Search Results (8,831)

This study investigates the effect of a nonlinear saturation controller (NSC) on the van der Pol–Mathieu–Duffing oscillator (VMDO). The oscillator is a single degree of freedom (DOF) system. It is driven by an external force. It is described by a nonlinear differential equation (DE). The multiple-scale perturbation method (MSPT) is applied. It gives second-order analytical solutions. The first indirect Lyapunov method is used. It provides the frequency–response equation. It also shows the stability conditions. Internal resonance is included. The analysis considers steady-state responses. It studies simultaneous primary resonance with a 1:2 internal resonance (<!-- MathType@Translator@5@5@MathML2 (no namespace).tdl@MathML 2.0 (no namespace)@ --> Full article

Natural cooling and ventilation have been fundamental principles in vernacular architecture for millennia, shaping sustainable building practices across diverse climatic regions. This paper examines the historical evolution, technological advancements, environmental benefits, and prospects of passive cooling strategies, with a particular focus on wind catchers. Originating in Mesopotamian, Egyptian, Caucasia, and Iranian architectural traditions, these structures have adapted over centuries to maximize air circulation, thermal regulation, and humidity control, ensuring comfortable indoor environments without reliance on mechanical ventilation. This study analyzes traditional wind catcher designs, highlighting their geometric configurations, airflow optimization, and integration with architectural elements such as courtyards and solar chimneys. Through a comparative assessment, this paper contrasts passive cooling systems with modern HVAC technologies, emphasizing their energy neutrality, low-carbon footprint, and long-term sustainability benefits. A SWOT analysis evaluates their strengths, limitations, opportunities for technological integration, and challenges posed by urbanization and regulatory constraints. This study adopts a comparative analytical method, integrating a literature-based approach with qualitative assessments and a SWOT analysis framework to evaluate passive cooling strategies against modern HVAC systems. Methodologically, the research combines historical review, typological classification, and sustainability-driven performance comparisons to derive actionable insights for climate-responsive design. The research is grounded in a comparative assessment of traditional and modern cooling strategies, supported by typological analysis and evaluative frameworks. Looking toward the future, the research explores hybrid adaptations incorporating solar energy, AI-driven airflow control, and retrofitting strategies for smart cities, reinforcing the enduring relevance of vernacular cooling techniques in contemporary architecture. By bridging historical knowledge with innovative solutions, this paper contributes to ongoing discussions on climate-responsive urban planning and sustainable architectural development. Full article

The deep carbonate reservoirs in the Yingzhong Block of the Qaidam Basin exhibit strong vertical heterogeneity and complex natural fracture development. Conventional fracability evaluation methods struggle to accurately characterize formation features, thereby affecting the stimulation effectiveness. To enhance the evaluation accuracy of fracturing sweet spot intervals, automatic mineral scanning equipment is employed to obtain formation micro-physical property parameters at continuous depths. Considering the temperature-pressure coupling effect under deep conditions, a rock mechanics computational model based on mineral composition was established to derive macroscopic mechanical parameters such as brittleness index and in situ stress. Based on a combined algorithm of the improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP), a fracturing sweet spot prediction model integrating micro- and macro-multi-factors is established, and sweet spot index levels are classified. The research results indicate that the rock mechanics computational model demonstrates high accuracy, the calculated macroscopic parameters are reliable, and the fracturing sweet spot index model can fracability and meticulously evaluate the characteristics of deep carbonate formations. The fracturing sweet spots can be classified into three levels: Level I with an index higher than 0.50, Level II with an index between 0.35 and 0.50, and Level III with an index lower than 0.35. After using this method for layer selection, the fracture pressure decreases by 11.6%, and the sand addition success rate increases by 24%. Applying this method to guide the optimization of fracturing intervals demonstrates good on-site practical value, providing an important reference for identifying fracturing sweet spots in deep carbonate reservoirs. Full article

This article introduces two numerical methods based on the Theory of Functional Connections (TFC) for solving linear ordinary differential equations that involve step discontinuities in the forcing term. The novelty of the first proposed approach lies in the direct incorporation of discontinuities into the free function of the TFC framework, while the second proposed method resolves discontinuities through piecewise constrained expressions comprising particular weighted support functions systematically chosen to enforce continuity conditions. The accuracy of the proposed methods is validated for both a second-order initial value and boundary value problem. As a final demonstration, the methods are applied to a third-order differential equation with non-constant coefficients and multiple discontinuities, for which an analytical solution is known. The methods achieve error levels approaching machine precision, even in the case of equations involving functions whose Laplace transforms are not available. Full article

Hydrogel-based biosensors are commonly used in diagnostic applications. However, their performance remains constrained by slow analyte diffusion within polymer matrices, particularly when larger biomolecules are involved. Concave hydrogel geometries present a promising solution to enhance diffusion rates through increased surface area. However, the interfacial dynamics governing their formation must be studied. In this research, we investigated the interfacial dynamics that influence the formation of concave hydrogel discs fabricated by a simple pipetting method. We characterized the fluid interactions occurring during droplet deposition of alginate and CaCl₂ solutions. A three-phase flow model incorporating confocal microscopy validation was employed to simulate time-dependent interfacial behaviors. Concave hydrogel discs fabricated with alginate-first deposition exhibited 83% larger surface area compared to hemispherical counterparts at a CaCl₂: alginate volume ratio of one. Increasing the volume ratio further enhanced both surface area and diameter, though this highlighted limitations for microscopy-based detection. According to our results, reaction speed in alginate concave hydrogel discs can be controlled by varying the volume of CaCl₂ solution while keeping the volume of alginate solution constant, which changes the surface area while maintaining constant hydrogel volume. Full article

A key goal when managing copper alloy heritage is preventing “bronze disease,” which damages surface detail and may disintegrate objects by oxidation and hydrolysis of nantokite (CuCl), forming voluminous copper trihydroxychlorides (Cu₂(OH)₃Cl). The success of mitigation strategies is difficult to evaluate due to the complexity of copper alloy corrosion profiles, limitations in non-destructive analytical methods and incomplete understanding of the corrosion mechanisms and reactions involved in bronze disease. Without better understanding, it is impossible to design truly effective solutions for the safe storage and display of archaeological copper alloys. Advancing current understanding, this paper examines oxidation and hydrolysis of CuCl using oxygen consumption, Fourier transform infrared spectroscopy and Raman spectroscopy, recognised as the basis of bronze disease. Variables potentially affecting bronze disease processes are evaluated, including relative humidity (RH) (15–80%RH at 20 °C) and the presence of metallic copper with CuCl and their respective ratios. Results confirm that these variables influence the reaction mechanisms and kinetics of bronze disease. The rate of oxidation and hydrolysis of CuCl accelerates with RH, and its effect is quantified. The presence of copper is shown to be important for producing bronze disease; it facilitates a cyclic reaction forming Cu₂(OH)₃Cl, increases its formation rate at lower RH than by hydrolysis of CuCl alone and prevents formation of soluble chloride compounds. The formation of Cu₂(OH)₃Cl without counteracting copper ions is shown to promote formation of CuCl₂ and CuCl₂·2H₂O, accelerating bronze disease. This new understanding is used to better quantify risk of bronze disease as a function of RH, providing a more quantitative tool for managing preservation of archaeological copper alloy collections. Full article

The traditional process for kinematic synthesis of planar mechanisms involves setting a few prescribed positions, then solving a set of equations to identify a vector chain that exactly reproduces those positions. In evaluating these equations, designers often must sift through multiple “infinities” of solutions corresponding to some number of free-choice variables that each have an infinite number of possible values. In this vast solution space, some combination of those variables will produce the most optimal solution, but finding that optimal solution is not trivial. There are two extremes for addressing the impossibility of sifting through infinite possible values. First, one could use analytical techniques to make educated estimates of the optimal values. Or, alternatively, a designer could completely remove their perspective from the process, passing the problem into a computer and programming it to sift through millions (or orders of magnitude more) possible solutions. The present work proposes a novel intermediate step in the analytical synthesis process that functions as a middle ground between these extremes. Optimizing solution density involves a designer manually manipulating the problem definition to increase the percentage of solutions that have pivots in acceptable locations. This is accomplished by changing the values of δ_j and α_j (prescribed translation and rotation of the moving plane, respectively) to manipulate the position of the poles. A physical example, designing a 7-bar parallel-motion generator, shows that applying this method yields more passing solutions when comparing over the same search depth. Specifically, 0.008% of solutions pass the design criteria without applying the method, and 3.154% pass after optimizing. This approach can reduce the computational load placed on a computer running a search script, as designers can use larger increments on the free choices without skipping over a family of solutions. Full article

Saxitoxin (STX) is a toxin with paralyzing and lethal properties, necessitating the development of a simple analytical method. This study developed a nucleic acid aptamer biosensor using graphene oxide (GO) as a fluorescence quencher for STX detection. GO was combined with M30-f, an STX nucleic acid aptamer modification with 5-carboxyfluorescein, which can produce fluorescence absorption under the conditions of an excitation wavelength of 408 nm and emission wavelength of 515 nm. Based on the principle of fluorescence resonance energy transfer, the fluorescence of M30-f was quenched. In the presence of STX, M30-f specifically binds to STX and dissociates from the GO surface, thereby restoring fluorescence. The STX content can be quantitatively detected through differences in fluorescence absorption. The influence of ultrasonic time on the fluorescence quenching ability of GO was investigated. The aqueous solution of graphene oxide, 30GO, optimized by ultrasound treatment for a duration of 30 min, demonstrated excellent fluorescence quenching capability. 30GO was analyzed utilizing various characterization techniques, including SEM, FT-IR, UV, XPS, XRD, AFM, and contact angle measurements. The methodological validation showed that the established STX sensor exhibits excellent linearity within a concentration range of 10–100,000 ng/L, with a limit of detection (LOD) as low as 0.098 μg/L. In addition, the results further demonstrated the sensor’s high specificity for detecting neurotoxic shellfish toxin STX. The recovery rate for clam samples ranged from 89.12% to 104.71%, while that for oyster samples ranged from 91.20% to 109.65%, with relative standard deviations (RSDs) all below 3%. This aptamer sensor is characterized by its simplicity, high sensitivity, and broad detection range, providing significant technical support for advancing marine biotoxin research. Full article

The 4-body equations of motion are derived in our previously published paper. Here we prove the existence–uniqueness of a periodic solution by applying the fixed-point method for a suitable introduced operator. To apply the fixed-point theorem, we need to derive appropriate analytical inequalities for the right-hand sides of the equations that ensure that the operator for periodic solutions maps the set of periodic functions into itself. In this way, we prove the existence of the Bohr–Sommerfeld orbits for the 4-body problem in the relativistic case. That allows us to estimate the minimal distances between the electrons on the first and second Bohr–Sommerfeld stationary states. A natural example of such a problem is the Lithium atom, which has three electrons orbiting the nucleus. Full article

In many scientific and engineering fields, such as hydrogeology, petroleum engineering, geotechnical research, and developing renewable energy solutions, fluid flow modeling in porous media is essential. In these areas, optimizing extraction techniques, forecasting environmental effects, and guaranteeing structural safety all depend on an understanding of the behavior of single-phase flows—fluids passing through connected pore spaces in rocks or soils. Darcy’s law, which results in an elliptic partial differential equation controlling the pressure field, is usually the mathematical basis for such modeling. Analytical solutions to these partial differential equations are seldom accessible due to the complexity and variability in natural porous formations, which makes the employment of numerical techniques necessary. To approximate subsurface flow solutions, traditional methods like the finite difference method, two-point flux approximation, and multi-point flux approximation have been employed extensively. Accuracy, stability, and computing economy are trade-offs for each, though. Deep learning techniques, in particular convolutional neural networks, physics-informed neural networks, and neural operators such as the Fourier neural operator, have become strong substitutes or enhancers of conventional solvers in recent years. These models have the potential to generalize across various permeability configurations and greatly speed up simulations. The purpose of this study is to examine and contrast the mentioned deep learning and numerical approaches to the problem of pressure distribution in single-phase Darcy flow, considering a 2D domain with mixed boundary conditions, localized sources, and sinks, and both homogeneous and heterogeneous permeability fields. The result of this study shows that the two-point flux approximation method is one of the best regarding computational speed and accuracy and the Fourier neural operator has potential to speed up more accurate methods like multi-point flux approximation. Different permeability field types only impacted each methods’ accuracy while computational time remained unchanged. This work aims to illustrate the advantages and disadvantages of each method and support the continuous development of effective solutions for porous medium flow problems by assessing solution accuracy and computing performance over a range of permeability situations. Full article

Global policy actions to reduce the environmental and social impacts of natural gas flaring are primarily derived from voluntary arrangements. This paper evaluates stakeholder preferences amongst competing policies and regulatory options, optimizing environmental governance to eliminate routine gas flaring by 2030 and achieve net-zero greenhouse emissions by 2050, whilst addressing questions of justice and fair implementation. Using a mixed-methods social scientific approach, incorporating literature and document review, interviews, expert surveys, Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (G-TOPSIS), we derive two competing perspectives on gas flaring policy strategy, with differences revealed through the AHP ranking process of individual criteria. All identified criteria and sub-criteria were integral to achieving the flaring and emissions targets, with “policy and targets” and “enabling framework” being the most important individual criteria. The “background and the role of reductions in meeting environmental and economic objectives” and ‘’nonmonetary penalties” were the key emergent sub-criteria. G-TOPSIS showed that fully implementing gas flaring policies and regulatory framework criteria to limit warming to 1.5 °C is the most effective policy alternative. Globally coordinated, uniform, and reciprocal legally binding agreements between countries to supplement national initiatives are imperative for improving the effectiveness of country-specific gas flaring policy strategies. Full article

The proper development of groundwater resources is very important in many parts of the world. Its planning requires mathematical simulation of groundwater flows. Simulation can be either analytical or numerical. Analytical tools, when available, require fewer computational resources, but they are usually based on more assumptions, at the conceptual level, which restrict their applicability. In this paper, we aim to check the applicability of one-dimensional analytical solutions for groundwater flows through non-homogeneous aquifers, which are bound by two constant head and two impermeable boundaries and bear many zones of different transmissivities. These solutions are based on the stepwise inclusion of neighboring zones to larger ones, with equivalent transmissivity coefficients. We compare analytical results with numerical ones, obtained from a two-dimensional numerical model. We have selected the boundary element method (BEM) for this task. BEM is very versatile in solving steady-state groundwater flow problems, since discretization is restricted to external and internal field boundaries only. This feature fits perfectly with our research, which requires flow velocities at the boundaries only. Our research shows that analytical results can serve as upper and lower limits of total inflow. If the differences between the transmissivities of adjacent zones are small, they can be used in preliminary calculations too. Full article

In this study, a semi-analytical solution to the inhomogeneous Whittaker equation is developed for both initial and boundary value problems. A new class of special integral functions ${}^f\mathrm{Zi}_{\kappa ,\mu }\left(x\right)$, along with their derivatives, is introduced to facilitate the construction of the solution. The analytical properties of ${}^f\mathrm{Zi}_{\kappa ,\mu }\left(x\right)$ are rigorously investigated, and explicit closed-form expressions for ${}^f\mathrm{Zi}_{\kappa ,\mu }\left(x\right)$ and its derivatives are derived in terms of Whittaker functions ${\mathrm{M}}_{\kappa ,\mu }\left(z\right)$ and ${\mathrm{W}}_{\kappa ,\mu }\left(z\right)$, confluent hypergeometric functions, and other special functions including Bessel functions, modified Bessel functions, and the incomplete gamma functions, along with their respective derivatives. These expressions are obtained for specific parameter values using symbolic computation in Maple. The results contribute to the broader analytical framework for solving inhomogeneous linear differential equations with applications in engineering, mathematical physics, and biological modeling. Full article

The mineral chalcopyrite (CuFeS₂) is inherently resistant to conventional leaching techniques, necessitating the intensification of the leaching process to achieve efficient metal recovery. Microwave-assisted leaching, combined with the application of a suitable oxidizing agent, presents a viable approach to enhancing the dissolution rate of metals in solutions. The objective of this study is to investigate the effect of microwave irradiation on the leaching behavior of chalcopyrite concentrate in a hydrochloric acid (HCl) medium, employing deep-sea polymetallic nodules (DSP) as the oxidizing agent. The influence of acid concentration and microwave power on copper extraction efficiency was examined. Optimal copper extraction was observed at an HCl concentration of 5 M and a microwave power of 750 W. The results indicate that DSP nodules serve as a more effective oxidizing agent than pyrolusite in acidic oxidative microwave-assisted leaching of chalcopyrite, particularly in terms of copper recovery. Analytical techniques employed for the characterization of leach residues and solutions included Atomic Absorption Spectroscopy (AAS) and Scanning Electron Microscopy (SEM) coupled with Energy-Dispersive X-ray Spectroscopy (EDS). Full article

A physics-informed neural network (PINN) framework is developed to model the large deformation and coupled electromechanical response of dielectric elastomer tubes for energy harvesting. The system integrates incompressible neo-Hookean elasticity with radial electric loading and compressible gas inflation, leading to nonlinear equilibrium equations with deformation-dependent boundary conditions. By embedding the governing equations and boundary conditions directly into its loss function, the PINN enables accurate, mesh-free solutions without requiring labeled data. It captures realistic pressure–volume interactions that are difficult to address analytically or through conventional numerical methods. The results show that internal volume increases by over 290% during inflation at higher reference pressures, with residual stretch after deflation reaching 9.6 times the undeformed volume. The axial force, initially tensile, becomes compressive at high voltages and pressures due to electromechanical loading and geometric constraints. Harvested energy increases strongly with pressure, while voltage contributes meaningfully only beyond a critical threshold. To ensure stable training across coupled stages, the network is optimized using the Optuna algorithm. Overall, the proposed framework offers a robust and flexible tool for predictive modeling and design of soft energy harvesters. Full article