Search Results (232)

This study investigates hydrogen storage enhancement through adsorption in porous materials by coupling the Dubinin–Astakhov (D-A) adsorption model with H₂ conservation equations (mass, momentum, and energy). The resulting system of partial differential equations (PDEs) was solved numerically using the finite element method (FEM). Experimental work using activated carbon as an adsorbent was carried out to validate the model. The comparison showed good agreement in terms of temperature distribution, average pressure of the system, and the amount of adsorbed hydrogen (H₂). Further simulations with different adsorbents indicated that compact metal–organic framework 5 (MOF-5) is the most effective material in terms of H₂ adsorption. Additionally, the pair (273 K, 800 s) remains the optimal combination of injection temperature and time. The findings underscore the prospective advantages of optimized MOF-5-based systems for enhanced hydrogen storage. These systems offer increased capacity and safety compared to traditional adsorbents. Subsequent research should investigate multi-objective optimization of material properties and system geometry, along with evaluating dynamic cycling performance in practical operating conditions. Additionally, experimental validation on MOF-5-based storage prototypes would further reinforce the model’s predictive capabilities for industrial applications. Full article

Supercritical carbon dioxide (sCO₂) Brayton cycle is a promising technology for concentrating solar power systems. However, existing studies predominantly rely on steady-state or quasi-steady-state assumptions, thereby neglecting transient characteristics of fluid flow and heat transfer. This study develops a transient analysis program for solar power tower systems integrated with sCO₂ Brayton cycles using the finite difference method. The program comprises two interactive modules—a molten salt loop and a Brayton cycle module—coupled through an intermediate heat exchanger. For the Brayton cycle module, a fluid network model enabling a unified framework for the simultaneous solution of all governing equations is adopted. The SIMPLE algorithm and Gauss–Seidel iteration method are employed to solve the conservation equations. Following validation of key components and system performance, dynamic simulations under load and solar irradiance step disturbances are conducted. The results demonstrate that the program accurately captures transient behaviors and supports control strategy design and safety analysis for solar power tower systems with arbitrary sCO₂ Brayton cycle layouts. Full article

This paper presents the application of conic programming methods to the limit analysis of plane rigid-plastic problems in structural and geotechnical engineering. The approach is based on the formulation of yield criteria as second-order cone constraints and on the dual optimization problem, which directly provides collapse mechanisms and limit loads. Two benchmark examples are investigated. The first concerns a deep beam under uniform top pressure, analyzed with linear and quadratic finite elements. The results confirm the ability of the method to reproduce realistic collapse mechanisms and demonstrate the effect of mesh refinement and element type on convergence. The second example addresses the ultimate bearing capacity of a strip footing on cohesive-frictional soil. The numerical implementation was carried out in MATLAB using CVX with MOSEK as the solver, which ensures practical applicability and efficient computations. Different soil models are considered, including Mohr–Coulomb and two Drucker–Prager variants, and the results are compared with the classical Terzaghi solution. Additional elastoplastic FEM simulations carried out in a commercial program are also presented. The comparison highlights the differences between rigid-plastic optimization and incremental elastoplastic analyses, showing that both conservative and liberal estimates of bearing capacity can be obtained. The study shows that conic programming is an efficient and flexible framework for limit analysis of plane rigid-plastic problems, providing engineers with complementary tools for assessing ultimate loads, while also ensuring good computational efficiency. Full article

The present research seeks to characterize and evaluate a lid-driven cavity–TEG system to harness residual energy. Therefore, the behavior of water and a nanofluid ($\mathrm{S}\mathrm{i}{\mathrm{O}}_2$) in a rectangular lid-driven cavity is numerically studied. The Navier–Stokes and energy conservation equations are solved using the finite difference method in Python. The fluid behavior is analyzed with a Reynolds number of 100, Richardson number of 100-77 and variable lid direction. Likewise, a thermoelectric module is integrated in the cavity, and the power generated by varying the size and number of thermocouples is studied. The results obtained contribute to the characterization of applicable thermal systems for their optimization. In the cavity, when the lid direction is positive, its interaction with the buoyant flow generates a vortex on the right side, and multiple vortices when it is in the negative direction; the isotherms present horizontal and vertical stratification in both cases. $\mu$TEG generates the most power with a 0.07 mm thermocouple size in the negative lid direction case, with an inlet gradient temperature of 8 K. $\mathrm{S}\mathrm{i}{\mathrm{O}}_2$ (Ri = 77) showed a 23% increase in power output compared to water (0.318 μW/cm² and 0.461 μW/cm², respectively). With a 30% higher inlet gradient temperature ($\mathrm{S}\mathrm{i}{\mathrm{O}}_2$ at Ri = 100, $\mathsf{\Delta }$T = 10.4 K, 0.569 μW/cm²), it generated 79% more power output compared to water. Full article

Wireless Sensor Networks are composed of a set of sensors distributed within an area that monitor physical variables of the environment and send back information to a central node. Nodes cannot always remain active since they would swiftly drain the system’s energy. As such, some works have proposed the use of different on/off schemes to monitor the phenomena of interest efficiently but also to conserve energy as much as possible. To this end, the use of on/off protocols has been used before, but has no relation to the characteristics of the monitored events. However, in scenarios where the phenomena to monitor occur in a certain pattern or specific region, the use of more suited techniques to activate the nodes can yield better results. In this sense, we propose the use of cellular automata (CA), based on the Game of Life (GoL), in order to turn the nodes on and off, according to the patterns described by the automata. Cellular automata are discrete models consisting of a lattice or grid of cells in a finite number of states that remain or change into another state following pre-established rules commonly associated with the states of their neighbors. As such, we propose to activate/deactivate the nodes following the natural behavior of the GoL scheme. Since the initial state of the cellular automata directly modifies the pattern evolution of the GoL, we consider several possible patterns that can occur in practical systems in order to prove the effectiveness of our proposal. We evaluate the system performance in terms of successful event report probability and energy consumption, comparing our results to the conventional on/off schemes with a certain probability of nodes being in the on state. With this premise, we think CA is a good alternative to determine the on/off process in WSNs. We compared the system performance of the GoL patterns compared to the classical approach and found the cases where the GoL scheme performs better. Full article

The shallow water equations (SWEs) model fluid flow in rivers, coasts, and tsunamis. Their nonlinearity challenges analytical solutions. We present a numerical algorithm combining the finite integration method with Chebyshev polynomial expansion (FIM-CPE) to solve one- and two-dimensional SWEs. The method transforms partial differential equations into integral equations, approximates spatial terms via Chebyshev polynomials, and uses forward differences for time discretization. Validated on stationary lakes, dam breaks, and Gaussian pulses, the scheme achieved errors below ${10}^{-12}$ for water height and velocity, while conserving mass with volume deviations under ${10}^{-5}$. Comparisons showed superior shock-capturing versus finite difference methods. For two-dimensional cases, it accurately resolved wave interactions over complex topographies. Though limited to wet beds and small-scale two-dimensional problems, the method provides a robust simulation tool. Full article

To investigate the oscillation modes of iced transmission lines, this study introduces a forcing term into the galloping equation and applies two discretization approaches: Discrete Method I (DMI), which directly transforms the partial differential equation into an ordinary differential form, and Discrete Method II (DMII), which first averages dynamic tension along the span. The finite element method is employed to validate the analytical solutions. Using a multiscale approach, amplitude-frequency responses under primary, harmonic, and internal resonance are derived. Results show that DMII yields larger galloping amplitudes and trajectories than DMI, with lower resonant frequencies and weaker geometric nonlinearities. In harmonic resonance, superharmonic and subharmonic modes (notably 1/2) are more easily excited. Under 2:1:2 internal resonance, amplitude differences in the vertical (z) direction are more sensitive to the discretization method, whereas the 1:1:1 case shows minimal variation across directions. These findings suggest that the choice of discretization significantly influences galloping behavior, with DMII offering a more conservative prediction. Full article

Pipe-insulating joints are common cathodic protection devices in long-distance oil and gas pipeline infrastructures. To ensure safety, they are often designed too conservatively, resulting in large dimensions, high self-weight, and substantial costs. This study analyzed an insulating joint under the most unfavorable conditions to identify the component of the maximum stress in the insulating joint, which is the right flange. Then, using parameterized finite element calculations, five independent dimensions of the right flange were combined and arranged to obtain a dataset of the right flange dimensions and their maximum stress. Subsequently, four different fitting algorithms were trained with this dataset, and the ridge regression algorithm, which showed the best predictive performance, was used to establish a surrogate model for calculating the maximum stress of the right flange. Finally, the surrogate model was combined with a genetic algorithm to determine the optimal design dimensions of the right flange. This study also provides examples verifying the accuracy and reliability of the surrogate model and genetic algorithm. In these examples, the maximum stress under the design dimensions given by the optimization algorithm has a maximum error of 8.98% and an average error of 4.63% compared to the preset maximum stress target, while the stress predicted by the surrogate model has a maximum error of 9.65% and an average error of 5.33% compared to the actual stress. This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints. Full article

This study presents the development of a discrete algorithm for interpreting ground-penetrating radar (GPR) data in vertically inhomogeneous media for the diagnostics of road structures. Experimental data were obtained using an OKO-2 GPR system, followed by primary radargram processing using the CartScan software. This included noise and interference filtering, as well as the initial estimation of the dielectric permittivity of detected layers. The resulting dataset was used to validate numerical algorithms for solving the forward and inverse problems of geolectrics. The proposed approach is based on minimizing a quadratic misfit functional between the calculated and observed values of the horizontal component of the electromagnetic field. The gradient of the functional required for optimization is obtained via the numerical solution of an adjoint problem. A discrete version of this problem was developed, which satisfies the properties of conservativeness and uniformity according to finite difference theory. The inverse problem reconstruction of dielectric permittivity is considered a non-destructive method for radargram interpretation. Assuming a piecewise-continuous medium structure eliminates the need for computing gradients at material interfaces. The proposed methodology enhances the accuracy and reliability of pavement condition assessment and holds practical value for road infrastructure monitoring. Full article

In this paper, we present a compact finite difference method for solving the cubic–quintic Schrödinger equation with an additional anti-cubic nonlinearity. By applying a special treatment to the nonlinear terms, the proposed method preserves both mass and energy through provable conservation properties. Under suitable assumptions on the exact solution, we establish upper and lower bounds for the numerical solution in the infinity norm, and further prove that the errors are fourth-order accurate in space and second-order in time in both the 2-norm and infinity norm. A detailed description of the nonlinear system solver at each time step is provided. We validate the proposed method through numerical experiments that demonstrate its efficiency, including fourth-order convergence (when sufficiently small time steps are used) and machine-level accuracy in the relative errors of mass and energy. Full article

Objective: This study aims to evaluate the stress distribution on endodontically treated anterior teeth restored using different restorative materials and different post lengths versus endocrowns employing finite element analysis (FEA). Methods: An extracted human central incisor tooth with a fully formed apex was scanned using high-resolution cone beam computed tomography (CBCT) to generate 3D finite element models. Six models of restorations of badly destructed central incisor were grouped according to the type of ceramic material and post length versus endocrown restorations. Group V-L: Vita Enamic, long post (10 mm intra-radicular), Group C-L: Celtra Duo, long post (10 mm intra-radicular), Group V-Sh: Vita Enamic, short post (3 mm intra-radicular), Group C-Sh: Celtra Duo, short post (3 mm intra-radicular), Group V-E: Vita Enamic endocrown (3 mm intra-radicular), and Group C-E: Celtra Duo endocrown (3 mm intra-radicular). A static load of 200 N was applied to the palatal surface at a 45 degree angle to the tooth’s long axis. The maximum equivalent von Mises stress and maximum principal stress were analyzed at four locations: the finish line, coronal third of the root (12 mm from the apex), middle third of the root (8 mm from the apex), and apical third of the root (4 mm from the apex). Results: Group C-L exhibited the highest maximum VM stress and PS at the finish line, in addition to the highest maximum VM stress and PS at the root apical third, while group C-Sh reported the least maximum VM stress at the root apical third among the groups. All Celtra Duo groups reported higher maximum VM stress than the corresponding groups of Vita Enamic at the finish line and root coronal thirds. However, at the root middle and apical thirds, both materials recorded similar stresses. Conclusions: Short posts and Vita Enamic endocrowns showed minimal stress, especially at the finish line, while long posts increased stress and fracture risk. The findings support conservative restorations without posts, although clinical validation is needed to confirm their long-term effectiveness and safety. Full article

Previous research on non-finite catenative complementation (for example, start Ving/to V; force NP into Ving/to V) has largely been restricted to BrE and/or AmE. The present study seeks to expand the regional coverage of such research by analysing a set of catenative constructions in two large web-derived corpora, GloWbE and NOW, both of which comprise 20 subcorpora representing different national varieties of English. The implications of the findings for such diachronically relevant phenomena as colloquialisation and grammaticalisation are considered. For example, the dominance of bare infinitivals over to infinitivals with catenative help is suggestive of auxiliarisation, an interpretation supported by the semantically bleached sense of generalised causation associated with help, and historical evidence of support for the bare-infinitival variant in colloquial registers. Notable findings include American English epicentrality—and possibly hypercentrality—in many of the results, with Canadian English and Philippine English in particular sharing the American aversion to from-less “prevent NP Ving” and “help to V”; the occasional conservative tendency of the Outer Circle varieties to resist diachronic trends associated with the reference varieties (such as the rise of “fear Ving” at the expense of “fear to V”); and high scores for the African Englishes, suggested to be attributable to the popularity of “serial verb” constructions in a number of African languages. Full article

This paper advances the forward extrusion process by integrating sustainable methodologies and optimizing energy efficiency. This research investigates the impact of die geometry and elongation coefficients on energy usage and process efficiency, employing finite element method (FEM) simulations alongside empirical analysis. Artificial neural networks and experimental data were utilized to predict process energy. The experimental study utilized flat, conical, and arc-shaped dies to extrude lead profiles exhibiting different elongation coefficients. The study analyzed the dynamics of material flow, energy requirements, and maximum forces. Patterns of deformation, distribution of tension, and losses of energy were discerned, with finite element models enhancing understanding of these phenomena. The mathematical framework forecasting the peak extrusion force in relation to elongation parameters was substantiated via residual diagnostics and regression analysis. The findings indicate that conical and arc dies can conserve up to 15% of the energy in comparison to flat dies, thereby improving material flow and reducing deformation forces. This comprehensive strategy provides practical solutions to reduce energy consumption and improve metal forming processes, thereby enhancing industrial efficiency and sustainability. The results not only benefit industry but also align with environmental objectives, thereby increasing the efficiency and sustainability of extrusion operations. Full article

Shear lag stresses increase significantly in cracked concrete box girders; however, most existing models assume intact sections and are, therefore, unsuitable for rapid field diagnosis. This study integrates a stepped stiffness model with deflection influence lines to accurately capture the mechanical response of damaged, simply supported box girders. Regions containing flexural cracks are assigned a reduced bending stiffness ${EI}^{\prime }$, whereas intact zones retain the original stiffness $EI$. A closed-form stiffness-reduction coefficient $\phi ={EI}^{\prime }/EI$ is obtained from crack geometry and, independently, from the second derivative of the deflection influence line. Embedding $\phi$ in a variational shear lag formulation yields explicit expressions for flange displacement and normal stress without numerical iteration. This approach is validated by finite element simulations of a plexiglass scale model with four preset damage levels and by a load test on a 30 m prestressed concrete box girder bridge. Field measurements show that midspan stiffness decreased to 81% of the as-built value; the proposed method reproduces this value with a deviation of 3%. Predicted upper-flange stresses differ from measured values by 5.7–13.6% and from finite element results by less than 10% for damage ratios up to 40%. The second derivative of the influence line difference exhibits a distinct peak at the cracked region, accurately localizing the damage. Compared with classical formulas, the proposed model (i) is fully closed-form, (ii) links global deflection data to local shear lag stresses, and (iii) delivers conservative estimates suitable for routine bridge assessment. Full article

Accurately simulating the thermal behavior of wheel–brake shoe friction on long downhill ramps is challenging due to the complexity of modeling appropriate heat source models. This study investigates heat generation during the frictional braking process of freight train wheels and brake shoes under long-slope conditions. Four heat source models—constant, modified Gaussian, sinusoidal, and parabolic distributions—were developed based on energy conservation principles and validated through experimental data. A thermomechanical coupled finite element model was established, incorporating a moving heat source to analyze the effects of different models on wheel tread temperature distribution and its evolution over time. The results show that all four models effectively simulate frictional heat generation, with computed temperatures, deviating by only 6.0–8.2% from experimental measurements, confirming their accuracy and reliability. Among the models, the modified Gaussian distribution heat source, with its significantly higher peak local heat flux (2.82 times that of the constant model) and rapid attenuation, offers the most precise simulation of the non-uniform temperature distribution in the contact region. This leads to a 40% increase in the temperature gradient variation rate and effectively reproduces the “hot spot” effect. The new non-uniform heat source model accurately captures local temperature dynamics and predicts frictional heat transfer and thermal damage trends. The modified Gaussian distribution model outperforms others in simulating local temperature peaks, offering support for optimizing braking system models and improving thermal damage prediction. Future research will refine this model by incorporating factors like material wear, environmental conditions, and dynamic contact characteristics. Full article