that gap by systematically analyzing computational, geospatial, and machine learning approaches used for EMF exposure mapping across both wireless communication engineering and public health domains. A novel taxonomy is introduced to clarify overlapping terminology—encompassing radio maps, radio environment maps, and EMF exposure maps—and to classify construction methods, including analytical models, model-based interpolation, and data-driven learning techniques. In addition, the review highlights domain-specific challenges such as indoor versus outdoor mapping, data sparsity, and model generalization, while identifying emerging opportunities in hybrid modeling, big data integration, and explainable AI. By combining perspectives from communication engineering and public health, this work provides a broader and more interdisciplinary synthesis than previous surveys, offering a structured reference and roadmap for advancing robust, scalable, and socially relevant EMF mapping frameworks. Full article

To address the challenges of short allowable motion windows and complex motion planning inherent in dual forging manipulator systems, this study proposes a coordinated motion pattern tailored to dual-manipulator operations, focusing on forging deformation behavior and press control characteristics. First, six representative long-shaft forging materials were classified based on typical industrial applications. Using DEFORM-3D (V11.0) software, the deformation process during the elongation operation was analyzed, and the velocity and displacement characteristics at both ends of the forgings were extracted to clarify the compliant motion requirements of the grippers. Next, a segmented computation method for manipulator allowable motion time was developed based on the motion–time curve of the hydraulic press, significantly improving the time utilization efficiency for coordinated control. Furthermore, experimental tests were carried out to verify the dynamic response performance and motion accuracy of the dual-manipulator system. Finally, the dual-manipulator forging cycle was systematically divided into four stages—pre-forging adjustment, inter-pass compliance, execution phase, and forging completion—resulting in a structured and implementable coordination control framework. This research provides both a theoretical foundation and practical pathway for achieving efficient and precise coordinated motion control in dual forging manipulator systems, offering strong potential for engineering application and industrial deployment. Full article

Gallic acid (GA), a polyphenol extensively used in the food, wine, and pharmaceutical industries, is known for its inhibitory effects on soil microbial activity. Photocatalytic degradation offers an environmentally friendly solution for GA removal from water. In this work, graphitic carbon nitride (g-C₃N₄) photocatalysts were synthesized by two methods: thermal exfoliation (CN-E) and supramolecular assembly via hydrothermal processing (HCN-II). Structural analyses by XRD, FTIR, and XPS confirmed the formation of the g-C₃N₄ framework, while SEM revealed that CN-E consisted of folded and curled nanosheets, whereas HCN-II displayed a polyhedral–nanosheet hybrid architecture with internal channels. Both materials achieved approximately 80% GA degradation within 180 min under visible-light irradiation, yet HCN-II exhibited a superior apparent rate constant (k = 0.01156 min⁻¹) compared with CN-E. Radical trapping experiments demonstrated that O₂•⁻ and h⁺ were the primary reactive oxygen species involved, with OH• making a minor contribution. The enhanced performance of HCN-II is attributed to its higher surface area, improved light harvesting, and efficient charge separation derived from supramolecular assembly. These findings highlight the potential of engineered g-C₃N₄ nanostructures as efficient, metal-free photocatalysts for the degradation of recalcitrant organic pollutants in water treatment applications. Full article

Resonant acoustic technology utilizes low-frequency vertical harmonic vibrations to induce full-field mixing effects in processed materials, and it is regarded as a “disruptive technology in the field of energetic materials”. Although numerous scholars have investigated the mechanisms of resonant acoustic mixing, there remains a lack of parameter selection methods for improving product quality and production efficiency in engineering practice. To address this issue, this study employs phase-field modeling and fluid–structure coupling methods to numerically simulate the transport process of glycerol during resonant acoustic mixing. The research reveals the mass transfer mechanism within the flow field, establishes a liquid-phase distribution index for quantitatively characterizing mixing effectiveness, and clarifies the enhancement effect of fluid transport on solid particle mixing through particle tracking methods. Furthermore, parameter studies on vibration frequency and amplitude were conducted, yielding a critical curve for guiding parameter selection in engineering applications. The results demonstrate that Faraday instability first occurs at the fluid surface, generating Faraday waves that drive large-scale vortices for global mass transfer, followed by localized mixing through small-scale vortices. The transport process of glycerol during resonant acoustic mixing comprises three distinct stages: stable Faraday wave oscillation, rapid mass transfer during flow field destabilization, and localized mixing upon stabilization. Additionally, increasing either vibration frequency or amplitude effectively enhances both the rate and effectiveness of mass transfer. These findings offer theoretical guidance for optimizing process parameters in resonant acoustic mixing applications. Full article

Surface engineering and architectural design represent key frontiers in total ankle arthroplasty (TAA) implant development. This narrative review examines biointegration strategies, focusing on porous structures, surface modification techniques, and emerging smart technologies. Optimal porous architectures with 300–600 µm pore sizes facilitate bone ingrowth and osseointegration, while functionally graded structures address regional biomechanical demands. Surface modification encompasses bioactive treatments (such as calcium phosphate coatings), topographical modifications (including micro/nanotexturing), antimicrobial approaches (utilizing metallic ions or antibiotic incorporation), and wear-resistant technologies (such as diamond-like carbon coatings). Multifunctional approaches combine strategies to simultaneously address infection prevention, enhance osseointegration, and improve wear resistance. Emerging technologies include biodegradable scaffolds, biomimetic surface nanotechnology, and intelligent sensor-based monitoring systems. While many innovations remain in the research stage, they demonstrate the potential to establish TAA as a comprehensive alternative to arthrodesis. Successful implant design requires integrated surface engineering tailored to the ankle joint’s demanding biomechanical and biological environment Full article

The use of consumer-grade cameras for stereo vision provides a cost-effective, non-contact method for measuring three-dimensional displacement in civil engineering experiments. However, obtaining accurate 3D coordinates requires accurate temporal alignment of several unsynchronized cameras, which is often lacking in consumer-grade devices. Current synchronization software methods usually only achieve precision at the frame level. As a result, they fall short for high-frequency shake table experiments, where even minor timing differences can cause significant triangulation errors. To address this issue, we propose a novel image-based synchronization method and a graphical user interface (GUI)-based software for acquiring stereo videos during shake table testing. The proposed method estimates the time lag between unsynchronized videos by minimizing reprojection errors. Then, the estimate is refined to sub-frame accuracy using polynomial interpolation. This method was validated using a high-precision motion capture system (Mocap) as a benchmark through large- and small-scale experiments. The proposed method reduces the RMSE of triangulation by up to 78.79% and achieves maximum displacement errors of less than 1 mm for small-scale experiments. The proposed approach reduces the RMSE of displacement measurements by 94.21% and 62.86% for small- and large-scale experiments, respectively. The results demonstrate the effectiveness of the proposed method for precise 3D displacement measurement with low-cost equipment. This method offers a practical alternative to expensive vision-based measurement systems commonly used in structural dynamics research. Full article