An increase in operating temperature of the crystalline photovoltaic modules (PVMs) has a significant impact on their electrical efficiency. Accurate determination of this parameter is crucial for a credible evaluation of PVM performance. Due to the difficulty of analytically solving the energy balance equations (EBEs) to determine the temperature profile of the various layers of the PVM, numerical solutions are often chosen. The exact analytical solution of these equations is challenging to achieve due to the complexity of some time-dependent parameters (solar irradiance, ambient temperature, wind speed, front and rear surface temperatures, & mldr;) and can only be reached in particular cases. To overcome this difficulty, some approximations are considered and permit the resolution of this problem analytically. In this study, a one-dimensional model is developed. It is based on an analytical solution of the steady-state EBEs. The analytical solution is reached by assuming that the time-varying parameters can be considered constant over more or less long time intervals, depending on the change rate of these parameters. The objective of this study is to propose an analytical model improving the prediction accuracy of the temporal and spatial evolution of the PVM operating temperature compared with literature results; meanwhile, simplifying the estimation process of the various photovoltaic system parameters. The experimental and modeling results obtained are compared with those evaluated using other relevant models. The compatibility between the experimental and model results attests to the reliability of the assumed approximations, with regard to calculated RMSE (0.78) and MBE (0.77) values.
This work extends the original Wave Closure Universal Law by integrating a two-part appendix. Appendix A provides complete mathematical derivations for field closure behavior using CNBIT-v3, π(t), ψ_closure, τ_corr, and entropy-free conditions. Appendix B presents narrative explanations, analogies, and illustrations, including the Schumann resonance and dynamic π(t) behavior. The publication introduces an interpretable structure for researchers, educators, and system designers interested in field closure principles in quantum, thermodynamic, and informational systems.
This study investigates image-based navigation methods and algorithms for devices, with a focus on curve detection as a key step in object recognition. Image-based navigation relies on identifying objects in the environment and determining the device’s position based on their coordinates. Roads were selected as the objects of interest, and their identification was explored through curve detection in images. Curve detection is a fundamental problem in computer vision, as curves represent object boundaries, contours, and trajectories, and play a critical role in shape analysis, cartography, and navigation systems. The study employs the Hessian matrix, constructed from second-order derivatives of pre-processed images, to analyze local curvature. By examining the eigenvalues of the Hessian matrix, local structures are classified, and pixels belonging to curves are identified with high precision. A curvature detection criterion based on the relative magnitudes of the eigenvalues is applied: if one eigenvalue is significantly larger than the other, the corresponding pixel is determined to lie on a curve. This approach enables accurate and robust identification of road structures in images, forming a reliable foundation for subsequent navigation and mapping applications.
Description / Abstract This paper presents a novel theoretical framework for describing the closure dynamics of information fields. We propose that information fields do not close through symmetric return mechanisms, but rather through spiral closure with direction vector inversion, resulting in a phase jump into a cyclic but torsional phase space. The mathematical formalization is based on the analysis of field divergence and dynamic behavior, showing empirical connections to prime number entropy, ex-dark-matter wave-tension models, and CNBIT–POSON coherence analysis. We present the first field-validated numerical simulation of the Null Closure Principle using CNBIT-v3 validated constants. The simulation demonstrates complete energy closure (99.89% of the time domain) under the condition |dE/dτ| < E_CNBIT, where E_CNBIT = 1.988186×10⁻²³ J/bit. This establishes the constant as a physically valid closure threshold and a reference point for future information-field models.
This publication introduces the Wave Closure Universal Law, a new principle stating that all waveforms persist only when field feedback and phase convergence are satisfied. Integrating the CNBIT-v3 quantized energy metric (1.988×10⁻²³ J/bit), the dynamic π(t) v2 model, and the Null Closure Principle, the law defines universal closure behavior across all fields (optical, quantum, acoustic, electromagnetic). The work includes mathematical formalization, numerical simulation, and integration with the T6 entropy-free closure model. A motivational example based on Schumann resonance is provided to illustrate real-world relevance.
