The dual-pressure evaporation Organic Rankine Cycle (ORC) consists of two compression processes, two evaporation processes, and two expansion processes, and is becoming more prevalent than single-pressure evaporation ORCs due to its higher performance and maximum net power output. This study investigates different heat sources analysis in a simulated parametric dual-pressure evaporation ORC according to the assessment design process. The current dual-pressure evaporation ORC makes a comparison between R245fa, an old refrigerant, and R1233zd(E), a substitute for R245fa, as working fluids, paying attention to three water temperatures (100, 125, and 150 ºC) as a heat source to generate maximum net power output. Based on designing an assessment process for dual-pressure evaporation ORC at 100 °C and 125 °C heat sources, R1233zd(E) is compared with R245fa, revealing an improvement of 9.58 kW and 16.14 kW in maximum net power output. Furthermore, according to the first and second laws of efficiency, R1233zd(E) exhibits improvements of 0.09% and 0.56%, as well as 0.15% and 1.04%, respectively. The pressure rise in low and high-pressure compression processes, parallel with a higher exergy flow rate in evaporation processes of R1233zd(E), demonstrates a direct and positive influence with a maximum net power output. At 150 °C, the power generated by the lower-pressure turbine improved by 28.1 kW in R1233zd(E) compared with R245fa.
The article presents a stochastic approach to the shape optimization of compressed rods, taking into account random deviations of Young’s modulus and the second moment of area. The parameters are described as stationary random fields with a specified correlation length, and their influence on the critical buckling load is determined using a first-order perturbation expansion. The obtained expressions for the expected value and variance of the critical load made it possible to assess the sensitivity of the structure to local stiffness disturbances. Subsequently, a probabilistic optimization problem was formulated within a family of Gaussian-type profiles, with the aim of minimizing mass while maintaining the required level of reliability. Numerical analysis shows that accounting for uncertainties makes it possible to obtain a rod approximately 12 % lighter than the reference rod, without reducing load-carrying capacity. The presented approach demonstrates that modeling
This study investigated the effect of cylindrical-shaped hybrid nanoparticles on the flow of magnetohydrodynamic blood through a narrowed artery, considering the impact of body acceleration and the variable viscosity of blood, which is temperature-dependent. The mathematical flow equations have been converted into a dimensionless form, and the solution is obtained using the finite difference scheme. Graphs are used to illustrate the influence of controlling flow parameters on various physical properties such as velocity, concentration, temperature, heat transfer coefficient, mass transfer coefficient, flow rate, and wall shear stress. It is observed that the velocity profiles exhibit a pronounced enhancement with increasing values of the parameters solutal Grashof number, Prandtl number, and body acceleration parameter, indicating their direct role in accelerating the flow dynamics. In contrast, the parameters magnetic field and Reynolds number exert a suppressing influence, leading to a noticeable reduction in velocity profile. Furthermore, the temperature profiles rise with increasing concentration of copper nanoparticles, alumina oxide nanoparticles, and hybrid nanoparticles, due to the significant enhancement in effective thermal conductivity. This improved heat transport capacity facilitates greater energy absorption and elevates the overall temperature profile of the blood. Finally, the WSS increases with a rise in the thermal Grashof number, as buoyancy-driven forces strengthen blood motion near the arterial wall. In contrast, an increase in the magnetic field parameter suppresses blood velocity through Lorentz force resistance, thereby reducing wall shear stress. The findings could be valuable insights into blood flow beahviour in the stenosed artery, applied therapeutically within the biomedical sciences.
EN24 alloy steel is widely used in high-strength engineering components such as shafts, gears and spindles, where machining performance and surface integrity are critical for reliable service. The present work investigates the influence of spindle speed, feed rate and depth of cut on material removal rate (MRR) and surface roughness (Ra) during milling of EN24 steel. A Taguchi L27 orthogonal array is employed to design the experiments, and three replications are carried out for each condition. Signal-to-noise ratio analysis and analysis of variance (ANOVA) are used to identify the most significant cutting parameters for both responses. The results indicate that depth of cut is the dominant factor for MRR, contributing more than 80% of the total variation, whereas feed rate is the most influential parameter for Ra. Regression models are developed to predict MRR and Ra as functions of the cutting parameters, and confirmation experiments are performed at the optimal settings. For MRR, the optimum combination of 600 rpm spindle speed, 118 mm/min feed rate and 0.5 mm depth of cut yields a prediction error below 1%, while for Ra the optimal condition of 600 rpm, 102 mm/min and 0.1 mm results in a prediction error of about 2%. The study demonstrates that the Taguchi approach provides an effective and economical framework for optimising metal machining of EN24 steel, enabling higher productivity with controlled surface roughness, and contributes to improved, more sustainable manufacturing practice..
This study experimentally investigates the influence of annular fin geometry on thermo-hydraulic performance under crossflow forced-convection conditions. Four heat sink configurations—a constant cross-section fin, a stepped fin, a modified stepped fin, and a triangular fin—were tested using an open-channel rig over 36 operating conditions formed by three air velocities (2–6 m/s) and three electrical input powers (13–39 W). The results show that the Nusselt number increases with Reynolds number for all geometries, with average enhancements of approximately 10–15%, 20–25%, and 30–35% for the stepped, modified stepped, and triangular fins, respectively, compared to the baseline. Pressure drop also increased with Reynolds number, with the modified stepped fin exhibiting the highest penalty, while the triangular fin maintained a more moderate increase. At fixed Reynolds numbers, the effect of input power was secondary, confirming the dominance of flow inertia and geometry. Geometry-specific Nusselt number correlations with coefficients of determination exceeding 0.95 were developed, and the analytical model for the baseline fin was validated against experimental data with deviations below 2%.
The contact between the artificial leg (prosthesis) and an amputees residual limb is a significant factor in the success of prosthetic fitting and overall comfort. An improper interface can result in issue such as pressure sores, skin irritation, residual limb pain and discomfort for the amputee. The prosthetic socket bridges the gap between the two. In this work, the customized complex geometry of the prosthetic socket is developed using advanced 3D scanning technology of the residual limb. Following the accurate 3D scan of the residual limb, the development of a Computer-Aided Design (CAD) model is a critical next step in the development of customized prosthetic socket. The raw 3D scan data undergoes a process that transforms the information into a more refined and functional design suitable for manufacturing the socket. Given the strength-to-weight ratio already presented as a challenge for socket, the prosthetic socket needs to be made as light as possible. This makes it challenging to maintain strength and optimal structure for the prosthetic socket by just removing unwanted material; therefore, the topology optimization technique is adopted. The process revealed that extra material existed at the stress location on the socket. In the following stage a new customized design is developed possessing low weight maintaining the structural as well as functional integrity of the socket. The final geometry of the customized socket is almost impossible to fabricate from conventional method. Hence it was printed using Fused Deposition Method (FDM), and used for the patient.
Research into biodiesel-based fuels for diesel engines has accelerated due to the growing need for sustainable fossil fuel substitutes. The combustion and emission properties of a hybrid biodiesel made from algal oil and Calophyllum inophyllum oil that has been converted into methyl esters are examined in this study. In order to enhance combustion efficiency, titanium dioxide (TiO₂) nanoparticles have been employed as nano-additives. A single-cylinder, four-stroke, water-cooled, variable compression ratio (VCR) diesel engine had been employed for the experiments under different load conditions like 3 Kg to 12 Kg along with compression ratio 16 and 18 . Hybrid biodiesel blends B10, B15, B20, B25, B30, and B35 were used to run the engine, and the outcomes were contrasted with traditional diesel fuel. Combustion analysis revealed that the B25 blend for 12 Kg load and compression ratio 18 delivered an improvement in brake power of about 6 % and an 8% decrease in brake-specific fuel usage when measured against diesel. Analyses of emissions revealed notable 5% decreases in carbon dioxide (CO2), while nitrogen oxide (NOx) emissions exhibited only a marginal reduction of 1 %. These findings show that a suitable low-emission substitute fuel for VCR diesel engines is TiO₂ nano-additive-assisted hybrid biodiesel.
This study presents a semi-analytical model for transient magnetohydrodynamic (MHD) flow with electrokinetic coupling in cylindrical capillaries representing subsurface oil transport pathways. The model incorporates Lorentz force, electric double layer (EDL) effects, constant pressure gradient, and time-dependent momentum in the Navier–Stokes equations. Using the electrokinetic potential and magnetic field parameters, the governing equations are transformed into a Bessel-type form and solved through Laplace transform methods. Analytical expressions for velocity, shear stress, and flow rate are obtained in Laplace domain after which a numerical inversion method based on Riemann-Sum Approximation is used to describe the flow behavior under combined magneto-electrohydrodynamic effects in time domain. Parametric results show that stronger magnetic fields damp velocity oscillations, while higher electrokinetic coupling enhances near-wall fluid motion due to EDL-induced slip. The interaction between magnetic field and electroosmotic forces determines the time required for full flow development. The findings provide insight into microscale transport in oil–brine mixtures and indicate that electrokinetic effects significantly increase both velocity and mass flow rate.
The precise characterization of mechanical properties is essential to ensure the durability and safety of civil engineering infrastructures, particularly pavements. However, indirect tensile tests (IT-CY) on cylindrical specimens are sensitive to uncertainties related to non-uniform load distributions at the specimen–platen interface, which strongly influence the stress fields and the measurement of the stiffness modulus. This study employs finite element modeling (FEM) using the Abaqus software under the assumption of linear elastic behavior to analyze the impact of three load distribution profiles—uniform, sinusoidal, and parabolic—on the radial, tangential, and shear stress components in cylindrical specimens subjected to diametral compression, with a fixed contact angle of 15°. The simulations reveal significant variations: the uniform distribution generates high stress concentrations (up to 40 MPa in radial stress near the contact zones) and pronounced heterogeneity, thereby influencing the determination of the material’s stiffness modulus. In contrast, the sinusoidal and parabolic profiles promote a smoother stress transition, reducing peak stresses by up to 60% and concentrating the stresses along the vertical diameter. A comparative analysis with experimental results from previous studies supports these observations. Overall, the findings emphasize the critical role of contact conditions in minimizing experimental artifacts and reducing uncertainty in stiffness modulus evaluation. While based on a linear elastic framework, the results provide general mechanical insights that may contribute to the optimization of indirect tensile test protocols and the improvement of pavement design methodologies.
Robot manipulators are geometrically classified into parallel, serial, and hybrid configurations, with parallel manipulators demonstrating superior characteristics including enhanced payload-to-weight ratios, increased structural stiffness, and improved operational accuracy compared to their serial counterparts. This research investigates a three-degree-of-freedom translational parallel cube manipulator through comprehensive kinematic analysis. The study successfully resolves the inverse kinematics problem and derives the corresponding Jacobian matrix, establishing the mathematical foundation for performance evaluation. The condition number serves as a fundamental performance index for quantifying manipulator dexterity and assessing system sensitivity to geometric parameter variations, including link dimensions and moving platform radius, calculated as the ratio between the highest and lowest singular values of the Jacobian matrix. Condition number values are systematically computed across the entire workspace for various geometric parameter ratios, introducing the concept of "well-conditioned" workspace regions where the condition number remains within acceptable bounds. The percentage of well-conditioned workspace area is calculated to evaluate overall manipulator performance. A specialized Python implementation facilitates comprehensive manipulator analysis and computational processing. Results are presented through graphical visualization, demonstrating the relationship between design parameters and workspace performance characteristics, providing valuable insights for optimal manipulator design and operational planning
This study investigates the free vibration characteristics of orthotropic cantilever composite plate containing symmetric double edge cracks. A detailed finite element analysis (FEA) was conducted in ANSYS APDL to investigate the influence of crack length (a/W=0 0.04) and crack location (x_c/L=0-0.75) on the first six natural frequencies. The results show a consistent frequency reduction with increasing crack length and proximity to the clamped edge, while higher-order modes display greater sensitivity due to localized strain energy near the cracks. A semi-empirical relation was also developed to predict frequency degradation based on crack geometry and position, achieving excellent agreement with numerical data (R^2>0.99). The findings provide a concise framework for vibration-based damage detection and structural health monitoring (SHM) of orthotropic composite structures. Unlike previous works that primarily examined single-edge or isotropic configurations, this study uniquely quantifies the coupled influence of symmetric double-edge cracks in orthotropic cantilever plates, thereby extending the understanding of multi-crack interaction effects in composite dynamics.
The complex boundary layer (BL) featuring nanofluid phenomena involving multiple slip conditions, heat-mass transfer, magnetohydrodynamics (MHD), stretching ratio, heat generation, curvature, viscous dissipation, thermal radiation, mixed convection, and chemical reaction through a nonlinear stretching cylindrical surface is investigated by this research. The collection of nonlinear partial differential equations is transformed into ordinary differential equations using a suitable transformation. These resultant equations are resolved using a numerical approach, specifically the shooting method. The novelty of this work lies in the integrated analysis of nanofluid boundary layer flow over a nonlinear cylindrical surface, simultaneously incorporating MHD effects, multiple slip conditions, heat and mass transfer, thermal radiation, viscous dissipation, mixed convection, chemical reactions, and heat generation, while providing both numerical solutions and regression-based predictive insights. The velocity gradient increases by almost 58%, 56%, and 49% due to escalating magnetic field, power-law index, and velocity slip, respectively, whereas the Nusselt number increases by almost 39%, 78%, and 47% for escalating heat generation, velocity, and thermal slips, respectively. The significant contributing variables for the multiple regression equations of the skin friction, thermal, and material transport rates are calculated. The research findings may have implications for various engineering and industries such as MHD power generators, drug delivery systems, and boundary layer management in aerodynamics, which control and manage velocity-thermal-concentration fields.
Drilling is one of the most common machining operations, and its capabilities are utilized on lathes, drilling machines, conventional milling machines, as well as various CNC machines. This paper provides an overview of modern drill bit designs and current trends in their development. The study considers twist drills, three-flute drills, drills with index able inserts, step drills, solid carbide drills, and other types of drills widely used in industry. The rationale for this review is to systematize knowledge of existing solutions and to highlight the factors affecting drill performance, including material, design, and manufacturing precision. The review identifies dominant development trends, research gaps, and technological challenges that require further investigation. Special attention is given to drill bit geometry, cutting parameters, and design modifications aimed at improving tool life, machining efficiency, and hole quality, as well as reducing production costs.
This paper investigates the hybrid effect of Nanoparticles and liquid metal on MHD flow with slip boundary layer on Permeable arterial tube subjected to external electromagnetic fields and slip boundary conditions. Blood based carrier fluid with two different particles have been modelled and are used to describe a physiologically relevance of combined effect of nanofluid and MHD liquid metal. The governing equations, such as momentum, energy, and mass transfer, are derived through boundary layer approximations and similarity transformations, which reduce the system of PDEs to a set of nonlinear ODEs. The equations incorporate major physical effects such as viscous dissipation, Brownian motion, thermophoresis, and chemical reactions. MATLAB's shooting method in association with a Runge-Kutta solver is used to solve the resulting ODEs. The study examines the influence of various parameters including the Hartmann number, permeability factor, nanoparticle volume fraction, and slip coefficients on axial velocity, temperature, and concentration profiles. The findings show the enhancement of heat transfer and flow stability resulting from the incorporation of hybrid nanoparticles and extensive modification of velocity and temperature distributions by magnetic and slip effects. Such analysis provides valuable inputs to maximize the uses of blood-based nanofluid in biomedical engineering, drug delivery, and magnetic field-assisted therapies.
The steady laminar flow past a time-dependent radially stretching sheet within a hybrid nanofluid is studied. The governing equations are converted into ordinary differential equations utilizing the similarity transformations. Successive linearization is applied to linearize the nonlinear system of equations. The resultant system of equations is solved using the Chebyshev collocation method. Plots demonstrating velocity, temperature, Nusselt number, and skin friction coefficient for a few chosen parameters are shown. When volume fractions of Cu-containing nanoparticles rise, the critical values of these parameters fall, and when alumina (Al2O3) nanoparticle volume fractions rise, they increase. Compared with the nanofluid on the radially stretched surface, the hybrid nanofluid transfers heat faster. The addition of more alumina nanoparticles also lowers the Nusselt number and raises the skin friction coefficient. Furthermore, adding more copper (Cu) nanoparticles lowers the skin friction coefficient and the local Nusselt number on the stretching surface. This study is important because it demonstrates how hybrid nanofluids can be engineered to optimize heat transfer and flow resistance over stretching surfaces, providing valuable guidance for improving thermal performance in industrial and engineering applications.
This computational study examines a Williamson-micropolar nanofluid flow over a nonlinear stretching sheet subjected to a magnetic field. The Williamson fluid model, known for its ability to describe non-Newtonian shear-thinning behavior, is commonly applied in industrial polymers sheet extrusion. To highlight the influence of the involved parameters on the profiles an adequate mathematical model is formulated. Similarity transformations are used to convert the governing partial differential equations into a system of coupled nonlinear ordinary differential equations. The bvp4c solver of Matlab software is used to solve equations using the Lobatto III finite difference discretisation method with prior verification of the code developed. The impact of various physical parameters are explained and presented through graphs, tables and summarized in conclusion.The main result is that the relevant Williamson micropolar-nanofluid provides substantial improvement in thermal performance and reduced skin-friction can be gained. The values [M, K,
ABSTRACT: Both numerical and experimental investigations were conducted to study the thermal and flow behavior via natural convection between two vertical walls with a triangular heated cylinder and three staggered plates. The experimental setup featured two vertical adiabatic walls with an aspect ratio of A = 12. Air flowed in from the bottom and exited from the top, which was open to the atmosphere. A horizontally heated triangular cylinder, with a side length of 26 cm, was subjected to constant heat fluxes of 200 W/m², 400 W/m², and 800 W/m². The configurations tested included setups without staggered plates (h = 0.0 cm) and with plates of varying lengths (h = 0.5, 1.0, 1.5, and 2.0 cm) attached to the cavity walls. Numerical simulations were performed using ANSYS FLUENT 2020 to solve the governing equations. The results indicated that the Nusselt number increased with higher Rayleigh numbers, greater heat fluxes, smaller inclination angles, and larger lower surface opening distances. Additionally, incorporating fins of any geometry enhanced the rate of heat transfer. The optimal enhancement in the Nusselt number occurred with ribs, showing increases of 7%, 15%, 38%, and 42% for the cases of h = 0.0 cm, and h = 0.5, 1.0, 1.5, and 2.0 cm, respectively. The experimental data were compared with the numerical results, showing good agreement under identical conditions.
To address the use of nanorefrigerants of recognized environmental interest, this research focuses primarily on the impacts of thermal dispersion and inertia effect of porous medium. Combined with nanoparticles in natural convection of Casson base nanofluid flow on an embedded vertical plate, heat transfer is then examined. Using technical similarity, the ordinary differential equations resulting from the transformation of the partial differential equations are solved by the III Lobatto discretization of finite differences method through bvp4c @Matlab. The present numerical results are compared with previously obtained similar solutions and they are in good agreement. The significant influences of nanoparticles, thermal dispersion, shape factor, inertial effects of the porous medium, Casson and Eckert parameters on the natural convection flow are highlighted. Maximum values of the Nusselt number are obtained for a high values of γ, Rad, F0 and low values of the Brownian and thermophoretic diffusions of the nanorefrigerant. Dispersion should not be neglected because of its close connection with the nonlinearity effects induced by the structure of the porous medium. Working with strong inertials effects and permeability of porous medium is more attractive.The novelty of this paper is the extended coupling of diverse phenomena combinations with taking into account the thermal dispersion. Advanced cooling systems in microelectronics, compact heat exchangers, refrigeration and solar collectors are promising for applying the present findings.
Waterflooding represents one of the most extensively employed techniques for secondary oil recovery, where water is injected into reservoirs to displace oil toward production wells and enhance hydrocarbon recovery. However, a major challenge in waterflooding operations is salt precipitation, which results from the chemical incompatibility between the injected water, commonly enriched with divalent cations such as calcium, strontium, and barium, and the formation water, which generally exhibits elevated concentrations of sulfate ions. This chemical interaction leads to the formation of sulfate scales, significantly reducing reservoir permeability and hindering oil recovery efficiency. This study employed Gaussian Process Regression (GPR), a nonparametric, probabilistic machine learning method, to predict the extent of permeability damage resulting from sulfate scale deposition during waterflooding. A dataset of 431 experimental tests was used, incorporating input variables such as ion concentrations, differential pressure, temperature, pore volume, and initial permeability. The GPR model successfully captured the nonlinear relationships between these inputs and the resulting permeability damage. Both graphical and statistical evaluations demonstrated strong agreement between the model predictions and experimental results, with a high coefficient of determination (R² = 0.99) and low prediction errors (RMSE = 0.0839; MAE = 0.0529). The GPR model exhibited enhanced predictive accuracy relative to alternative machine learning algorithms, such as decision trees, support vector machines (SVMs), and artificial neural networks. Furthermore, the probabilistic framework of GPR facilitated the quantification of predictive uncertainty, thereby establishing it as a dependable and robust tool for informed operational decision-making in reservoirs susceptible to scaling.
This paper presents a detailed study of the interaction between conduction through a vertical fin and conjugate mixed convection of a nanofluid flowing in a porous medium. The fin model and the primitive partial differential equations governing the nanofluid with boundary conditions are transformed into dimensionless forms. For the nanofluid, fin, and fin-nanofluid interface equations, a second-level nonsimilarity transformation is obtained and solved by the bvp4c solver. A validation of the computational code is ensured by comparing the results to a conventional fluid. It was found that the fin temperature is strongly controllable by the geometrical parameters and thermal conductivity of the fin, while Brownian motion and thermophoresis have a moderate effect on it. In addition, low values of Nr and Ω favor the fin efficiency. An analysis on very different values of the Pr number reveals that the use of nanofluids with a suitable base fluid allows high fin dissipations. A more advantageous thermal design can be achieved by combining a nanofluid in a porous medium with a fin in specific applications. These main results provide valuable information on the necessary optimization of the fin efficiency.
