Universitas Islam Negeri Sultan Syarif Kasim Riau

This study examines the Falkner–Skan boundary layer flow over a moving wedge containing a mixture of nano-encapsulated phase change material (NEPCM) nanofluids. As the NEPCM particles are transported by the base fluid, they encounter temperature gradients within the boundary layer. This causes them to undergo melting and solidification processes associated with latent heat absorption and release. The governing partial differential equations are transformed into a system of coupled nonlinear ordinary differential equations using similarity transformations and solved numerically via the shooting technique combined with the Runge–Kutta method. The analysis explores the effects of the wedge motion parameter ( -0.5 ≤λ≤ 1.2 ), the wedge angle parameter ( 0.05 ≤ m ≤ 0.5 ), the NEPCM volume fraction ( 0.0 ≤ϕ≤ 0.05 ), the Stefan number ( 0.2 ≤ Ste ≤ 0.8 ), and the dimensionless fusion temperature ( 0.03 ≤ T_f ≤ 0.3 ). Increasing the NEPCM concentration was found to broaden and elevate the phase transition region, thereby enhancing both the local Nu and skin friction coefficient. This enhancement in thermal and momentum transport is particularly significant near the critical value of the wedge velocity parameter.

Purpose Optimizing thermal management in systems with multiple heat sources, such as in electronics cooling, requires innovative coolants. Nano-encapsulated phase change materials (NEPCMs) offer superior thermal energy storage via latent heat, but their interaction with complex flow fields from multi-cylinder arrays is not well understood. This study aims to analyze natural convection and melting of NEPCM nanofluid within a square enclosure containing multiple hot cylinders. Design/methodology/approach The non-dimensional governing equations are solved using a finite element method. A parametric study evaluates the effects of cylinder number (N), spacing (S), NEPCM concentration (ϕ), fusion temperature (Θf) and Rayleigh number (Ra). Findings The results show that the optimal system configuration is regime-dependent. At low Ra, four cylinders with larger spacing perform best. At high Ra, flow congestion and thermal wake effects cause this configuration to become the worst, with a two-cylinder system proving most efficient. NEPCM concentration is the most significant performance driver, increasing the average Nusselt number by 137%–190% as ϕ rises from 0.01 to 0.05, depending on spacing. A higher fusion temperature further enhances performance at high Ra. Research limitations/implications This study is limited to the 2D configuration and stationary flow condition. Practical implications This work demonstrates that synergistic design of the enclosure geometry and NEPCM properties is crucial. The findings provide essential guidelines for developing high-performance thermal management systems. Originality/value While existing literature has extensively studied natural convection with multiple cylinders or with NEPCMs separately, the interplay between complex multi-cylinder geometries and the dynamic phase change behavior of NEPCM suspensions remains unexplored. This study bridges this gap by systematically investigating the coupled effects of parameter on the flow structure, melting dynamics, thermal performance and entropy generation. The primary novelty lies in understanding how the latent heat of NEPCMs modulates and is modulated by the complex flow fields generated by interacting multiple heat sources.

PurposeThis study aims to explore the thermal convection characteristics of nano-encapsulated phase change materials (NEPCMs) suspended in non-Newtonian nanofluids within a rotating enclosure, addressing a critical gap in the understanding of heat transfer and flow behavior in such complex systems.Design/methodology/approachThe finite element method is used to solve the dimensionless governing equations for continuity, momentum and energy, providing insights into the effects of power-law indices, nanoparticle concentrations and rotational speeds on flow dynamics, thermal transport and phase change processes.FindingsThe findings highlight that the interplay between non-Newtonian rheology and NEPCM concentration significantly influences natural convection, particularly near the cold wall. Pseudoplastic nanofluids exhibit greater sensitivity to rotational forces than dilatant fluids, where shear-thinning behavior enhances circulation and heat dissipation. Among the examined fluid types, Newtonian nanofluids demonstrate the highest heat transfer efficiency, achieving a 42% enhancement as nanoparticle concentration increases from 0.01 to 0.04.Originality/valueThis study uniquely investigates NEPCM nanofluids suspended in non-Newtonian fluids within a rotating enclosure, a combination not previously explored in detail. By analyzing the coupled effects of power-law rheology, rotation and phase change, the work provides new insights into thermal transport mechanisms relevant to advanced energy storage and cooling systems.

This study aims to examine public perceptions of Integrated Islamic Schools through aspect-based sentiment analysis by integrating Latent Dirichlet Allocation, Lexicon-Based approach, and Deep Neural Networks. LDA is employed to extract topic structures that represent the semantic context of public reviews, Lexicon Based method is used for sentiment analysis, while DNN infers sentiment orientation based on the extracted representations. This approach seeks to combine the strengths of probabilistic topic modeling and deep learning to obtain a more comprehensive understanding of public opinion. The analysis was conducted on a collection of 2,280 online reviews, which after preprocessing resulted in 1,438 reviews processed using the LDA–DNN combination. The results demonstrate that this approach is capable of identify in opinion dimensions in a more contextual manner and enhancing the interpretability of the analysis outcomes. Empirical evaluation shows that the proposed model achieved an accuracy of 63.89% for aspect classification and 93.06% for sentiment classification, outperforming the K-Means–LSA and K-Means–PCA approaches, which achieved 45.14% and 31.94% accuracy for aspect classification and 92.36% accuracy for sentiment classification, respectively. These findings confirm the superiority of probabilistic topic modeling in capturing complex semantic relationships and provide a methodological contribution to the development of sentiment analysis in the context of integrated Islamic education.

Qur’anic manuscripts preserve material evidence of copying practices and reading traditions. This article analyses Qur’anic manuscript 07.15/2017 in the Sang Nila Utama Museum, Riau, which records the qirāʾah of Nāfiʿ transmitted by Qālūn. Using a qualitative philological approach, the study combines codicological description with a textological examination of reading variants. The codicological analysis covers the manuscript’s paper, watermark, dimensions, textual arrangement, illumination, and dated colophon. Juz 30 is used for the textological analysis because the relevant folios are legible and contain numerous points at which canonical readings differ. The manuscript comprises 863 pages, begins at Q 3:82, and contains several displaced or missing folios. Its colophon names Ibrāhīm bin Aḥmad bin Aḥmad bin al-Amīn al-Khalīl, a Shāfiʿī from Zabīd, and dates completion to 4 Jumādā al-Ūlā 1153 AH (28 July 1740 CE). The analysed portion records four groups of morphological variants and twenty-seven phonological forms associated with Qālūn’s transmission. Because the examination is limited to Juz 30, the findings establish the reading pattern only for that section. The manuscript nevertheless provides material evidence that Nāfiʿ–Qālūn readings circulated within the wider manuscript environment of the Malay world alongside the region’s more common ʿĀṣim–Ḥafṣ tradition.