Terms Of Energy Research Articles

Meshfree methods for nonlinear equilibrium radiation diffusion equation with interface and discontinuous coefficient

The partial differential equation describing equilibrium radiation diffusion is strongly nonlinear, which has been widely utilized in various fields such as astrophysics and others. The equilibrium radiation diffusion equation usually appears over multiple complicated domains, and the material characteristics vary between each domain. The diffusion coefficient near the interface is discontinuous. In this paper, the equilibrium radiation diffusion equation with discontinuous diffusion coefficient will be solved numerically by the unsymmetric radial basis function collocation method. The energy term T4 is linearized by utilizing the Picard-Newton and Richtmyer linearization methods on the basis of the fully implicit scheme discretization. And the successive permutation iteration and direct linearization methods are applied to linearize the diffusion terms. The accuracy of the proposed methods is proved by numerical experiments for regular and irregular domains with different types of interfaces.

Physisorption of benzene on cation/silica clusters via cation-π interactions: Theoretical study

Interactions of a benzene molecule with four different silica clusters decorated with mono- and divalent cations (Li+, Na+, Mg2+) have been theoretically studied. By means of SAPT0 calculations, we have analyzed the changes in the energy components in dependence of hydrophobic or hydrophilic positions of adsorption, the size of the cluster studied or the cation used for the ’decoration’. It was found that adsorption of benzene on pristine silica clusters is mainly driven by electrostatic (∼37–43 %) and dispersion (∼37–55 %) forces. At the same time, cation-π interactions can be accounted for by significant electrostatic (∼20–50 %) and induction (∼24–54 %) energy terms. IGM analysis reveals the existence of cation-π and van der Waals interactions. The significant binding of benzene to the decorated silica surface (up to ∼ − 19.97, −29.63, − 93.82 kcal/mol for Na+, Li+, Mg2+, respectively) can pave a way for the sorption of a typical organic contaminant.

Size Dependence of the Tetragonal to Orthorhombic Phase Transition of Ammonia Borane in Nanoconfinement.

We have investigated the thermodynamic property modification of ammonia borane via nanoconfinement. Two different mesoporous silica scaffolds, SBA-15 and MCM-41, were used to confine ammonia borane. Using in situ Raman spectroscopy, we examined how pore size influences the phase transition temperature from tetragonal (I4mm) to orthorhombic (Pmn21) for ammonia borane. In bulk ammonia borane, the phase transition occurs at around 217 K; however, confinement in SBA-15 (with ~8 nm pore sizes) reduces this temperature to approximately 195 K, while confinement in MCM-41 (with pore sizes of 2.1-2.7 nm) further lowers it to below 90 K. This suppression of the phase transition as a function of pore size has not been previously studied using Raman spectroscopy. The stability of the I4mm phase at a much lower temperature can be interpreted by incorporating the surface energy terms to the overall free energy of the system in a simple thermodynamic model, which leads to a significant increase in the surface energy when transitioning from the tetragonal phase to the orthorhombic phase.

Perturbational and variational energy decomposition analysis on hydrogen bonds of coordinated glycine with water molecule.

Three types of hydrogen bonds of coordinated glycine and water had been investigated: NH/O of α-amino group, O1/HO involving oxygen coordinated to the metal ion (O1), and O2/HO involving α-carbonyl oxygen (O2). Various glycine complexes were investigated: octahedral cobalt(III) and nickel(II), square pyramidal copper(II), and square planar copper(II), palladium(II), and platinum(II) complexes. Nature of these three hydrogen bond types was analysed using symmetry-adapted perturbation theory (SAPT) and variational energy decomposition analysis (EDA) method (TPSS-D3/def2-TZVPP). The results of the EDA decomposition are in good agreement with the reliable SAPT2+3/def2-TZVPP and its total interaction values with CCSD(T)/CBS energies. Electrostatic interaction is generally the dominant attractive energy term in most of the interactions, followed by orbital relaxation, and lastly dispersion as the weakest. We compared EDA results of various complexes to determine the effects of complex charge, metal oxidation, coordination, and atomic number on the energy decomposition terms. The complex charge influences the values of decomposition terms the most, followed by metal oxidation and coordination number, while atomic number effects them the least. All complex and metal changes have a more significant effect on the results of NH/O and O1/HO then O2/HO interactions, due to its location further away from the metal ion.

Collective nature of phonon energies beyond harmonic oscillators

Phonon quasi-particles have been monumental in microscopically understanding thermodynamics and transport properties in condensed matter for decades. Phonons have one-to-one correspondence with harmonic eigenstates and their energies are often described by simple independent harmonic oscillator models. Higher order terms in the potential energy lead to interactions among them, resulting in finite lifetimes and frequency shifts, even in perfect crystals. However, increasing evidence including constant volume heat capacity violating the Dulong-Petit law suggests the need for re-evaluation of phonons as having independent harmonic energies. In this work, we explicitly examine inter-mode dependence of phonon energies of a prototypical crystal, silicon, through energy covariance calculations and demonstrate the concerted nature of phonon energies even at 300 K, questioning independent harmonic oscillator assumptions commonly used for phonon energy descriptions of thermodynamics and transport.

A level-set method for fast image segmentation based on local pre-fitting and bilateral filtering

PurposeAlthough many conventional level-set approaches can be used for segmenting images containing factors such as noise and intensity inhomogeneities, they still can impact the accuracy of the results seriously. To solve this problem, a level-set method for fast image segmentation based on pre-fitting and bilateral filtering is proposed.Design/methodology/approachFirstly, an improved bilateral filter was investigated for image preprocessing. Secondly, by computing the local average intensity of the preprocessed enhanced picture, two local pre-fitting functions were defined. Thirdly, a new level-set energy functional was defined. Finally, a new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level-set function in a smooth state.FindingsThe experimental results demonstrate that the proposed model has an excellent segmentation capability for images with noise and intensity inhomogeneities and has different degrees of performance improvement compared with the mainstream models.Originality/value(C1) An improved bilateral filter was investigated and integrated into the model. (C2) Proposing two local pre-fitting functions by computing the local average intensity of the preprocessed enhanced image. (C3) Proposing a new level-set energy functional. (C4) A new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level set function in a smooth state. (C5) Analyzing and comparing the performance of the proposed model with other similar models.

AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics.

All-atom molecular simulations offer detailed insights into macromolecular phenomena, but their substantial computational cost hinders the exploration of complex biological processes. We introduce Advanced Machine-learning Atomic Representation Omni-force-field (AMARO), a new neural network potential (NNP) that combines an O(3)-equivariant message-passing neural network architecture, TensorNet, with a coarse-graining map that excludes hydrogen atoms. AMARO demonstrates the feasibility of training coarser NNP, without prior energy terms, to run stable protein dynamics with scalability and generalization capabilities.

Validation of OpenFOAM with respect to the elementary processes involved in the generation of waves by subaerial landslides

This study presents a validation of the OpenFOAM multiphase solver (i.e., multiphaseInterFoam) with respect to the elementary processes involved in the simulation of waves generated by high mobility subaerial landslide with a specific focus on the computation of energy terms. These processes include slide flow over a slope, impulse wave generation, wave dispersion, wave propagation and breaking. The simulations are conducted in 2D. The results allow to determine the minimum number of cells and the appropriate model tuning to reach acceptable accuracy while maintaining the computation time in a reasonable limit. To respect energy conservation, the choice of the turbulence model appears critical. Only, with a turbulence including a buoyancy term in the equations to account for the multiphase flow, and optimized initial values of the turbulence model parameters, could be the energy components of the flow accurately calculated. This study highlights the complexity of the phenomenon and the care with which, simulations should be conducted for the accurate computation of the energy transfers in the context of subaerial landslides.

Consistency-enhanced modified SAV time-stepping method with relaxation for binary mixture of and viscous fluids

In this work, the binary mixture of nematic liquid crystals and viscous fluids (NLC-VF) system consists of the Cahn–Hilliard (CH) equations for the phase-field variable for the free interface, the Allen–Cahn (AC) type constitutive equation for the nematic director, and the incompressible Navier–Stokes (NS) equation for the two fluids. To address the computational challenges posed by this complex system, we propose a scheme that is fully decoupled, energy-stable and highly consistent, based on a modified scalar auxiliary variable (MSAV) with stabilization. Our approach employs two auxiliary variables: one derived from the nonlinear terms in the original energy, and the other leveraging the “zero-energy-contribution (ZEC) ”property satisfied by some nonlinear terms. To ensure consistency between the continuous and discrete auxiliary variables, we employ relaxation techniques. Besides, the proposed method enables sequential solving of each variable, and the computational overhead of the relaxation technique is minimal, resulting in highly efficient computation. We demonstrate the accuracy, stability, consistency, and practicality of the method through comprehensive numerical experiments, and provide rigorous proof of its unconditional energy stability.

Shear elastic buckling of corrugated steel plate shear walls with stiffeners considering torsional rigidity

This paper conducted theoretical and numerical investigations on shear elastic buckling formulas of stiffened corrugated steel plate shear walls (SCSPSWs) considering torsional rigidities of stiffeners. Firstly, based on the orthotropic plate theory and the energy method, a theoretical model for the derivation of elastic buckling coefficients was established, introducing the torsional strain energy term of the stiffeners. On this basis, the variation law of the elastic buckling coefficient of the walls concerning the stiffener positions was studied, determining the optimal layout of the stiffeners. The formula for calculating the elastic buckling coefficient at any stiffener layout was provided. Furthermore, based on the stiffeners arranged in the optimal layout, the transition torsional rigidity of the stiffeners was determined, and the formulas for the elastic buckling coefficient of the SCSPSW with stiffeners considering torsional rigidity were proposed, in which the enhancement of torsional constraints provided by the stiffeners was measured by an enhancement factor. Finally, eigenvalue buckling analyses were performed based on finite element models to validate the theoretical analysis results on the optimal stiffener layout and elastic buckling coefficient.

A Consistent Kinetic Fokker–Planck Model for Gas Mixtures

We propose a general multi-species Fokker–Planck model. We prove consistency of our model: conservation properties, positivity of all temperatures, H-Theorem and the shape of equilibrium as Maxwell distributions with the same mean velocity and temperature. Moreover, we derive the usual macroscopic equations from the kinetic two-species BGK model and compute explicitly the exchange terms of momentum and energy.

Emergent potentials and non-perturbative open topological strings

We show that integrating out M2 branes ending on M5 branes inside Calabi-Yau manifolds captures non-perturbative open topological string physics. The integrating out is performed using a contour integral in complexified Schwinger proper time. For the resolved conifold, this contour can be extended to include the zero pole, which we argue captures the ultraviolet completion of the integrating out and yields the tree-level polynomial terms in the free energy. This is a manifestation of the Emergence Proposal, and provides further evidence for it. Unlike the case of closed strings, where the emergent terms are kinetic terms in the action, for these open strings it is tree-level potential terms which are emergent. This provides a first quantitative example of the proposal that classical tree-level potentials in string theory emerge from integrating out co-dimension one states.

Chemical Reaction Simulator on Quantum Computers by First Quantization (II)─Basic Treatment: Implementation.

Chemical simulation is a key application area that can leverage the power of quantum computers. A chemical simulator that implements a grid-based first quantization method has promising characteristics, but an implementation fully in quantum circuits seems to have not been published. Here, we present "crsQ" (chemical reaction simulator Q), which is a quantum circuit generator that generates such a chemical simulator. The generated simulator is capable of antisymmetrization of the initial wave function and time-evolution of the wave function based on the Suzuki-Trotter decomposition. The potential energy term of the Hamiltonian is implemented using arithmetic gates, such as adders, subtractors, multipliers, dividers, and square roots. Circuit diagrams and output samples are shown. The number of qubits in the circuits scales on the order of O(η log η), where η is the number of electrons. Each component of the generated circuit was verified in unit tests. Along with this development, we designed frameworks to ease the development of large-scale circuits, namely, a temporary qubit allocation framework and an abstract syntax tree framework for arithmetic formulas. These frameworks are expected to be useful in large-scale quantum circuit generators.

Measuring the solubility of tacrolimus in supercritical carbon dioxide (binary and ternary systems), comparing the performance of machine learning models with conventional models

The solubility of tacrolimus in a supercritical carbon dioxide (SC-CO2) with and without co-solvent (ternary and binary system) was investigated. The experimental conditions include the temperatures of 308 to 338 K and the pressures of 12 to 30 MPa were considered. The values of tacrolimus solubilization in SC-CO2 in binary and ternary systems were from 0.416 × 10−5 to 1.589 × 10−5 and from 0.389 × 10−4 to 0.875 × 10−4, respectively. The obtained results presented that adding a co-solvent (ethanol) could affect tacrolimus solubility significantly, the mole fraction of tacrolimus in SC-CO2/co-solvent under all experimental conditions was at least 4.9 more than that of SC-CO2 alone. The correlation of the solubility data was achieved by three distinct methods: (1) SRK EoS with van der Waals (vdW2) and Wong-Sandler (WS) as mixing rules, (2) solution theory, (3) empirical and (4) machine learning based models. The analysis of variance (ANOVA) results showed that Sparks et al. (AIC −817.05, and AARD 5.08 %) and Bian et al. (AIC −815.77 and AARD 5.17 %) models could correlate the experimental data of tacrolimus in SC-CO2 with more accuracy, as compared to the other empirical models. Sodeifian and Sajadian model with AARD% and AIC of 2.99 and −726.22, respectively, has acted as the most accurate empirical model in ternary system. The solution theory was able to calculate the solubility for the tacrolimus-SC-CO2-ethanol system with high accuracy (AARD, % 4.85, AIC −701.41, F value 169.70 and Radj 0.9622). Also, the Gradient Boosting model (AARD accurately predicted the outcomes with perfect accuracy for binary and ternary systems. Finally, total (ΔHtotal, 23.21 cal/mol), solvation (ΔHsol, −19.47 cal/mol) and vaporization (ΔHvap, 42.68 cal/mol) enthalpies were obtained by using an energy term in Chrastil and Bartle models.

Improving turbulence modeling for gas turbine blades: A novel approach to address flow transition and stagnation point anomalies

Accurate prediction of temperature and Heat Transfer Coefficient (HTC) distributions over gas turbine blades is crucial for the design process and life assessment of these components. Numerical studies of flow over gas turbine blades face significant challenges in accurately simulating two complex phenomena: (1) the transition of flow from laminar to turbulent, and (2) stagnation point flow at the leading edge. Many turbulence models tend to overpredict the temperature on turbine blades, leading to incorrect identification of hot-spot regions and, consequently, erroneous estimations of blade life. This paper investigates the performance of various turbulence models in simulating flow and heat transfer over gas turbine vanes. The study includes three full turbulence models, i.e., Spalart-Allmaras (SA), Shear Stress Transport k−ω (SST-kw), and v2−f (V2F), as well as two transitional models, i.e., Transition SST (Trans-SST) and k−kL−ω (k-kl-w). Simulation results indicate that the v2−f, Trans-SST, and k−kL−ω models can detect flow transition. However, the transition length and onset location predicted by the Trans-SST and k−kL−ω models do not align with experimental data. Conversely, the v2−f model suffers from over-predictions at the leading edge due to stagnation point anomaly. To address these issues and due to capacities of the V2F model, this study proposes two modifications to enhance the performance of the V2F model. First, the production term of turbulent kinetic energy is redefined to mitigate the stagnation point anomaly. Second, the model is recalibrated to improve the prediction of flow transition. The new model, named the Production Modified V2F (PMV2F) model, shows promising results in predicting temperature and heat transfer coefficients.

The influence of renewable energy and financial development on testing the environmental Kuznets curve in Lebanon: ARDL approach

This study considers the impacts of financial development and the consumption of renewable energy in Lebanon for the period 1990–2021, employing the Environmental Kuznets Curve. The financial sector in Lebanon is considered a major engine in the economic development. Green energy sources and environmental protection are taking higher importance nowadays with the increase of implications for climate change and global warming worldwide. This paper examines the Environmental Kuznets Curve’s presence and implications for Lebanon’s financial development and renewable energy consumption. The econometric model used annual data from the World Development Indicators. Utilizing the autoregressive distributed lag (ARDL) technique, both near- and long-term relationships were estimated. The findings support the Environmental Kuznets Curve hypothesis and show that energy consumption and real income have a statistically significant beneficial effect on carbon emissions and that their square has a statistically significant negative impact on carbon emissions over the long and short term. The results show variations in signs for financial development between the short and long term and stable results for renewable energy with negative signs in both terms. These results show the importance of further research on the influence of financial development and green energy consumption on EKC. Therefore, policymakers need to pay more attention to these variables for a sustainable economy that is facing the effects of climate change.

Be-dataHIVE: a base editing database

Base editing is an enhanced gene editing approach that enables the precise transformation of single nucleotides and has the potential to cure rare diseases. The design process of base editors is labour-intensive and outcomes are not easily predictable. For any clinical use, base editing has to be accurate and efficient. Thus, any bystander mutations have to be minimized. In recent years, computational models to predict base editing outcomes have been developed. However, the overall robustness and performance of those models is limited. One way to improve the performance is to train models on a diverse, feature-rich, and large dataset, which does not exist for the base editing field. Hence, we develop BE-dataHIVE, a mySQL database that covers over 460,000 gRNA target combinations. The current version of BE-dataHIVE consists of data from five studies and is enriched with melting temperatures and energy terms. Furthermore, multiple different data structures for machine learning were computed and are directly available. The database can be accessed via our website https://be-datahive.com/ or API and is therefore suitable for practitioners and machine learning researchers.

Fixed-Magnetization Ising Model with a Slowly Varying Magnetic Field

The motivation for this paper is the analysis of the fixed-density Ising lattice gas in the presence of a gravitational field. This is seen as a particular instance of an Ising model with a slowly varying magnetic field in the fixed magnetization ensemble. We first characterize the typical magnetization profiles in the regime in which the contribution of the magnetic field competes with the bulk energy term. We then discuss in more detail the particular case of a gravitational field and the arising interfacial phenomena. In particular, we identify the macroscopic profile and propose several conjectures concerning the interface appearing in the phase coexistence regime. The latter are supported by explicit computations in an effective model. Finally, we state some conjectures concerning equilibrium crystal shapes in the presence of a gravitational field, when the latter contributes to the energy only to surface order.

Optimization of Low-Pressure Turbine Blade by Means of Fine Inspection of Loss Production Mechanisms

Abstract In this study, Proper Orthogonal Decomposition (POD) was applied to Large Eddy Simulations (LES) of two high-loaded low-pressure turbine cascades under unsteady inflow conditions to investigate entropy production within different parts of the blade passage. The terms for Turbulent Kinetic Energy (TKE) production, diffusion, and dissipation from the stagnation pressure transport equation were integrated across the computational domain. The POD-based method enables the decomposition of contributions from various coherent flow dynamics to TKE production and dissipation, such as the migration, bowing, tilting, and reorientation of incoming wake filaments, as well as the breakdown of streaky structures in the blade boundary layer and the formation of Von Karman vortices in the blade wake. This approach helps designers identify the dominant POD modes (i.e., turbulent flow structures) responsible for loss generation, understand their dynamics and locate where they primarily act. Using this optimization strategy, a new low-pressure turbine profile was designed. LES calculations on the optimized geometry showed that it is possible to design a higher-loaded profile with a lower global loss coefficient. The new loading distribution, characterized by stronger acceleration in the early part of the blade passage, results in reduced upstream wake migration losses and lower TKE production in the trailing edge wake zone due to early suction side boundary layer transition.

Long-time behaviors of wave equations stabilized by boundary memory damping and friction damping

In this paper, we study the long-time behaviors of wave equations subject to boundary memory damping and friction damping. Different from assumptions that memory kernel is a nonnegative, monotone function in the previous literatures, we assume that the primitive of the memory kernel is a generalized positive definite kernel (abbreviated to GPDK), which may vary sign or oscillate. The key to the problem lies in establishing the connection between memory damping and energy terms. By combining the properties of the positive definite kernel with classical multiplier methods, and constructing auxiliary systems, we ultimately establish the asymptotic stability, exponential stability and polynomial stability of systems featuring boundary memory damping and friction damping. To illustrate our theoretical results, we provide some numerical simulations.