The impulse injection Residence Time Distribution (RTD) method uses sensors at the inlet and outlet of the industrial-scale pulp digester to measure values that are recorded on the Data Acquisition System (DAS). The data collected on DAS is imperfect due to random measurement errors, sampling intervals, and premature termination of the tracer test. Manual pre-processing of DAS data requires replacing missing and null values, alphanumeric values, special characters, etc. After these corrections, the hydrodynamics by fitting RTD models such as the Axial Dispersion Model (ADM) and the Tank-in-Series with Back-Mixing Model (TIBM) are assessed. The repeated correction on DAS data is labor-intensive, tedious, and prone to errors and generates inaccurate results. The proposed work uses Machine Learning (ML) to eliminate these errors and optimize data. The DAS data is treated for background, radioactive decay, starting point, and tail correction, and E(t) curves are generated for RTD analysis. The work therefore evaluates the predictive ability of different machine learning models in estimating the degree of fit between the traditional computational ADM and TIBM model with the ML-predicted model. Researchers utilize Linear Regression (LR), Random Forest (RF), K-Nearest Neighbors (KNN), Generalized Additive Model (GAM), Decision Tree (DT), XGBoost, LightGBM, and AdaBoost to develop ML predictive models. The present findings show a thorough comparison of different ML strategies for forecasting the degree of agreement between experimental models and ML models. The evaluation metrics were obtained using R-squared scores for comparison. The RF followed by XGBoost ML models outperformed the other selected algorithms. Thus, the presented work demonstrates the effectiveness of ML in predictive modelling for RTD data.

The jet impinging slot is frequently adopted to efficiently and instantly dissipate the large quantity of heat to cool the sophisticated engineering devices for improving their performance, such as anti-icing of aircraft wings, micro-processor/controllers, heat exchangers, etc. The present work aims to examine the proposed impinging slot jet configuration to improve heat transfer. The study focuses the convective flow of heat dynamics by a porous jet impingement slot to Casson fluid. The temperature lag within the fluid layer and solid structure of porous medium is accomplished by the local thermal non-equilibrium (LTNE) model for the parameter's range as Casson parameter ($0.1 \leq \beta \leq \ 5$0.1 <=beta <= 5), Peclet number ($1 \leq Pe \leq \ 1000$1 <= Pe <= 1000), Darcy number ($10<^>{-6} \leq Da \leq \ 10<^>{-2}$10-6 <= Da <= 10-2), Rayleigh number ($1 \leq Ra \leq \ 300$1 <= Ra <= 300), porosity ($\epsilon = 0.7\comma\; 0.98$& varepsilon;=0.7,0.98). The Brinkman-Forchheimer-extended Darcy fluid flow model was employed to address the porous media, and the finite element technique (FEM) was used to achieve the numerical solution of the governing equations. The findings are displayed in the form of streamline and isotherm profiles, as well as the total local and average Nusselt number and LTNE parameter. The highest value of the overall average Nusselt number is achieved when $\epsilon = 0.7\comma\; Pe = 1000\comma\; Da = 10<^>{-2}\comma\; \beta =5$& varepsilon;=0.7,Pe=1000,Da=10-2,beta=5.

The nanoscience and nanotechnology is playing vital role in each and every interdisciplinary fields. The products made by nanomaterials are trending nowadays. There are huge applications of nanomaterials in agricultural, pharmaceutical, chemical, cosmetics, petrochemical, automobile, etc. including all other allied industries. In the same sequence, the nanocomposites are the multiphase solid material, which represents many interdisciplinary applications. Therefore, it is important to understand the scientific and technical aspects of nanocomposites. Hence, we have chosen a carbon nanotube (CNT), which belongs to the same family of nanocomposites for our study. It is frequently used in many significant industrial applications including wastewater treatments. In this study, we have performed a thermodynamic analysis on multi-walled carbon nanotubes (MWCNTs) as it is more durable and efficient in comparison to single-walled carbon nanotubes (SWCNTs). We have used molecular simulation techniques in combination of “Muller-Plathe” method followed by LAMMPS open-source software. Based on the generated data (i.e., thermal conductivity) for differently oriented and structured MWCNTs [i.e., Chirality (5, 5), Chirality (10, 10), and Chirality (19, 10)] we have performed a significant analysis and found that the thermal conductivity increases while increasing the length of MWCNTs for each orientation. These are interesting results and we are able to confirm that the MWCNTs with high thermal conductivity are more efficient and durable for multiple applications. Also, the changes (i.e., increments) in thermal conductivity are irrespective of chirality. This is an interesting finding and may be helpful to design and construct the qualitative MWCNTs for desirable purpose.

This study investigated the momentum and thermal characteristics of a blunt‐headed cylinder immersed in a stream of generalized Newtonian fluids (i.e., power‐law fluids) under various planar confinements. The flow and heat transfer characteristics were obtained by solving the constitutive equations with a finite‐element‐based solver for varying ranges of governing parameters. Reynolds number ( Re = 1–40), Prandtl number ( Pr = 5–100), power‐law index ( n = 0.3–1.8), and blockage ratios ( β = 2–40) were considered as the governing parameters for the study. Streamlines, drag coefficients, isotherm contours, and average Nusselt numbers were obtained as output parameters of the study. The local distribution of the pressure coefficient and Nusselt number are also presented to gain deep insight into the vicinity of the blunt‐headed cylinder. Shear‐thickening and shear‐thinning fluids exhibited an inverse trend for flow separation under planar confinements. The average Nusselt number exhibits a positive correlation with the Reynolds and Prandtl numbers while showing negative dependence on the power‐law index and blockage ratio. Overall, momentum and heat transfer show complex relationships with the governing parameters. The functional relationships are shown as correlations for flow‐separation Reynolds number, total drag force, and average Nusselt number on relevant dimensionless parameters for general applications.

The current paper deals with viscous dissipation effects in a permeable (or porous) channel filled with non‐Newtonian Casson fluid by considering the local thermal non‐equilibrium (LTNE) model. The dependency of the effective thermal conductivities of the solid and fluid phases on the respective temperatures has been studied along with the spatially varying Biot number. The Brinkman number Casson fluid parameter , thermal conductivity variation parameter , porosity Darcy number , and the ratio of fluid and solid phase thermal conductivities are the main governing parameters. The Darcy–Brinkman model is employed to govern the fluid flow in permeable media and the velocity profile has been obtained analytically. Moreover, the energy equations for both phases along with suitable boundary conditions are derived and solved with the fourth order boundary value solver. The findings of the current study depict that the Nusselt number increases with the increment in Casson fluid parameter and decreases with the increment in Brinkman number and thermal conductivity variation parameter. Overall, the heat transmission between the solid and fluid phases increases with the decrement in Brinkman number and thermal conductivity variation parameter. On the other hand, the heat transmission between both the phases magnifies by increasing the value of Casson fluid parameter.

Coating, paint, thin film, and functional coatings research institutes, organizations, societies, associations, and centers play a vital role in advancing surface coatings and exploring functional coatings' development, application, and utilization. These entities are dedicated to conducting research, development, and innovation while fostering collaboration to enhance coatings' performance, functionality, and application across various industries. These research investigate different aspects of coating technology, including materials, formulation, deposition methods, surface modification, characterization, and performance evaluation. Their efforts aim to improve the properties and functionalities of coatings, such as corrosion resistance, wear resistance, self-cleaning properties, antimicrobial properties, optical properties, electrical conductivity, thermal stability, and adhesion. By conducting cutting-edge research and development, these entities contribute to creating advanced coating technologies, such as nanocoatings, biocompatible coatings, energy-efficient coatings, smart coatings, and functionalized coatings for specific applications. They work closely with industry partners, academia, and other stakeholders to translate research findings into practical solutions and promote technology transfer. Collaboration and knowledge exchange are fundamental to the work of these entities. They organize conferences, symposiums, workshops, and technical seminars, serving as platforms for researchers, scientists, engineers, industry professionals, and end-users to share insights, explore emerging trends, discuss challenges, and foster collaborations that drive innovation in the field of coatingsactively contribute to standardization and quality control efforts by participating in the development of industry standards, certifications, and regulatory frameworks. They collaborate closely with regulatory bodies, governmental agencies, and industry associations to ensure coating application compliance, safety, and sustainability. Through their activities, coating, paint, thin film, and functional coatings, research significantly contribute to diverse industries such as automotive, aerospace, electronics, energy, healthcare, and consumer products. Their work leads to the development of coatings that protect substrates, enhance performance, improve esthetics, enable new functionalities, and address emerging challenges in the ever-evolving coatings landscape. This comprehensive worldwide list presented in this chapter serves as a valuable resource for researchers, professionals, academicians, and students worldwide, facilitating global connectivity and providing a foundation for collaboration and knowledge exchange in the field.

The tetrahedral materials represents a structure of polyhedron which usually having four triangular faces. The most applicable tetrahedral materials are listed as silicon, water, germanium, carbon, and tin in periodic table (Group-14). All these tetrahedral materials shows very interesting features specifically close to the transition temperature or in super-cooled region. However the water is the most common tetrahedral material which shows density and heat capacity anomalies in super-cooled region. Hence it’s an opportunity and challenge to understand the scientific aspects of this tetrahedral material (i.e. water) in super-cooled region where the transformation from one phase to other phase is quite rapid as compare to the melting point of water. Since the system size plays a significant role to define the scientific aspects of any thermodynamic system. Therefore, we have focused our study on different system sizes with 1000, 4096, 8000, 46656, and 125,000 particles respectively for water by using empirical monatomic potential model followed by Isothermal-Isobaric (NPT) Molecular Dynamic (MD) simulation technique. This study shows the comparison analysis based on the thermodynamic changes in terms of density, potential energy, enthalpy, etc. for water close to the transition temperature. The results predicted over this study are significant and consistent with the literature. The entire comparative analysis represents in this study would be useful to understand the system size effects on thermodynamic behavior of the tetrahedral materials (i.e. water) which can further be extended to other tetrahedral as well as complex materials in the same sequence.

The combined implementation of porous medium and hybrid nanofluid with heaters and coolers can be an effective technique to improve the efficiency of several types of electric equipment. In this regard, the present study has been conducted to analyze the forced convection heat transfer of Al2O3-CuO water-based hybrid nanofluid in porous channel with pairs of heaters and coolers of various shapes. The circular and semi-circular heaters and coolers with distinct orientations are considered. The Peclet number (25 <= Pe <= 200), Darcy number (10(-6) <= Da <= 10(-1)), porosity (0.1 <= epsilon <= 0.9), and volume fraction of hybrid nanoparticles (0.02 <= phi <= 0.08) are chosen as the governing parameters. The governing equations are solved by using the finite element method based commercial software COMSOL Multiphysics. The acquired results exhibit that the heat transfer from heaters and coolers is enhanced by decreasing epsilon and Da for all the cases and values of Pe and phi. The lowest heat transfer has been obtained by circular heaters and coolers (case 1). Moreover, the semi-circular heaters and coolers with curved facing towards channel inlet (case 2) and flat surface towards the bottom channel wall (case 4) show higher heat transfer compared to other cases. The average Nusselt number for case 4 is around 3.63% higher from case 2 at the highest values of the considered parameters. Case 4 shows the minimum drag coefficient and maximum heat transfer at the highest values of the governing parameters.

Semi -circular cylinders provide better space economy than circular and other non -circular cylinders. The cylinders are frequently used in a tandem arrangement in heat transfer equipment. The present study aims to obtain the flow and heat transfer characteristics for the tandem arrangement of semi -circular cylinders. The cylinders are placed in a vertical channel with a blockage (beta) of 0.2. The upward flow under the reverse gravity is considered here. The influence of various parameters such as Reynolds number (Re), Prandtl number (Pr), Richardson number (Ri), and spacing between cylinders (YC) is observed. The governing parameters are varied in a range of 1 <= YC <= 6, 1 <= Re <= 50, 0.7 <= Pr <= 50, and 0 <= Ri <= 2. The numerical results are obtained by solving governing equations using FVM (Finite volume method). The velocity field, thermal field, drag coefficient (CD), pressure coefficient (Cp), and average Nusselt number (Nuavg) are presented. The increase in Re and Pr has enhanced the Nuavg and CD, whereas Ri and YC have shown complex dependency. The obtained results show that the mutual interaction of upstream and downstream cylinders has vanished for YC > 4. The upstream and downstream cylinders have shown different behavior at identical operating conditions. The drag coefficient for the upstream cylinder varies with YC for 1 <= Re <= 10, whereas for 10 <= Re <= 50, it shows negligible change except for the case of Pr = 0.7 and Ri = 2. The drag on the downstream cylinder increases monotonically with an increase in YC. The average Nusselt number for both cylinders increased with an increase in YC except for the downstream cylinder at Re = 1 and Pr = 0.7. Overall, the complex interplay of governing parameters has been observed in the flow and thermal characteristics.

Polymer Composite material is made of two or more constituent materials that, when combined, produce a material with properties that are distinct from those of the individual constituents. The fabrication of polymer nanocomposites especially lignin-based nanocomposites are growing prospective research interest, thanks to various advancements made possible by the combination of a polymeric matrix with, in most cases, an inorganic nonmaterial. The advancement and modification of lignin-based nanocomposites is a step towards the replacement of conventional plastics (traditional polymer). Polymer composites have been produced or formed specifically for a variety of applications that are employed in a specific location for a specific purpose. Lignin is a highly heterogeneous polymer that is found naturally in plants that account for up to 15–35% of woody biomass made up of several precursors. Lignols that crosslink in a variety of ways with antioxidant property, high thermal stability, biodegradability, and UV absorption characteristics. Despite the fact that lignin is the most prevalent phenolic component in nature, and a small percentage of lignin removed by industrial processing which gets turned into dispersants and fillers has the potential to enhance various properties like mechanical, thermal, thermo-chemical, anticorrosive, flame retardant and many more of the polymer composite which is beneficial for our society as well our environment.

The thermal conductivity of the porous materials is dependent on the temperature in a range of applications, including nuclear reactors and fossil fuel sources. The LTNE (local thermal nonequilibrium) model is widely used to study the thermal interactions between solid and fluid phases inside the porous media. The majority of the prior LTNE models assumed the constant thermal conductivities of both the fluid and solid phases, but in actual practice, the thermal conductivities depend on the temperature variations. In the current study, the effective thermal conductivities of the fluid and solid phases in the porous channel are considered as the functions of the respective temperatures by implementing the LTNE model. The Biot number is assumed to vary linearly, quadratically and sinusoidally along with the channel height. The thermal conductivity variation parameter [Formula: see text], porosity [Formula: see text] the ratio of fluid and solid phase thermal conductivities [Formula: see text] and heat generation parameter [Formula: see text] are considered as the main operating parameters. A system of ordinary differential equations has been derived and solved numerically under the above-mentioned conditions which is the generalization of the constant thermal conductivities of both the phases. The present results are validated with the already published results for the constant thermal conductivity and variable Biot number with the LTNE model. The obtained results show that the maximum heat transfer between the two phases is observed by taking [Formula: see text] as the linear increasing function of [Formula: see text] i.e., [Formula: see text] and correspondingly, it provides the highest values of Nusselt number. The Nusselt number increases with the decrement in thermal conductivity variation parameter [Formula: see text], heat generation parameter [Formula: see text] and ratio of fluid to solid phase conductivities [Formula: see text] A complex relationship has been observed between the porosity and the Nusselt number.