Department of Chemical Engineering

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Polymer-based composites have been widely used in the enhanced tribological technologies of various automobile, aerospace industry, sports, etc. The epoxy-based polymer composites reinforced with glass fiber have significantly improved the wear inhibitors and ultimate strength along with ultra-low density than other available materials. This current research aims to fabricate a variation of such non-woven viscose-based polymer composites for various weight fractions (100–400 GSM) with a constant fiber loading of 30 wt% and subsequently analyze its physical, mechanical, and tribological properties under various operating parameters. The density of the fabricated composite exhibits an increase of magnitude with an increase in weight fraction. The composites consist of 400 GSM fabric showing a higher tensile, impact, flexural strength, hardness, and inter lamina shear strength (ILSS). A pin-on-disc wear set-up held dry sliding wear tests of various nonwoven viscose fabric-based composites under various operating parameters like sliding velocity, sliding distance, area density, and normal load. A Taguchi-based L16 orthogonal array design was utilized to estimate the optimal behavior for maximum wear resistance for operating conditions. The result reveals that the normal load over the composite contributes the highest towards wear on a composite compared to area density, sliding velocity, and distance. The wear phenomena have been verified with SEM micrographs to characterize various wear phenomena like fiber rapture, ploughing, micro-cracks, and wear lines. © IMechE 2021.

World University root node

Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology

Physical, mechanical and dry sliding wear properties of non-woven viscose fabric epoxy-based polymer composites: An optimization study

In this paper, a data-driven smart optimization algorithm is presented to identify the optimal operating point of the process and the path from the current operating condition to the optimal operating condition. To model the plant dynamics, a locally weighted semi-supervised probabilistic principal component regression (PPCR) model that is robust to missing data and can handle the time-invariant delay is developed in this paper. Being a locally weighted linear model, a nonlinearity index is utilized to control the accuracy of approximation of the local model. In addition, an updating strategy on the delay range is proposed to reduce the computational effort of real-time modeling. To account for the model–plant mismatch, a penalty term in the form of a robust Gaussian process regression is incorporated into the optimization problem. Finally, to ensure that the algorithm reaches different regions of search space and avoid convergence to local optimum, an exploration step with the aid of acquisition functions is utilized. The performance of the developed approach is illustrated through an experimental case study on a hybrid tank system, and the practical applicability of the algorithm is demonstrated through an industrial example. © 2023 Elsevier B.V.

Chemometrics and Intelligent Laboratory Systems

Smart optimization with PPCR modeling in the presence of missing data, time delay and model-plant mismatch

Over the years, incredible evolution has been framed in developing particle-induced discrete simulation techniques over conventional continuum approaches. In particular, the lattice Boltzmann method (LBM) originated from a flexible and robust computational tool for scientific research and various practical applications. LBM is based on a mesoscopic approach that acts as a bridge between the microscale and macroscale, offering distinct features in the accuracy of simulations and numerical efficiency. LBM has been successfully employed over a broad aspect of disciplines, encompassing biomedicine, geothermal energy, flow physics, materials, chemistry, medical treatment, storage of energy, and several engineering disciplines. Meanwhile, phase change materials (PCMs) are extensively utilized in thermal energy storage (TES) systems as they can absorb and release heat throughout the phase change process. Moreover, phase change heat transfer (HT) has a substantial occurrence in industrial and domestic activities. It is expected to enhance the thermal transport rate between HT fluid and PCMs for the confinement of a larger amount of heat. This current work aims to provide a comprehensive review of LBM for thermo-fluids concentrating on thermal flows and PCM. It also enlightens a brief insight into the LBM formulation of heat transfer for PCMs under various external force conditions and the implementation of boundary conditions for PCMs. In addition, it also introduces the study and examination of the existing TES systems comprising PCMs for various applications. © 2023, Akadémiai Kiadó, Budapest, Hungary.

Journal of Thermal Analysis and Calorimetry

Lattice Boltzmann method for heat transfer in phase change materials: a review

In this research study, orange peel-based biocatalysts developed from different acid protonation were used as a metal-free catalyst for hydrogen production from sodium borohydride (NaBH4). In order to prepare the orange peel-based biocatalyst with higher catalytic activity, experiments were conducted with pure orange peel, different acid molar concentrations, and calcination temperatures. The physical morphology, surface texture, and chemical interaction were thoroughly analyzed by XRD, FTIR Raman, FESEM, BET, and TGA. As a result of the experiment, it was determined that the highly acid-treated biocatalyst (40% H3PO4, 40% H2SO4, 40% HCl) and calcinated at 450 °C for 1 h had higher catalytic activity. As a result, bio-hydrogen production at 35 °C and 70 °C methanolysis with 3% NaBH4 catalyzed by a mixture of acid-treated catalysts were found as 46,213 and 63,842 ml min−1g.cat−1, respectively. However, with the increase of molar concentration of biocatalyst with 40% individual acid prolonged samples, the HGR rates will not have a satisfactory value in comparison with the 40% mixture of the acid-treated catalyst due to less number of active sites. © 2023 Hydrogen Energy Publications LLC

International Journal of Hydrogen Energy

Synthesis of novel biocatalyst from organic waste protonated with acid treatment for hydrogen production

A cost-effective and facile synthesis method is developed for hybrid aerogels using recycled cellulose fiber concentration of 1-4 wt.% and methoxytrimethylsilane (MTMS). The developed hybrid aerogel was modified with surface hydroxyl groups to achieve superhydrophobic behavior with a contact angle as high as 163.4°. This excellent three-dimensional reticular structure with various cellulose concentrations provides a thermal conductivity of 0.039-0.041 W m-1 K-1. However, the thermal degradation of the hybrid aerogels exhibits a superior improvement with minimum weight loss. A comparatively good sound absorption coefficient of 0.392-0.504 was achieved with the inclusion of cellulose fiber concentration from 1 to 4 wt.% in comparison with silica aerogels (0.303-0.512). The experimental results also show an increase in compressive Young's modulus of hybrid aerogels up to 96%, with an increase in cellulose concentration. This work delivers a facile approach to developing hybrid aerogels with an industrial application to replace polymer-based insulations. © 2023 Walter de Gruyter GmbH, Berlin/Boston.

International Journal of Materials Research

Development of superhydrophobic hybrid silica-cellulose aerogel as promising thermal insulation and sound absorption

This work reports the synthesis and characterization of hybrid nanoparticles-based phase change material (HNbPCM) along with a practical approach in the pin-fin heat sink system. In particular, the hybrids of Nickel cobaltite (NiCO4O4) - Nickel ferrite (NiFe2O4) nanoparticles (NiCo−NiFe) were synthesized by traditional sol–gel method. The (HNbPCM) composites were then prepared by suspending the nanoparticles in paraffin wax (PW) and polyethylene glycol-6000 (PEG−6000) eutectic organic PCMs with various weight fractions (ϕ=1%–5%). The surface texture, physical and chemical interaction of hybrid nanoparticles and its dispersion in the HNbPCM composites were comprehensively analyzed. The cyclic thermal stability, thermal conductivity, and charging and discharging of characteristics of the developed nano-composites were also confirmed by transient hot-wire apparatus, thermo-gravimetric analysis (TGA), differential scanning calorimetry (DSC). A nanoparticles concentration of 3wt% in the HNbPCM shows a promising enhancement in the thermophysical properties. The thermal conductivity of HNbPCM was improved by 304.4% by adding hybrid NiCo-NiFe nanoparticles with ϕ=5%. In addition to thermal conductivity augmentation, nanoparticles enriched HNbPCM altered the phase transition process and eliminated super-cooling by maintaining the high latent heat capacity of 188.95J/g in the melting phase and 189.70J/g in crystallization phase. A systematic experimental framework of thermal performance characteristics for HNbPCM composite in rectangular pin-fin heat sink subjected to steady state heat transfer for effective and reliable cooling was also studied. The cooling of heat sinks was under testimony at different power inputs, volume fractions and modes of heat transfer in two distinct case studies with and without PCM. A volume fraction of 3wt% shown the best thermal performance with a heat transfer enhancement up to 3.2kW/m2 with 18°C temperature reduction in operational time, specific heat capacity, and thermal conducting ability. An improved thermal performance shows considerable thermal and chemical stability, which can expedite the transition process and makes it a desirable prospect for superior thermal energy storage (TES) applications. © 2023 Elsevier Ltd

Journal of Energy Storage

Hybrid NiFe2O4-NiCO4O4 nanoparticles-based eutectic phase change materials for enhancement of thermal efficiency of pin-fin heat sink arrangement

A two-dimensional, steady-state, laminar, double-diffusive convection within the rectangular cavity containing heated rectangular blockage at its geometric center has been explored by the lattice Boltzmann method. The research work is focused on determining the combined influence created by a magnetic force and double-diffusive convective characteristics in the shallow cavity (length > height) and rectangular blockage (width > height). In particular, the influence of various pertinent parameters, such as the aspect ratio of the cavity (AR = 1, 2, and 4), the aspect ratio of the heated blockage (ar = 1, 2, and 4), Lewis number (Le = 2, 5, and 10), Prandtl number (Pr) = 0.054, Rayleigh number (Ra = 103, 104, and 105), Hartmann number (Ha = 0, 50, and 100), and the buoyancy ratios (N = -2, 0, and 2), on the double-diffusive convection accompanied by magnetohydrodynamics characteristics has been elaborated. The working fluid in the cavity is considered to be a liquid metal-sodium-potassium alloy (Pr = 0.054). The results indicated the augmentation in Le leads to the formation of multi-cell zones within the cavity. For N < 0, the direction of fluid flow, thermal, and concentration patterns is reversed as for N > 0. Denser crowding of temperature and concentration contour lines along the block was noticed for N = 2 than N = -2 for a given Ra. The total Nusselt (Nutotal) and Sherwood number (Shtotal) decreases with a decrease in N. The heat and mass transfer rates enhance with augmentation in both cavity and blockage aspect ratios. © 2022 Author(s).

Physics of Fluids

Double-diffusive convection in a rectangular cavity subjected to an external magnetic field with heated rectangular blockage insertion for liquid sodium-potassium alloy

The influence of triangular surface corrugations on the mixed convection characteristics in a tall lid-driven cavity for non-Newtonian power-law fluids is reported. In particular, numerical experimentations are executed for a range of parameters, such as aspect ratio of cavity, number of triangular corrugations, Richardson numbers, Prandtl numbers (Pr), power-law indexes, and at a constant Grashof number. The corrugation number seems to be the maximum impact for higher Prandtl number fluids. For taller cavities, higher Nusselt number values were obtained for Pr = 100. Triangular corrugations showed a modest change in the heat transfer augmentation in most of the considered parameters. © 2022 Wiley-VCH GmbH.

Chemical Engineering and Technology

Mixed Convection in a Lid-Driven Cavity with Triangular Corrugations and Built-in Triangular Block

In this work, the effect of four different precipitating agents on the structural and magnetic properties of synthesized ferromagnetic nanoparticles (FMNPs) by the co-precipitation method has been explored. In particular, different precipitating agents used in work include (I) NH3, (II) NH3 with alcohol, (III) NaOH, and (IV) aqueous NH3 solution. The synthesized nanoparticles were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), scanning electron microscope (FESEM/EDS), zeta-potential, and vibrating sample magnetometer (VSM). From the XRD pattern and Debye-equation, it appears that the obtained nanoparticles were magnetite with an average crystallite size of 8–27.6 nm. The FTIR spectrum of NH3 in an alcohol solution indicates a perfect stretching of the Fe–O, O–H, C–H functional groups compared to other cases. Moreover, superparamagnetic behavior at room temperature was also noticed from VSM analysis. NH3 in an alcohol solution as a precipitating agent showed higher magnetic properties of FMNPs than the other cases. Conversely, the response time was found to be the longest for the same set. The procedure with NaOH in an aqueous solution was the cheapest with a shorter reaction time. Nevertheless, the particle surface and magnetic characteristics were lesser than the other cases of precipitating agents. © 2022 Elsevier B.V.

Powder Technology

Effect of precipitating agents on the magnetic and structural properties of the synthesized ferrimagnetic nanoparticles by co-precipitation method

The main objective of this paper is to develop a soft sensor for predictions of the residue element concentrations of feed mixture in a KIVCET furnace, since such measurements are not available online and are crucial in achieving the objective of real-time optimization. To realize this, a wavelet neural network is considered owing to its high accuracy in approximating functions with a few functional components over networks with sigmoid/tanh activation functions. The idea of wavelet decompositions is used to address the challenges associated with random initialization in such networks. A one-norm penalty on the data-fit term is considered to make the approach robust to outliers, and a sparsity constraint on the parameter vector in terms of zero-norm is considered to handle the issues of over-fitting and input redundancy. The efficiency of the proposed method is demonstrated through an industrial KIVCET unit and a simulation study. © 2022