Search Results (171)

The paper outlines the hybrid framework of spin hydrodynamics, combining classical kinetic theory with the Israel–Stewart method of introducing dissipation. The local equilibrium expressions for the baryon current, the energy–momentum tensor, and the spin tensor of particles with spin 1/2 following the Fermi–Dirac statistics are obtained and compared with the earlier derived versions where the Boltzmann approximation was used. The expressions in the two cases are found to have the same form, but the coefficients are shown to be governed by different functions. The relative differences between the tensor coefficients in the Fermi–Dirac and Boltzmann cases are found to grow exponentially with the baryon chemical potential. In the proposed formalism, nonequilibrium processes are studied including mathematically possible dissipative corrections. Standard conservation laws are applied, and the condition of positive entropy production is shown to allow for the transfer between the spin and orbital parts of angular momentum. Full article

This study systematically investigates the effects of trap concentration on self-heating and terahertz (THz) responses in GaN HEMTs using Sentaurus TCAD. Traps, inherently unavoidable in semiconductors, can be strategically introduced to engineer specific energy levels that establish competitive dynamics between the electron momentum relaxation time and the carrier lifetime. A simulation-based exploration of this mechanism provides significant scientific value for enhancing device performance through self-heating mitigation and THz response optimization. An AlGaN/GaN heterojunction HEMT model was established, with trap concentrations ranging from 0 to $5\times {10}^{17} {\mathrm{c}\mathrm{m}}^{-3}$. The analysis reveals that traps significantly enhance channel current (achieving 3× gain at $1\times 10^{17} {\mathrm{c}\mathrm{m}}^{-3}$) via new energy levels that prolong carrier lifetime. However, elevated trap concentrations (>$1\times {10}^{16} {\mathrm{c}\mathrm{m}}^{-3}$) exacerbate self-heating-induced current collapse, reducing the min-to-max current ratio to 0.9158. In THz response characterization, devices exhibit a distinct DC component (${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$) under non-resonant detection ($\mathsf{\omega }\mathsf{\tau }\ll 1$). At a trap concentration of $1\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ peaks at $0.12 \mathrm{V}$ when ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-7.8 \mathrm{V}$. Compared to trap-free devices, a maximum response attenuation of 64.89% occurs at ${\mathrm{V}}_{\mathrm{g}}\mathrm{D}\mathrm{C}=-4.9 \mathrm{V}$. Furthermore, ${\mathrm{U}}_{\mathrm{d}\mathrm{c}}$ demonstrates non-monotonic behavior with concentration, showing local maxima at $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ and $7\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$, attributed to plasma wave damping and temperature-gradient-induced electric field variations. This research establishes trap engineering guidelines for GaN HEMTs: a concentration of $4\times {10}^{15} {\mathrm{c}\mathrm{m}}^{-3}$ optimally enhances conductivity while minimizing adverse impacts on both self-heating and the THz response, making it particularly suitable for high-sensitivity terahertz detectors. Full article

Load forecasting plays a crucial role in power system planning and operational dispatch management. Accurate load prediction is essential for enhancing power system reliability and facilitating the local integration of renewable energy. This paper proposes a hybrid approach combining traditional time series models (ARIMA) with machine learning models (SVR). The particle swarm optimization (PSO) algorithm is improved by adjusting its elastic momentum, and the enhanced APSO algorithm is employed to optimize the adaptive weights of the hybrid model. Consequently, an elastic momentum-enhanced adaptive weighted load forecasting model (APSO-ARIMA-SVR) is developed. Numerical simulations using real-world datasets validate the model’s effectiveness. Results demonstrate that the proposed APSO-ARIMA-SVR model achieves optimal fitting performance, with prediction errors of 274.23 (MAE) and 321.50 (RMSE), representing the lowest errors among all comparative models. Full article

The European Union (EU) is advancing a digital twin of its electricity grid as a flagship initiative to accelerate the dual transitions of decarbonization and digitalization. By creating a real-time virtual replica of the EU-27 power network, policymakers and industry stakeholders aim to enhance grid efficiency, resilience, and renewable energy integration. This review provides a comprehensive analysis of the three critical dimensions shaping the digital twin’s development: (1) regulatory barriers, including fragmented policies, inconsistent data governance frameworks, and the need for harmonized standards and incentives across member states; (2) technological challenges, such as achieving interoperability, integrating real-time data, developing robust cybersecurity measures, and ensuring scalable infrastructure; and (3) economic opportunities, centered on potential cost savings, optimized asset management, new flexibility services, and pathways for innovation and investment. Drawing on European Commission policy documents, regulatory reports, academic studies, and industry projects like the Horizon Europe TwinEU initiative, this review highlights that significant groundwork has been laid to prototype and federate local grid twins into a cohesive continental system. However, achieving the full potential of a pan-European digital twin will require additional regulatory harmonization, more mature data-sharing protocols, and sustained financial commitment. This review concludes with an outlook on the strategic convergence of policy reforms, collaborative R&D, and targeted funding, emphasizing how institutional momentum, federated architectures, and cross-sector integration are advancing a secure, resilient, and economically viable digital twin that is envisioned as a foundational layer in the operational and planning infrastructure of Europe’s future electricity system. Full article

The penetration of renewable energy, especially solar and wind, is increasing globally to promote a sustainable environment. However, in the Middle East, this momentum is slower compared to other regions, primarily due to abundant local fossil fuel reserves and historically low energy prices. This trend is shifting, with several countries, including the Kingdom of Saudi Arabia (KSA), setting ambitious goals. Specifically, KSA’s Vision 2030 aims to generate 50% of its energy from renewable sources by 2030. Due to favorable conditions for solar and wind, various mega-projects have either been completed or are underway in KSA. This study analyzes the potential and reliability impact of these projects on the power system through a three-step process. In the first step, all major projects are identified, and data related to these projects, such as global horizontal irradiance, wind speed, temperature, and other relevant parameters, are collected. In the second step, these data are used to estimate the solar and wind potential at various sites, along with annual averages and seasonal averages for different extreme seasons, such as winter and summer. Finally, in the third step, a reliability assessment of power generation is conducted to evaluate the adequacy of renewable projects within the national power grid. This study addresses a gap in the literature by providing a region-specific reliability analysis using actual project data from KSA, which remains underexplored in existing research. Sequential Monte Carlo simulations are employed, and various reliability indices, including Loss of Load Expectation (LOLE), Loss of Energy Expectation (LOEE), Loss of Load Frequency (LOLF), Energy Not Supplied per Interruption (ENSINT), and Demand Not Supplied per Interruption (DNSINT) are analyzed. The analysis shows that integrating renewable energy into KSA’s power grid significantly enhances its reliability. The analysis shows that integrating renewable energy into KSA’s power grid significantly enhances its reliability, with improvements observed across all reliability indices, demonstrating the viability of meeting Vision 2030 targets. Full article

The development of new technologies for the production of renewable energy is fundamental to reducing greenhouse gas emissions. Therefore, the search for new energy generation methods that are environmentally responsible, socially rational, and economically viable is gaining momentum in order to mitigate carbon footprint. The aviation sector is responsible for a significant fraction of greenhouse gas emissions; for this reason, the decarbonisation of this sector must be investigated using biorefinery models. This study presents a mixed-integer linear programming (MILP) model for optimising the design and configuration of the supply chain in different states of Brazil for the production of sustainable aviation fuel (SAF) and green diesel and gasoline, using microalgae cultivated in sugarcane vinasse as the raw material. The technology of hydrothermal liquefaction was assessed in terms of its capacity to convert microalgae without need for the energy-intensive drying step. The MILP model was developed in the LINGO v.20 software using a library of physical and economic process models. We consider the selection of processes based on the object of total minimum cost, with optimal production plant scaling and regional supply chain design, including an assessment of resources and final product distribution. A case study was implemented in Brazil, considering different regions of the country and its local demands for fuels. São Paulo is the most profitable state, with a cash flow of 1071.09 and an IRR of 36.19%, far outperforming the rest. Transport emissions alone represent between 0.6 and 8.6% of emissions generated by the model. The costs of raw materials, mainly hydrogen (57%) and electricity (27%) represent the main costs evaluated in the model. The production cost (MUS$/TJ biofuel) is in the range of 0.009–0.011. Finally, changes in the cost of electricity have the greatest impact on the model. Full article

With the continuous growth of global energy demand and the increasing severity of environmental issues, photovoltaic (PV) power generation, as a clean and renewable energy source, has attracted widespread attention. However, the performance of PV systems is easily affected by factors such as irradiance and temperature in complex environments, leading to significant fluctuations in output power and making it difficult to achieve stable and efficient energy conversion. To address this issue, this paper proposes an enhanced maximum power point tracking (MPPT) algorithm based on the combination of improved gray wolf optimizer (GWO) and incremental conductance (INC) methods, aiming to improve the adaptability and stability of PV systems in complex environments. By introducing innovative measures such as a candidate point dynamic focusing mechanism, position updates with perturbation factors, a five-level dynamic step-size strategy, direction consistency detection, and momentum suppression, the algorithm improves the search efficiency of the GWO and its adaptability to environmental mutations, avoids the drawbacks of fixed step sizes, and reduces overshoot and oscillations. Simulation verification was carried out on a simulation platform. The simulation results show that under various operating conditions, the algorithm achieves a good adaptive balance between global exploration and local exploitation, with tracking efficiency consistently above 99%, significantly improving the accuracy and efficiency of maximum power point tracking. Full article

Local equilibrium approximation (LEA) is a central assumption in many applications of non-equilibrium thermodynamics involving the transport of energy, mass, and momentum. However, assessing the validity of the LEA remains challenging due to the limited development of tools for characterizing non-equilibrium states compared to equilibrium states. To address this, we have developed a theory based on kinetic theory, which provides a nonlinear extension of the telegrapher’s equation commonly discussed in non-equilibrium frameworks that extend beyond LEA. A key result of this theory is a steady-state diffusion equation that accounts for the constraint imposed by available thermal energy on the diffusion flux. The theory is suitable for analysis of steady-state composition profiles and can be used to quantify the deviation from the local equilibrium. To validate the theory and test LEA, we performed molecular dynamics simulations on a two-component system where the two components had identical physical properties. The results show that deviation from the local equilibrium can be systematically quantified, and for the diffusion process we have studied here, we have confirmed that LEA remains accurate even under extreme concentration gradients in gas mixtures. Full article

One of the main interests of high-energy physics is the study of the phase diagram and the localization of phase transitions from hadronic to quark–gluonic matter. There are different techniques to study the hot matter. One of them is femtoscopy, which uses two-particle correlations to extract spatiotemporal characteristics of the emission source. Another approach involves obtaining thermodynamic parameters from the momentum distributions of produced particles based on various theoretical models. In this research, we perform a comparative analysis of femtoscopic volumes and volumes obtained using the Tsallis statistical fit. This analysis allows us to estimate system size at the time of kinetic freeze-out and its dependence on collision centrality and energy. We observe that at high energies, the volume values estimated taking the two approaches diverge significantly, while at low energies, they are more consistent. In the future, these results can help to combine these two different methods and provide a more comprehensive picture of the fireball produced in heavy-ion collisions. Full article

Star-forming galaxies are hosts of dominant populations of recently formed, hot, massive stars, which give rise to conspicuous stellar spectral features and provide the ionizing fluxes. Strong outflows of these stars shape their properties. These winds affect the evolution and the output of ionizing radiation, as well as the energy and momentum input in the interstellar medium and the chemical enrichment. Many properties of massive stars become even more extreme at a low metallicity. Owing to the pioneering observations of young, metal-poor stellar populations, both locally with HST and large ground-based facilities and at high redshift with JWST, we are at a key moment to assess our understanding of hot massive stars in these galaxies. Stellar population synthesis is a key tool. I will demonstrate how population models of hot, massive stars help to address some issues at the forefront of current research. The recent advent of new evolutionary and atmosphere models of massive stars probing new parameter space allows us to characterize the properties of nearby and distant populations. Full article

Storage ring X-ray light sources, which hold the great promises of high flux, high average brilliance, high stability, continuously adjustable spectra, and simultaneous multiple end-stations operations, have become indispensable tools for frontier research in diverse fields from materials science, condensed matter physics, chemistry, to life science, etc. Based on the double double-bend achromat (DDBA) lattice structure, an intermediate-energy electron storage ring with circumference of 288 m, emittance of 2.57 nm, is designed for dedicated materials research. Each cell of the storage ring consists of a 6.2 m-long straight section and a 1.86 m-short straight section, allowing more insertion devices to be accommodated in the entire ring. This lattice shows great nonlinear dynamic performances of large dynamic aperture and large local momentum aperture. Furthermore, the intra-beam scattering (IBS) effects under several circumstances, are also negligibly small. Full article

This study investigates the scattering dynamics of vector Bessel–Gaussian (BG) beams in winter haze environments, with a particular emphasis on the influence of ice-coated haze particles on light propagation. Employing the Generalized Lorenz–Mie Theory (GLMT), we analyze the scattering coefficients of particles transitioning from water to ice coatings under varying atmospheric conditions. Our results demonstrate that the presence of ice coatings significantly alters the scattering and extinction efficiencies of BG beams, revealing distinct differences compared to particles coated with water. Furthermore, the study examines the role of Orbital Angular Momentum (OAM) modes in shaping scattering behavior. We show that higher OAM modes, characterized by broader energy distributions and larger beam spot sizes, induce weaker localized interactions with individual particles, leading to diminished scattering and attenuation. In contrast, lower OAM modes, with energy concentrated in smaller regions, exhibit stronger interactions with particles, thereby enhancing scattering and attenuation. These findings align with the Beer–Lambert law in the single scattering regime, where beam intensity attenuation is influenced by the spatial distribution of radiation, while overall power attenuation follows the standard exponential decay with respect to propagation distance. The transmission attenuation of BG beams through haze-laden atmospheres is further explored, emphasizing the critical roles of particle concentration and humidity. This study provides valuable insights into the interactions between vector BG beams and atmospheric haze, advancing the understanding of optical communication and environmental monitoring in hazy conditions. Full article

Liquid metal is widely used as the primary coolant in many advanced nuclear energy systems. Prandtl number of liquid metal is much lower than that of the conventional coolant of water or gas. Based on the Reynolds analogy, the turbulent Prandtl number is assumed to be a constant around unity. For the turbulent convection of liquid metal, dissipations of half the temperature variance are larger than those of turbulent kinetic energies. The dissimilarity between the thermal and momentum fields increases as Pr decreases. The turbulent Prandtl number is larger than one for the liquid metal. In the current investigation, the turbulent convection of liquid metal in the channel is quasi-directly simulated with OpenFOAM-7. The turbulent statistics of the momentum and the thermal field are compared with the existing database to validate the numerical model. The power law for dimensionless temperature distribution with different Prandtl numbers is obtained by regression analysis of numerical results. A new Nusselt number correlation is derived based on the power law. The new Nusselt number correlation agrees well with the DNS results in the literature. The momentum mixing process between different layers in the cross section is compared with the thermal mixing process. The effects of the Prandtl number on the difference between the turbulence time scale and scalar time scale are analyzed. A new turbulent Prandtl number model with local parameters is obtained for turbulent convection with liquid metal. Combined with the $k-\omega$ model, the temperature distributions with the new turbulent Prandtl number model agree well with the DNS results in the literature. The new turbulent Prandtl number model can be used for turbulent convection with different Prandtl and different Reynolds numbers. Full article

In this paper, a hydrodynamic model of Jiaozhou Bay was developed using the Regional Ocean Modeling System and validated against observed tidal levels and current data. The model accurately characterizes the tidal and current features of the region. Based on this model, the spatial and temporal distributions of flow fields and tidal energy resources were analyzed. A 100-turbine tidal power plant was simulated utilizing a momentum-based approach that accounts for resource distribution, bathymetry, topography, and turbine parameters. The resulting hydrodynamic changes, including velocity variations peaking at 0.5 m/s within the turbine deployment zone and tidal level shifts confined to the bay (maximum change in ~10 cm), emphasize the importance of localized environmental assessments. However, the findings also highlight broader considerations for the sustainable development of tidal energy in semi-enclosed bays worldwide, where strategic siting and design can mitigate larger ecological disturbances. These findings may provide a scientific foundation for balancing clean energy extraction with minimal environmental impact, thus contributing to global efforts to develop more resilient and sustainable coastal energy systems. Full article

Offshore wind (OSW) technology has recently been included in California’s plans to achieve 100% carbon-free electricity by 2045. As an emerging technology, many features of OSW are changing more rapidly than established renewable options and are shaped by local circumstances in unique ways that limit transferrable experiences globally. This paper fills a gap in the literature by providing an updated technological assessment of OSW in California to determine its viability and competitiveness in the state’s electricity generation mix to achieve its near-term energy and environmental goals. Through a critical synthesis and extrapolation of technical, social, and economic analyses, we identify several major improvements in its potential. First, we note that while estimates of OSW’s costs per MWh of installed capacity have generally documented and projected a long-term decline, recent technical, microeconomic, and macroeconomic factors have caused significant backsliding of this momentum. Second, we project that the potential dollar value benefits of OSW’s greenhouse gas reduction capabilities have increased by one to two orders of magnitude, primarily due to major upward revisions of the social cost of carbon. Several co-benefits, including enhanced reliability, economic growth, and environmental justice, look to be increasingly promising due to a combination of technological advances and policy initiatives. Despite these advancements, OSW continues to face several engineering and broader challenges. We assess the current status of these challenges, as well as current and future strategies to address them. We conclude that OSW is now overall an even more attractive electricity-generating option than at the beginning of this decade. Full article