Search
358 articles for “numerical model”
-
Optimizing Performance Characteristics, Thermal Stability, and Manufacturing Performance of Polymer Nanocomposites Using Artificial Intelligence
Abstract: Artificial intelligence (AI) has proven an efficient method to optimize the design and manufacture of polymer nanocomposites, allowing the proper prediction of the behavior of the materials and the results of the processing. This work proposes an AI-based framework to enhance the performance characteristics, thermal stability and manufacturing performance of advanced polymer nanocomposites. The input variables of the proposed framework are the material composition, the nanoparticle concentration, the particle size, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
-
Microvita as a Fermi-Boson Hybrid Quantum Excitation: A Statistical Pathway Toward Unified Physics, Chemistry, and Biological Organization
Abstract: This article reformulates Microvita as a hybrid quantum excitation that interpolates continuously between fermionic and bosonic statistical behavior. A generalized operator algebra, a dynamical statistical order parameter, and a Lorentz-covariant field equation are used to frame Microvita as an effective unification scheme rather than a mere philosophical construct. The formalism predicts renormalization-group flow between infrared fermionic and ultraviolet bosonic limits, while numerical profiles suggest vacuum-energy smoothing and topological-defect suppression in …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 115–122 Read article
-
Wet Multi Plate Clutch Failure: A Review
Abstract: To create a successful design that satisfies modern demands, the traditional theoretical method of computing temperature area, in particular the maximum temperature considered inside the surfaces of the friction take hold of disc best during the single engagement, is used. The entire engagement time was 5s, although the temperature fields were calculated during 6 consecutive engagements. In order to calculate the heat conductivity of the friction grasp machine, a three-dimensional …
Published in Journal of Automobile Engineering and Applications · Vol. 10, Issue 1, 2023 · pp. 1–10 Read article
-
Numerical Prediction of Shear Modulus of Multi-Layer PUF Cored Sandwich Composites
Abstract: The present numerical investigation was mainly concerned with the evaluation of apparent shear modulus (Gc) of multi-layered polyurethane foam cored sandwich beams using a novel approach through the medium of general purpose program i.e. FEM/ANSYS. Aiming to the goal, three-point bending analysis was performed on sandwich beam models made up of composite face sheets and multi-layer polyurethane foam cores of different layer densities. Finite element models of sandwich beams were …
Published in Journal of Polymer & Composites · Vol. 5, Issue 3, 2017 · pp. 53–61 Read article
-
Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
A Resource Efficient Fast Recovery Strategy for Survivable WDM Networks
Abstract: ABSTRACT In WDM networks when failure occurs, huge amount of data is lost in a fraction of second. Therefore, the failed connection request must be re-routed through backup route as soon as possible. For achieving fast connection recovery, the primary lightpath is either link or segmented protected. However, the strategies result in inefficient utilization of resources. In this paper, we present a resource efficient parallel signaling-shared path protection (PS-SPP) based …
Published in Trends in Opto-electro & Optical Communication · Vol. 2, Issue 1, 2012 · pp. 1–17 Read article
-
Fractional Riemannian Fuzzy C-Means with Time-Series Regularization for Economic Manifold Forecasting
Abstract: A fractional Riemannian fuzzy c-means framework is proposed for uncertain economic forecasting on non-Euclidean data domains. Observations are represented on a Riemannian manifold, cluster centres are intrinsic prototypes, and a latent fuzzy regime signal is regularised by both autoregressive and fractional-memory penalties. The resulting objective couples geometric clustering with time-series consistency, thereby discouraging partitions that are locally plausible but temporally incoherent. Closed-form membership updates, exponential-map centre updates, normal equations for …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 49–55 Read article
-
Numerical Studies on Deep Drawability of the Aluminium Alloy, AA6082 and Parameters Affecting It
Abstract: Deep drawing is a metal forming operation used for manufacturing sheet-metal components for application in the automobile, aerospace, and packaging industries. The objective of the present work was to study the various parameters influencing the drawability of AA6082. The deep-drawing process was modeled and simulated in Ls-Dyna Pre-Post(R) V4.6.17 software. The tensile test was performed according to the ASTM-E8M standard on AA6082-T6 material and subsequently annealed to attain higher ductility. …
Published in Journal of Polymer & Composites Read article
-
Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 8–20 Read article
-
Constrained Online Non Negative Matrix Factorization (CONMF) for Visual Tracking
Abstract: Visual tracking is the process of locating a moving object (or multiple objects) over time using a camera. It is one of the most important components in numerous applications such as military, secure control, crime prevention systems, access control and biometric identification etc. of computer vision. In visual tracking, holistic and part-based representations are both popular choices to model target appearance. The former is known for great efficiency and convenience …
Published in Current Trends in Signal Processing · Vol. 7, Issue 1, 2017 · pp. 8–18 Read article
-
Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article
-
Representation-Theoretic Symmetry Reduction and Fuzzy-Grey Optimization of Modular Vibration Systems
Abstract: This paper presents a representation-theoretic framework for symmetry-aware vibration control in modular structural systems. Exploiting cyclic symmetry, the mass, damping, and stiffness operators are block-diagonalised into irreducible representations, reducing the full structural dynamics to a collection of lower-dimensional modal subsystems. This decomposition provides both computational efficiency and a rigorous mathematical description of symmetry-preserving dynamic behaviour. To account for imperfections arising in practical implementations, near-symmetry defects in stiffness and damping are …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 22–30 Read article
-
Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
-
Identification of Brain Stroke Using Artificial Intelligence
Abstract: Globally, strokes are the primary cause of disability and mortality. Recently, machine learning (ML) and deep learning (DL) have been employed by artificial intelligence algorithms as effective stroke diagnosing techniques. These days, machine learning and data mining technologies are used in the construction of the main models. We have used five machine learning algorithms to determine if a stroke has occurred or is likely to occur based on a patient’s …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
-
Penetrative Thermomagnetic Convection in a Micropolar Ferrofluid Layer via Internal Heating
Abstract: Through the internal heating model thermomagnetic convection in a micropolar ferrofluid layer has been studied in the presence of a uniform vertical magnetic field. The rigid-isothermal boundaries are considered to be paramagnetic. The eigenvalue problem is solved numerically by Galerkin technique. The system stability is dependent on the various parameters like, dimensionless internal heat source strength Ns, magnetic parameter M1, the non-linearity of magnetization parameter M3, magnetic susceptibility χ, coupling …
Published in Journal of Experimental & Applied Mechanics · Vol. 11, Issue 2, 2020 · pp. 30–50 Read article
-
Numerical Investigation of Ply-by-Ply Failure and Strength Degradation in Composite Laminates Under Transverse Loading
Abstract: This paper represents the failure analysis of composite symmetric and antisymmetric laminate, when laminates were subjected to the transverse loading conditions. The load is uniformly distributed in a transverse direction. The analysis includes failure load and nature of failure by using theories of failure. The ply degradation material model is used to modify and update the properties of failed lamina and upgrades the properties of laminate. Laminate is modelled as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
-
Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
-
An empirical investigation using artificial neural networks to evaluate the manageability of object-oriented systems
Abstract: Software can be called quality software if it produces consistent outputs over multiple time of testing. There can be very much difficulties to modify and maintain the software with poor maintainability. For assessing the characteristics of object-oriented software, such as scale, inheritance, integrity, and coupling, numerous object-oriented metrics have been recommended. In this study, we explore object-oriented variables that have the potential to be significant antecedents of software maintenance. In …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 50–58 Read article
-
Artificial Intelligence in Robotics: Current Trends, Applications, and Future Challenges
Abstract: The incorporation of artificial intelligence (AI) into robotics has transformed the industry by greatly improving robots' capacity to carry out complex and autonomous functions in a wide range of sectors. This paper explores the evolution, applications, and challenges associated with AI-driven robotics. It examines key AI methodologies employed in robotics, including machine learning, natural language processing (NLP), computer vision, and planning/control algorithms, which enable robots to perceive, learn, and interact …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 31–43 Read article