The European Physical Journal Plus最新文献

This study explores the thermal optimization of a cold square enclosure containing a heated circular cylinder, where the cylinder’s position varies along the vertical centerline of the enclosure. The cavity is filled with a suspension of nano-encapsulated phase change materials (NEPCMs) in a non-Newtonian fluid to enhance thermal performance. The primary aim is to examine the flow patterns, phase change dynamics, and overall thermal efficiency of the system. The governing equations for the NEPCMs nanofluid are reformulated into a dimensionless form and solved using the finite element method. Key parameters such as the cylinder’s position ((delta )), the power-law index (n), the NEPCMs particle volume fraction ((phi )), the fusion temperature ((varTheta _F)), and the Rayleigh number (Ra) are systematically analyzed to assess their influence on thermal performance. The findings of the study indicate that the region of active NEPCM fusion grows with increasing NEPCM concentration, except in the case of pseudoplastic fluids. The vertical position of the heated cylinder acts as an effective passive control parameter. Increasing NEPCM concentration consistently enhances overall heat transfer for all fluid types.

In this paper we study the first nonlinear stage of modulation instability (NLSMI) of x-periodic anomalous waves (AWs) in multidimensional generalizations of the focusing nonlinear Schrödinger (NLS) equation, like the non-integrable elliptic and hyperbolic NLS equations in (2+1) and (3+1) dimensions. In the quasi one-dimensional (Q1D) regime, where the wavelength in the x direction of propagation is significantly smaller than in the transversal directions, the behavior at leading order is universal, independent of the particular model, and described by adiabatic deformations of the Akhmediev breather solution of NLS. Varying the initial data, the first NLSMI shows various combinations of basic processes, like AW growth from the unstable background, followed by fission in the slowly varying transversal directions, and the inverse process of fusion, followed by AW decay to the background. Fission and fusion are critical processes showing similarities with multidimensional wave breaking, and with phase transitions of second kind and critical exponent 1/2. In (3+1) dimensions with radial symmetry in the transversal plane, fission consists in the formation of an opening smoke ring, while if the symmetry is hyperbolic in the transversal plane, the growing Q1D AW is an X-wave undergoing fission into branches of hyperbolas. In the long wave limit, the Q1D Akhmediev breather reduces to the Q1D analogue of the Peregrine instanton, rationally localized in space. Numerical experiments on the hyperbolic NLS equation show that the process of “AW growth + fission” is not restricted to the Q1D regime, extending to a finite region of the modulation instability domain. At last, we pose and solve the “inverse time-scattering problem of AWs”: the reconstruction of the (O({epsilon })) initial perturbation of the background, from the knowledge of the first nonlinear stages of modulation instability for positive and negative times. The universality of these processes suggests their observability in natural phenomena related to AWs in contexts such as water waves, nonlinear optics, plasma physics, and Bose–Einstein condensates.

Human exploration beyond low Earth orbit poses unique health and operational challenges, with space radiation recognized as one of the most significant hazards. This comprehensive review examines the complex nature of the space radiation environment, its biological effects on humans and life support systems, and current strategies for risk assessment and mitigation. It details the composition and properties of galactic cosmic rays (GCRs) and solar particle events (SPEs), their interactions with spacecraft shielding, and the resulting biological impacts ranging from DNA damage to systemic effects including cancer, cardiovascular disease, and central nervous system impairments. Special emphasis is given to the combined effects of radiation and microgravity, which together alter cellular function and influence health outcomes. The paper also explores the effects of radiation on plants and microorganisms as biological components of bioregenerative life support systems (BLSS). The issue of radiation-induced degradation of food and pharmaceuticals is also considered. Existing and emerging countermeasures, encompassing passive and active shielding, pharmacological agents, nutrition, physiological adaptations like synthetic hibernation, and personalized risk assessment through targeted crew selection are critically reviewed. Additionally, the work highlights the importance of high-fidelity analog studies, space-based experiments, and advanced risk models integrating physical, biological, and operational data to inform future mission planning. Finally, the paper reviews existing infrastructures, experimental platforms, and European research programs, emphasizing the critical role of ground-based accelerators, space analog environments, and in-flight studies in advancing our understanding of radiation risks. By identifying key knowledge gaps and proposing a structured mitigation framework, this study presents a strategic roadmap for protecting human health and sustaining life during long-duration missions to the Moon, Mars, and beyond. (The review work described in the paper stems from the discussions within the working group on Radiation sponsored by the Italian Space Agency.)

Nonlinear wave phenomena play a central role in fluid dynamics and plasma physics. Soliton interaction is a key feature of such systems. The coupled Korteweg–de Vries (KdV) equations describe these nonlinear and dispersive waves. However, obtaining accurate and stable solutions remains difficult. This study presents a combined analytical and machine-learning approach. Analytical two-soliton solutions are derived using Hirota’s bilinear method. Dispersion relations and interaction properties are obtained to explain the evolution of wave profiles. Interaction times and peak positions are computed numerically to track soliton behavior before, during, and after collision. A modified physics-informed neural network (PINN) is then developed. Global physical constraints, such as energy conservation, are included directly in the loss function. This ensures that the learned solutions remain consistent with the underlying physics. Numerical experiments show that the PINN framework provides improved stability and accuracy. The model captures long-term nonlinear wave interactions with higher fidelity. The proposed method offers a reliable computational framework for analyzing coupled KdV systems and other nonlinear dispersive wave models.

In this work, the propagation of optical solitons in magneto-optic waveguides is investigated with the inclusion of self-phase modulation modeled by Kudryashov’s quintuple power-law. Further, generalized temporal evolution and nonlinear chromatic dispersion have been taken into consideration. Higher-order nonlinearities and dispersive effects are considered in the study. Using the Sardar sub-equation method, soliton solutions are obtained such as bright, kink, and double-hump profiles. Numerical simulations confirm theoretical findings and show stability for the optical soliton under varying parameter conditions. Bifurcation analysis and chaos analysis are performed using phase portraits, time-series data, Lyapunov exponents, and bifurcation maps, detailing the dynamical characteristics of the system. These results will add to the knowledge about soliton dynamics in magneto-optic waveguides and will indicate some possible applications in high-speed optical communication and photonic technologies.

The paper proposes the analysis of a rather general reaction–diffusion equation in ((2+1))-dimensions with time-dependent coefficients. The novelty brought by our approach refers to the analysis of the equation with the diffusion coefficient as an explicit function of time and the dependent variable. The free derivative term called source will be considered here to be both linear and quadratic in the main variable. The reported results are of twofold importance: (i) for modeling real diffusion phenomena, such as the spread of tumor cells throughout brain tissue; (ii) for investigating mathematical models described by PDEs with variable coefficients in ((2+1))-dimensions, insufficiently studied until now.

This work examines the coupled flow–acoustic behaviour of a compact hybrid motorcycle muffler incorporating half-elliptical baffles, dual Helmholtz resonators, and ceramic-wool absorptive packing for a high-speed single-cylinder engine. Baseline spectral analysis of the untreated exhaust identified a dominant tonal component at 511 Hz, which guided the temperature-corrected tuning of the resonator cavities. One-dimensional acoustic simulations using Ricardo Wave predicted frequency-dependent transmission loss characterized by resonator-induced attenuation in the mid-frequency range and a progressive broadband increase associated with dissipative mechanisms. Three-dimensional CFD analysis revealed that the half-elliptical baffles condition the internal flow by redirecting the exhaust stream towards the absorptive region while limiting large-scale recirculation, thereby promoting stable acoustic coupling with the resonators under varying operating conditions. Experimental validation was carried out using ISO 5130:2019–compliant, dB(C)-weighted sound pressure level measurements, which indicated reductions of approximately 10–11 dB(C) at idle and 14–15 dB (C) at 7500 rpm, achieving compliance with Formula Bharat noise limits. The combined numerical and experimental results indicate that curvature-conditioned flow management, when integrated with reactive and dissipative elements, provides an effective and compact approach for broadband and tonal noise reduction in small-displacement engine exhaust systems.

This study presents a novel non-invasive dual wavelength photoacoustic imaging (DWPAI) system developed to detect distinct spectral signatures of historical ink families with high sensitivity. The recorded images were processed through unsupervised machine learning algorithms, to provide a quantitative indicator of the ink type based on the ratio of photoacoustic signals following excitation in the visible (532 nm) and near-infrared (1064 nm). The performance of the system was demonstrated using three inks commonly employed in 19th-century Europe and Greece, specifically Chinese ink, sepia ink, and iron gall ink. Chinese ink provided signal ratios around 0.9, sepia ink yielded consistent ratios at 0.6, whereas iron gall ink exhibited considerably higher ratios in the order of 1.7. Our findings demonstrate the ability of DWPAI to reliably and non-destructively discriminate between major ink families independent of the writer or the nib type used. Apart from guiding conservators in safe and effective restoration interventions, DWPAI may provide archaeologists and art historians with complementary insights into the dating, origin, and material characterization of various types of artifacts. Its demonstrated accuracy and versatility establish DWPAI as a powerful diagnostic tool for cultural heritage research, archaeology, and conservation science.

The intersection of machine learning and art authentication has emerged as a transformative area within the field of art analysis. This paper explores the application of various machine learning techniques to enhance the efficiency of art authentication processes. Two procedures with potential use in the identification of forgeries are discussed. The supervised one uses attribution markers collected in an extensive analysis of paintings as input to a classification model. The resulting classifier should aid an art expert in the final assessment of authenticity. The unsupervised method is easier to carry out, as it does not require labeled training data. It may help to identify forged artworks as outliers in the dataset by measuring their similarities to authentic objects. The methods are tested on paintings attributed to M. Willmann and A. Grottger, respectively. Our findings open up new avenues for research and exploration at the intersection of the art world and machine learning. They also emphasize the importance of a collaborative approach that integrates traditional art historical expertise with advanced computational methods, thereby enriching the understanding of artworks and enhancing the efficacy of authentication practices.

Graphical abstract

This study presents a new model of anisotropic quintessence compact stars within the framework of 5-dimensional Einstein–Gauss–Bonnet gravity (EGBG). To analyze the interior structure of the stellar configuration, we employ a static and spherically symmetric line element to derive the corresponding field equations in EGBG. The generalized Tolman–Kuchowicz metric potential is adopted to obtain exact solutions of the governing equations. By applying the continuity conditions at the boundary, we determine the numerical values of the constants appearing in the metric ansatz, using observational data for the mass and radius of the compact star. A comprehensive physical analysis is carried out by evaluating several key physical requirements to ensure the viability of the model. To this end, we derive analytical expressions for relevant physical quantities and present their graphical behavior. The stability of the model is assessed through the adiabatic index and Herrera’s cracking concept based on sound speed analysis. The effects of the Gauss–Bonnet coupling parameter (alpha), as well as the parameter n introduced via the generalized metric ansatz, are thoroughly examined. Furthermore, we explore the mass–radius relationship to evaluate the compactness factor and surface redshift of the stellar configuration. This comprehensive approach ensures that the proposed stellar model satisfies the fundamental physical criteria required for a realistic and stable compact object. Overall, the study enhances our understanding of dense astrophysical bodies and supports the development of EGBG theory, thereby paving the way for future investigations in this domain.