Numerical Analysis Techniques Research Articles

Improved electrocatalytic activity of selenide nanoparticle for oxygen evolution reaction

Oxygen Evolution Reaction (OER) plays a vital role in water electrolysis, but its slow kinetics and expensive catalysts are obstacles to widespread use. To improve the OER activity, it is crucial to create a well-structured design for electrocatalysts based on transition metals, which may be applied to a conducting polymer substrate. This research reports a facile hydrothermal synthesis and remarkable catalytic behavior of NbSe2/g-CN as an OER catalyst in an alkaline condition. The fabricated electrocatalysts were examined utilizing numerous analytical techniques to assess their crystallinity, oxidation states and morphology. NbSe2/g-CN shows enhanced electro-catalytic behavior to OER in alkaline solution (1.0 KOH) with minor overpotential (196 mV) and Tafel slop (38 mV/dec) than pristine NbSe2 electrocatalyst was associated with the exceptional conductivity of NF and its highly porous structure, along with a greater SSA. In addition, the durability of the electrocatalyst was examined via cyclic stability and chronoamperometry study over 40 h. This study demonstrates that TMSe with specific morphology can improve electrocatalytic activity when combined with g-CN, demonstrating its potential for reliable and eco-friendly energy generation

Error analysis for local discontinuous Galerkin semidiscretization of Richards’ equation

Abstract This paper concerns an error analysis of the space semidiscrete scheme for the Richards’ equation modeling flows in variably saturated porous media. This nonlinear parabolic partial differential equation can degenerate; namely, we consider the case where the time derivative term can vanish, i.e., the fast-diffusion type of degeneracy. We discretize the Richards’ equation by the local discontinuous Galerkin method, which provides high order accuracy and preserves stability. Due to the nonlinearity of the problem, special techniques for numerical analysis of the scheme are required. In particular, we combine two partial error bounds using continuous mathematical induction and derive a priori error estimates with respect to the spatial discretization parameter and the Hölder coefficient of the nonlinear temporal derivative. Finally, the theoretical results are supported by numerical experiments, including cases beyond the assumptions of the theoretical results.

Research on the crack formation mechanism of shaped charge blasting and the new dual-shaped charge blasting technology

Shaped charges are extensively utilized in various rock engineering fields for directional fracturing. Numerous scholars have conducted extensive research on this topic, yielding significant results and widespread application in engineering projects. Efforts have focused on improving the directional fracture effects and fully utilizing the energy generated by the explosion to enhance the directional blasting effects of shaped charges and minimize damage to the rock mass in areas not targeted by the shaped energy. This approach aims to preserve the integrity and stability of the rock mass in the areas unaffected by the directional fracture, thereby reducing damage to the surrounding rock. This study builds on the foundations of explosion mechanics. It incorporates a novel digital laser dynamic caustic line experiment system and pressure fields, and numerical analysis techniques. The research systematically analyzes the process of explosive action in shaped charges and proposes a new type of dual polymer charge. This novel charge is compared to traditional and common charges. The findings revealed that, compared to standard-shaped charges, the new dual-shaped charge achieves a more effective directional fracturing, The rock damage is less in the direction of non-gathering energy. Under the conditions of the same amount of explosive and the same decoupling coefficient, The crack propagation length of common charge is 1.34 times of the diameter of the gun hole, the crack propagation length of shaped charge is 10.17 times of the hole diameter, The crack propagation length of the new dual-charge is 19.67 times of the hole diameter. HIGHLIGHTS In this paper, a new type of dual-charge is proposed. The findings revealed that, compared to standard-shaped charges, the new dual-shaped charge achieves a more effective directional fracturing, The rock damage is less in the direction of non-gathering energy. Under the conditions of the same amount of explosive and the same decoupling coefficient, The crack propagation length of common charge is 1.34 times of the diameter of the gun hole, the crack propagation length of shaped charge is 10.17 times of the hole diameter, The crack propagation length of the new dual-charge is 19.67 times of the hole diameter. 1.Following the charge explosion, influenced by the shaped charge tube, the detonation wave and explosive gas alter, expanding outward in an approximate "elliptical" shape. The explosion stress field distribution is approximately "one"-shaped in the direction of energy concentration. The primary explosive crack expands along the direction of energy accumulation, while the secondary cracks predominantly distribute in the perpendicular direction. The seam width and the transmission coefficient (material) influence the condenser’s concentration effect. 2.Compared to ordinary charge blasting, shaped charge blasting exerts a pronounced guiding effect on the explosion stress field. The stress field primarily transfers along the direction of energy concentration, with the stress being markedly greater in this direction than in the direction of non-concentrated energy. In comparison, dual charge blasting undergoes two convergence effects, with longer durations and distances of convergent action. The stress field generated by dual-charge blasting is significantly greater than that of the shaped and common charges, offering enhanced effects. 3.Agglomeration length is a crucial factor in the agglomeration effect. Explosion energy directly transfers to the solid medium via the coalseam, minimizing explosion energy loss in the air medium and controlling the detonation wave shape and explosive gas flow in the energy accumulation direction, resembling "one." The dipolymer charge notably extends crack propagation length in the polymer direction and mitigates damage in the non-polymer direction.

Fractional Stochastic Partial Differential Equations: Numerical Advances and Practical Applications—A State of the Art Review

This article aims to provide a comprehensive review of the latest advancements in numerical methods and practical implementations in the field of fractional stochastic partial differential equations (FSPDEs). This type of equation integrates fractional calculus, stochastic processes, and differential equations to model complex dynamical systems characterized by memory and randomness. It introduces the foundational concepts and definitions essential for understanding FSPDEs, followed by a comprehensive review of the diverse numerical methods and analytical techniques developed to tackle these equations. Then, this article highlights the significant expansion in numerical methods, such as spectral and finite element methods, aimed at solving FSPDEs, underscoring their potential for innovative applications across various disciplines.

Unveiling the synthesis, characteristics, electrical conductivity, photocatalytic activity, and electrochemical activity of eco-friendly zinc oxide nanoparticles

The Nigella Sativa seeds were utilized for the environment-friendly zinc oxide nanoparticles (ZnO NPs), as evident by the observation of a white precipitate. Numerous analytical techniques, such as XRD, FTIR, UV–vis, SEM, and EDX, were utilized to describe the specimen's structural, optical, and electrical properties. XRD analysis was used to confirm that the ZnO NPs were crystalline. An absorbance peak at 401 nm was observed in the UV–vis, indicating that the ZnO NPs have a 2.91 eV bandgap. Functional groups are present in ZnO NPs, as seen by the FTIR graph. The nanoparticles' spherical form and average size of 37.9 nm were confirmed by the SEM image. EDX analysis confirmed the composition of the nanoparticles, with zinc accounting for 73.17% and oxygen for 26.83%. ZnO NPs demonstrated excellent electrical conductivity because of their higher surface-to-volume ratio. Additionally, the synthesis of ZnO NPs exhibited effective degradation of methylene blue dye. These results point to potential applications in several domains, including electronics, biomedical devices, industry, and agriculture, and they call for immediate follow-up research.

Research on Dynamic Characteristic Coefficients of Integral Squeeze Film Damper

Integral squeeze film damper (ISFD) is a new type of structure that appeared on the basis of traditional squeeze film damper (SFD). Since the oil film in ISFD is a segmented structure without annular flow, the nonlinearity of the oil film force has been improved to a great extent. The dynamic characteristic coefficients of ISFD have a close relationship with its damping performance. This work investigates and studies the dynamic characteristic parameters of ISFD by means of numerical analysis and experimental validation techniques in order to examine the dynamic features and unveil the damping mechanism. The ISFD solid and fluid analysis models are created, and the computational fluid dynamics (CFD) and mechanical performance analyses are completed. The force acting on the ISFD’s S-type elastomer under excitation conditions is revealed in the mechanical property analysis, and the flow characteristics of the internal oil film are investigated in the CFD analysis. It is discovered that the ISFD has good linear damping and stiffness characteristics, and numerical analytical values for the ISFD’s damping and stiffness coefficients are obtained. By constructing a bi-directional excitation test rig, the experimental values of the ISFD stiffness coefficient and damping coefficient are determined. These values are in close agreement with the results of the numerical analysis, confirming the accuracy of the ISFD’s numerical analysis conclusions.

Artificial neural network and ANFIS approaches for mechanical properties prediction and optimization of a turbine blade treated by laser shock peening

This research article covers a comprehensive investigation on the prediction and optimization of residual stresses, plastic deformations and damage induced by laser shock peening (LSP) on a thin Ti-6Al-4 V leading edge sample of a turbine blade. The study is based on a two-part approach: the first part involves a numerical simulation of the LSP process and the characterization of its effects on the material. The finite element analysis (FEA) is used to simulate the complex interactions between laser parameters, material properties and mechanical response. This numerical analysis generates valuable insights into the residual stress distribution, the plastic deformation and the potential damage within the sample being treated. Based on the numerical results, the second part highlights the novel application of the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS) methods. By taking advantage of the strength of ANN and ANFIS, the models are able to learn accurately from all the data generated by numerical simulations, allowing them to precisely predict and optimize the effects induced by LSP: residual stresses, plastic strains and damage. This paper provides a significant contribution to the field of materials science and engineering, by offering an in-depth comprehension of the LSP process impact on Ti-6Al-4 V leading-edge turbine blade specimens. The combined utilization of numerical analysis and artificial intelligence AI-driven techniques offers a comprehensive approach to optimize the LSP process, leading to the fatigue resistance improvement and service life extension of turbine blades and other critical aerospace components. The proven capability of ANN and ANFIS enables innovative solutions in aerospace engineering and surface treatment technologies, promoting the AI implementation in materials processing and design.

Boosting asymmetric measurement-device-independent quantum key distribution via numerical-analysis technology

Asymmetric measurement-device-independent quantum key distribution (MDI-QKD) enables building a scalable, high-rate quantum network with an untrusted relay in real-world scenarios. In this study, we improve the performance of asymmetric MDI-QKD using numerical analysis techniques. Simulation results show a twofold increase in tolerance to basis misalignment compared to the previous state-of-the-art method. Specifically, for instances of substantial basis misalignment, the key rate increases by an order of magnitude, and the maximum communication distance extends by 20 km. Our work significantly enhances the robustness and feasibility of asymmetric MDI-QKD, thereby promoting the widespread deployment of MDI-QKD networks.

Design and simulation of structural durability of passenger car front in collision

In this paper, design and calculate a damping system with HYPERMESH software. Research using LS-DYNA software to analyze finite element model and structural strength of passenger car front and violate the safe space on impact. Simulation results with a speed of 50 km/h according to ECE R66 standards show a reduction of 27%. Meet the requirements on the condition of the car head structure. The safe space is not violated according to ECE R66 standards in a head-on collision. Additionally, the numerical analysis techniques employed in this study could be used for future research on collisions between maritime structures including fishing boats and aquaculture engineering. Keywords: ECE R66 standard, HYPERMESH software, LS-SYNA software, collision, passenger car, damping system.

Solving a System of One-Dimensional Hyperbolic Delay Differential Equations Using the Method of Lines and Runge-Kutta Methods

In this paper, we consider a system of one-dimensional hyperbolic delay differential equations (HDDEs) and their corresponding initial conditions. HDDEs are a class of differential equations that involve a delay term, which represents the effect of past states on the present state. The delay term poses a challenge for the application of standard numerical methods, which usually require the evaluation of the differential equation at the current step. To overcome this challenge, various numerical methods and analytical techniques have been developed specifically for solving a system of first-order HDDEs. In this study, we investigate these challenges and present some analytical results, such as the maximum principle and stability conditions. Moreover, we examine the propagation of discontinuities in the solution, which provides a comprehensive framework for understanding its behavior. To solve this problem, we employ the method of lines, which is a technique that converts a partial differential equation into a system of ordinary differential equations (ODEs). We then use the Runge–Kutta method, which is a numerical scheme that solves ODEs with high accuracy and stability. We prove the stability and convergence of our method, and we show that the error of our solution is of the order O(Δt+h¯4), where Δt is the time step and h¯ is the average spatial step. We also conduct numerical experiments to validate and evaluate the performance of our method.

Experimental and numerical analysis of drilled‐ and molded‐hole glass fiber reinforced polymer matrix (GFRP) composites

AbstractDrilling glass fiber reinforced polymer matrix (GFRP) composites typically causes burrs, splintering, and microcracks within the GFRP structure, as well as delamination, fiber pull‐out, and thermal degradation of the polymer matrix. Designing and manufacturing molded‐hole GFRP components, as opposed to drilling, has recently been proposed as a promising method for overcoming the issues associated with drilling, for which there is limited research. Specifically, the mechanical response of molded‐hole GFRP has not been fully addressed in the literature. In the present study, molded and drilled GFRP composites with epoxy matrix were fabricated by hand lay‐up, and then the samples were analyzed utilizing experimental and numerical analysis techniques. Stress and strain analyses of GFRP samples were performed in Ansys Transient Structural Analysis. Although the fiber orientations of the layer geometries [0°/90°] and 3D models were the same, an additional layer was defined in the direction of the fiber orientation [45°/−45°] of molded‐hole composites to simulate the fiber accumulation effect. Experimental findings revealed that the flexural strength of molded composites was 12% greater than that of drilled composites. According to the numerical analysis, 98.7% proximity was achieved between the experimental and numerical results. Thus, the present study has provided numerical modeling to understand the flexural strength of molded composites for the first time, which will contribute to the increased use of molded composites in numerous applications in the fields of aerospace, automotive, and marine.Highlights Drilled‐ and molded‐hole GFRP composites were produced by hand lay‐up. Flexural properties of the composites were examined via 4P bending tests. Flexural strength of molded composites was higher than that of drilled ones. 98.7% proximity was achieved between the experimental and FEM results. A unified FEM method is proposed for the molded‐hole composites.

Enantiomeric purity of synthetic therapeutic peptides: A review.

Synthetic therapeutic peptides are a complex and popular class of pharmaceuticals. In recent years, peptides with proven therapeutic activity have gained significant interest in the market. The determination of synthetic peptide enantiomeric purity plays a critical role in the evaluation of the quality of the medicine. Since racemization is one of the most common side reactions occurring in AAs or peptides, enantiomeric impurities such as D-isomers can form during the peptide synthesis or can be introduced from the starting materials (e.g., AAs). The therapeutic effect of a synthetic or semi-synthetic bioactive peptide molecule depends on its AA enantiomeric purity and secondary/tertiary structure. Therefore, the enantiomeric purity determination for synthetic peptides is supportive for interpreting unwanted therapeutic effects and determining the quality of synthetic peptide therapeutics. However, enantiomeric purity analysis encounters formidable analytical challenges during chromatographic separation, as D/L isomers have identical physical-chemical properties except stereochemical configuration. To ensure peptides AA stereochemical configuration whether in the free or bound state, sensitive and reproducible quantitative analytical method is mandatory. In this regard, numerous analytical techniques were emerged for the quantification of D-isomeric impurities in synthetic peptides, but still, very few reports are available in the literature. Thus, the purpose of this paper is to provide an overview of the importance, regulatory requirements, and various analytical methods used for peptide enantiomeric purity determination. In addition, we discussed the available literature in terms of enantiomeric impurity detection, common hydrolysis procedural aspects, and different analytical strategies used for sample preparation.

Synthesis, XRD, spectroscopic (UV–Vis, IR, EPR) and biological evaluations of cobalt(II)-ciprofloxacin complex as antimicrobial agent: In silico molecular docking and ADME

Cobalt(II)-Ciprofloxacin complex ([Co(Cip)2(H2O)2].2(H2PO4).8(H2O); Cip=Ciprofloxacin) containing phosphoric acid was synthesized and its structure was characterized by numerous analytical techniques such as FT-IR (Fourier Transform Infrared), UV–Vis (Ultraviolet-Visible), EPR (Electron Paramagnetic Resonance), TGA (Thermogravimetric Analysis), elemental analysis and SCXRD (single crystal X-ray diffraction) for structural elucidation. According to XRD data, the environment of Cobalt has octahedral geometry with ciprofloxacin ligand bonded as bidentate (keto and carboxyl group) and aqua ligand. It was revealed that the metal complex left metal oxide and other residues as the final product in the multi-step decomposition TGA curve in the range of 20–1000 °C. The contribution of intermolecular interactions that lead to molecular packing was analyzed using Hirshfeld surface analysis. The synthesized complex was tested for antimicrobial activity against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Candida albicans. We conducted a molecular docking study using AUTODOCK 4.2 to investigate the binding energy and interaction modes of a highly potent microbial complex with three different enzymes: S. aureus DNA gyrase (PDB ID: 2XCT), GyrA (PDB ID: 3LPX), and mycobacterium tuberculosis gyrase type IIA topoisomerase (PDB ID: 3UC1).

Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems

Solar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics of solar panels, presenting a comprehensive mathematical model capturing the interdependencies between current, voltage, power, solar irradiation, and temperature. Existing numerical MPPT techniques are explored to provide their advantages and disadvantages. The proposed algorithm, formulated in MATLAB, encapsulates essential solar panel variables and undergoes rigorous dynamic testing in the Simulink® environment under diverse solar irradiation and temperature scenarios. These results are visually represented through graphs and tabulations. A subsequent section offers a simulation-driven comparative review of the proposed algorithm against established methodologies. The article culminates with conclusions drawn from the empirical findings and outlines promising avenues for future research.

Scour Impact on the Horizontal Bearing Capacity of Pier-Type Dolphin Structures

A study using numerical analysis techniques was conducted to examine the scour effect of pier-type dolphin structures installed in the domestic marine environment, and the effect of scour on horizontal bearing capacity was examined. In this study, we designed the berthing structures, taking into account the environmental and ground conditions of the target maritime area, and after calculating the predicted scour area, stability evaluation was performed by removing the ground elements of the area. The increase in scour depth was found to induce a direct decrease in horizontal bearing capacity due to soil loss in contact with the foundation, establishing a relationship that increases horizontal displacement. However, in the foundation designed to withstand the design load by reflecting the safety rate, the increase in horizontal displacement formed by possible scour is not large, which did not have a dominant effect on the horizontal bearing capacity of the foundation. In the future, research is required to analyze the impact of each factor and formalize evaluation and design techniques to evaluate the scour safety of marine foundations and pier-type structures installed in various ground conditions and structural formats.

Enhancing perovskite solar cell performance with a novel theoretical method and artificial neural networks

One of the most promising solutions for photovoltaics in space is perovskite solar cells (PSCs), which have intrinsic microscales in thickness. PSCs have power conversion efficiencies (PCEs) that are almost 26%, however, the stability issue prevents their commercialization. One of the PSC's primary operating difficulties is phase velocity performance, which should be enhanced stability in complex scenarios. This study investigates the size-dependent dynamic behavior of PSCs made of 3D-FG material at the metal layer site. The current relevant structure in the real-world situation that takes into consideration surface boundary domains is described mathematically using the 3D-elasticity theory while taking into account all strain–stress components. By building a multi-scale dynamics framework on the modified couple stress theory, the wave propagation analysis is broadened to encompass microscale composites. Considering the possibility of solving the size-dependent motion equations using the jointed analytical–numerical techniques. In addition to being modeled mathematically, artificial neural networks are used to train the findings in order to analyze solar cells in the future for the production of green energy. The artificial neural network's training and test datasets are used in batches to create the aforementioned artificial intelligence. The results show that, with an axial radius ratio of more than 1, the panel becomes more stable because from this point the change in sensitivity of the phase velocity to the 3D functionally graded material changes only slightly and gradually. Another important outcome is that with an increase in the y-direction curvature ratio, the sensitivity decreases, but this change is maximally 10%. The study's conclusions will help improve the impact-bearing capability and safety of the PSC energy-collecting devices by enhancing their astronautic design and space deployment.

Synthesis, Characterization, and Performance of Nano-Metal-Oxide (Al2O3) Blended Biochar for the Removal of Iron from Contaminated Water for Enhanced Kinetic and Adsorption Studies

This paper explored synthesis, characterization, and adsorption modeling for the application of nano-metal-oxide (Al2O3) blended biochar (NMOBC) derived from date palm waste in removing iron (Fe3+) from contaminated water. The pseudo-second-order model provided a goodness-of-fit that was superior to the pseudo-first-order kinetic model based on the value of R2 with all of the initial concentrations. The Elovich kinetic model also presented a good fit, indicating that chemisorption is a predominant mechanism in the adsorption process. The Langmuir, Freundlich, Redlich-Petersons, Temkin, and Sips models provided an exclusive perspective of the adsorption dynamics based on the high value of R2. However, the Sips model suggested the best fit of all of the employed models, with the lowest RMSE value of 0.0239 mg/g and the maximum adsorption capacity of 22.680 mg/g for NMOBC. Both adsorbents were effectively regenerated and reused in multiple cycles, thus leading to sustainable practices. Numerous analytical techniques, including SEM/EDX, FTIR, and BET, were employed in characterizing the structural, morphological, and functional properties of the synthesized NMOBC and BC. Subsequently, it revealed that the adsorption process and the role of various interactions are attributed to surface area, porosity, and ion exchange.

An Updated Review on the Chemistry, Biological Characteristics and Analytical Techniques of Dapagliflozin

Background: Globally, type 2 diabetes mellitus (T2DM) prevalence is increasing. A patient must have lifetime therapy for diabetes to manage it and prevent any complications. There are many different medications that can be used to treat Type 2 diabetes. Still, almost all of them concentrate on the declining insulin sensitivity and secretion that are associated with the onset of the illness. Methods: There is growing interest in the development of innovative anti-diabetic medications that are not insulin-reliant because treatments with such insulin-dependent mechanisms of action usually lose their effectiveness over time. One such technique is the inhibition of renal glucose reuptake. Results: Dapagliflozin, the first line of selective sodium-glucose cotransporter 2 inhibitors that re-duce renal glucose reabsorption, is currently being developed as a therapy for Type 2 diabetes. Numerous analytical techniques have been developed for its detection, measurement, and regular quality control procedures. Conclusion: This review deliberates a thorough discussion on the chemistry of Dapagliflozin, all of its pharmacological actions with analytical and bioanalytical analyses, and more information on the clinical trials.

Mode-matching technique for analyzing scattering in elastic shell chambers: Applications in trifurcated waveguide systems

This study presents a comprehensive investigation into the behavior of elastic shell chambers used for noise control and vibration mitigation in engineering applications. The study focuses on the analysis of fluid–structure coupled waves in a cylindrical waveguide system with trifurcated structures and membrane discs. The mode-matching technique is employed to analyze the scattering characteristics of the elastic chamber shell. Numerical simulations and analytical techniques are used to explore the interplay between material properties, geometric configurations, and loading conditions. The Galerkin formulation is utilized to model the response of membrane bridging discs and elastic shell regions. Linear algebraic systems are solved numerically to obtain the scattering amplitudes, and the convergence of the obtained solution is assessed. The energy conservation law and transmission loss are analyzed to evaluate the accuracy and convergence behavior of the system. The numerical results provide insights into the scattering behavior of the structure, showing the influence of frequency, chamber radius, and edge conditions. The findings highlight the importance of parameter selection and boundary conditions in guiding structures and provide a basis for design optimization.

Numerical investigation and deep learning approach for fractal–fractional order dynamics of Hopfield neural network model

This paper investigates the dynamics of Hopfield neural networks involving fractal–fractional derivatives. The incorporation of fractal–fractional derivatives in the neural network framework brings forth novel modeling capabilities, capturing nonlocal dependencies, complex scaling behaviors, and memory effects. The aim of this study is to provide a comprehensive analysis of the dynamics of Hopfield neural networks with fractal–fractional derivatives, including the existence and uniqueness of solutions, stability properties, and numerical analysis techniques. Numerical analysis techniques, including the Adams–Bashforth method, are employed to accurately simulate the fractal–fractional Hopfield neural network system. Moreover, the obtained numerical data serves as validation for developing predictions using Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) neural network methods. The findings contribute to the advancement of both fractional calculus and neural network theory, providing valuable insights for theoretical investigations and practical applications in complex systems analysis.