Search results

The purpose of this study is to adapt the incompressible smoothed particle hydrodynamics (ISPH) method with artificial intelligence to manage the physical problem of double diffusion inside a porous L-shaped cavity including two fins.

The ISPH method solves the nondimensional governing equations of a physical model. The ISPH simulations are attained at different Frank–Kamenetskii number, Darcy number, coupled Soret/Dufour numbers, coupled Cattaneo–Christov heat/mass fluxes, thermal radiation parameter and nanoparticle parameter. An artificial neural network (ANN) is developed using a total of 243 data sets. The data set is optimized as 171 of the data sets were used for training the model, 36 for validation and 36 for the testing phase. The network model was trained using the Levenberg–Marquardt training algorithm.

The resulting simulations show how thermal radiation declines the temperature distribution and changes the contour of a heat capacity ratio. The temperature distribution is improved, and the velocity field is decreased by 36.77% when the coupled heat Cattaneo–Christov heat/mass fluxes are increased from 0 to 0.8. The temperature distribution is supported, and the concentration distribution is declined by an increase in Soret–Dufour numbers. A rise in Soret–Dufour numbers corresponds to a decreasing velocity field. The Frank–Kamenetskii number is useful for enhancing the velocity field and temperature distribution. A reduction in Darcy number causes a high porous struggle, which reduces nanofluid velocity and improves temperature and concentration distribution. An increase in nanoparticle concentration causes a high fluid suspension viscosity, which reduces the suspension’s velocity. With the help of the ANN, the obtained model accurately predicts the values of the Nusselt and Sherwood numbers.

A novel integration between the ISPH method and the ANN is adapted to handle the heat and mass transfer within a new L-shaped geometry with fins in the presence of several physical effects.

Understanding and tailoring the solidification characteristics and microstructure evolution in as-built parts fabricated by laser powder bed fusion (LPBF) is crucial as they influence the final properties. Experimental approaches to address this issue are time and capital-intensive. This study aims to develop an efficient numerical modeling approach to develop the process–structure (P-S) linkage for LPBF-processed Inconel 718.

In this study, a numerical approach based on the finite element method and cellular automata was used to model the multilayer, multitrack LPBF build for predicting the solidification characteristics (thermal gradient G and solidification rate R) and the average grain size. Validations from published experimental studies were also carried out to ensure the reliability of the proposed numerical approach. Furthermore, microstructure simulations were used to develop P-S linkage by evaluating the effects of key LPBF process parameters on G × R, G/R and average grain size. A solidification or G-R map was also developed to comprehend the P-S linkage.

It was concluded from the developed G-R map that low laser power and high scan speed will result in a finer microstructure due to an increase in G × R, but due to a decrease in G/R, columnar characteristics are also reduced. Moreover, increasing the layer thickness and decreasing the hatch spacing lowers the G × R, raises the G/R and generates a coarse columnar microstructure.

The proposed numerical modeling approach was used to parametrically investigate the effect of LPBF parameters on the resulting microstructure. A G-R map was also developed that enables the tailoring of the as-built LPBF microstructure through solidification characteristics by tuning the process parameters.

This study aims to formulate a user-friendly pre-design model that could be a decision support tool for green wall systems to assist designers in selecting an optimal green wall system aligned with specified performance criteria while concurrently addressing project requirements linked to social and economic parameters. This approach seeks to enhance overall project satisfaction for the designer and the owner.

A correlation between the green wall context and design requirements and its performance on the buildings have been defined by considering its social and economic parameters, which represented the owner preferences to ensure the most satisfaction from installation as it achieves the required performance that is defined by the designer such as maximizing thermal insulation, improving indoor air quality, reducing the needed heating and cooling loads, etc. and also to achieve the satisfaction in social and economic requirements defined by the owner such as system installation cost, system maintenance cost, adding beauty value, etc.

The research developed an easy pre-design model to be a tool for green wall system decision-making for the most suitable system, which contains three main steps: the first one is defining the required performance of the green wall (designer requirements), the second step is limiting the context of the project which is made by designer and the owner requirements and finally the third step is choosing the system components that ensures achieving the requirements of both owners and designer, related to the building and climate context.

The added value lies in developing a green wall decision-making tool, essentially a pre-design model. This model considers the correlation between the project’s context, encompassing climate and building conditions. It provides a structured approach for decision-making in the early stages of green wall design. It offers valuable insights into the optimal choices related to system type, installation methods and plant characteristics. This enhanced decision-making tool contributes to more informed and efficient design processes, considering each project’s specific needs and conditions.

The purpose of this paper is to assess the feasibility of analytical models, specifically the radial basis function method, Akbari–Ganji method and Gaussian method, in conjunction with the finite element method. The aim is to examine the impact of processing parameters on temperature history.

Through analytical investigation and finite element simulation, this research examines the influence of processing parameters on temperature history. Simufact software with a thermomechanical approach was used for finite element simulation, while radial basis function, Akbari–Ganji and Gaussian methods were used for analytical modeling to solve the heat transfer differential equation.

The accuracy of both finite element and analytical methods was validated with about 90%. The findings revealed direct relationships between thermal conductivity (from 100 to 200), laser power (from 400 to 800 W), heat source depth (from 0.35 to 0.75) and power absorption coefficient (from 0.4 to 0.8). Increasing the values of these parameters led to higher temperature history. On the other hand, density (from 7,600 to 8,200), emission coefficient (from 0.5 to 0.7) and convective heat transfer (from 35 to 90) exhibited an inverse relationship with temperature history.

The application of analytical modeling, particularly the utilization of the Akbari–Ganji, radial basis functions and Gaussian methods, showcases an innovative approach to studying directed energy deposition. This analytical investigation offers an alternative to relying solely on experimental procedures, potentially saving time and resources in the optimization of DED processes.

This study is a targeted review of some of the major changes in European regulation that guided energy policy decisions in the Iberian Peninsula and how they may have aggravated the problem of lack of flexibility. This study aims to assess some of the proposed short-term solutions to address this issue considering the underlying root causes and suggests a different course of action, that in turn, could help alleviate future market strains.

The evolution of the most important (macro) energy and price-related variables in both Portugal and Spain is assessed using market and grid operator data. In addition, the authors present critical viewpoints on some of the most recent EU and national regulation changes (official document analysis).

The Iberian energy policy and regulatory agenda has successfully promoted a rapid adoption of renewables (main goal), although with insufficient diversification of generation technologies. The compulsory closings of thermal plants and an increased tax (mainly carbon) added pressure toward more environmentally friendly thermal power plants. However, inevitably, this curbed the bidding price competitiveness of these producers in an already challenging market framework. Moving forward, decisions must be based on “a bigger picture” that does not neglect system flexibility and security of supply and understands the specificities of the Iberian market and its generation portfolio.

This work provides an original account of unprecedented spikes in energy prices in 2021, specifically in the Iberian electricity market. This acute situation worries consumers, industry and governments. Underlining the instability of the market prices, for the first time, this study discusses how some of the most important regulatory changes, and their perception and absorption by involved parties, contributed to the current environment. In addition, this study stresses that if flexibility is overlooked, the overall purpose of having an affordable and reliable system is at risk.

The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal bearing (MHJB) system.

To simulate the behaviour of PVP lubricant in clearance space of the MHJB system, the modified form of Reynolds equation is numerically solved by using finite element method. Galerkin’s method is used to obtain the weak form of the governing equation. The system equation is solved by Gauss–Seidal iterative method to compute the unknown values of nodal oil film pressure. Subsequently, performance characteristics of bearing system are computed.

The simulated results reveal that the location of pressurised lubricant inlets significantly affects the oil film pressure distribution and may cause a significant effect on the characteristics of bearing system. Further, the use of PVP lubricant may significantly enhances the performance of the bearing system, namely.

The present work examines the influence of pocket orientation with respect to loading direction on the characteristics of PVP fluid lubricated MHJB system and provides vital information regarding the design of journal bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0241/

This study aims to focus on how reactive diluents with mono- and di-functionalities affect the properties of resin formulation developed from bioderived precursors. A hydroxyethyl methacrylate (HEMA) terminated urethane acrylate oligomer was synthesized and characterized to study its application in stereolithography 3D printing with different ratios of isobornyl acrylate and hexanediol diacrylate.

Polyester polyol was synthesized from suberic acid and butanediol. Additionally, isophorone diisocyanate, polyester polyol and HEMA were used to create urethane acrylate oligomer. Fourier transform infrared spectroscopy and ¹H NMR were used to characterize the polyester polyol and oligomer. Various formulations were created by combining oligomer with reactive diluents in concentrations ranging from 0% to 30% by weight and curing with ultraviolet (UV) radiation. The cured coatings and 3D printed specimens were then evaluated for their properties.

The findings revealed an improvement in thermal stability, contact angle value, tensile strength and surface properties of the product which indicated its suitability for use as a 3D printing material.

This study discusses how oligomers that have been cured by UV radiation with mono- and difunctional reactive diluents give excellent coating characteristics and demonstrate suitability and stability for 3D printing applications.

This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.

Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.

The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.

An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.