Energy Function Research Articles

On fundamental inconsistencies in a commonly used modification of a fluid model for glow discharge

This work considers the fundamental contradictions in the concept of one of the most well-known and widely used modifications of the fluid model for simulation of a glow discharge (GD), the ‘local mean energy approximation’ (LMEA). In this model, it is proposed to determine the kinetic coefficients in the electron particle and energy balance equations as functions of the electron mean energy (temperature) rather than local electric field, using a one-to-one correspondence between these parameters through the electron Boltzmann equation. It is shown that the scope of applicability of this model, like any other modification of the fluid model, is limited by the local mode of formation of the electron energy distribution function (EEDF). Therefore, as demonstrated by the examples of typical 1D and 2D problems for a GD in argon, its extension to the region of nonlocal EEDF is in no way justified and leads not only to serious errors in the results, but also to a logically intractable situation in attempts to apply the main postulate of the LMEA model to the region of a weak (or even reverse) electric field in a negative glow plasma. At the same time, the apparent reliability of calculations within the framework of the LMEA model for a number of parameters, in our opinion, only slows down progress in modeling of gas discharge plasma.

Pyrolysis kinetic analysis and model constructions of different ranks of coal and validation by GA–BP neural networks

In the current steel industry, environmental pressures are mounting. If the reducing gases generated from coal pyrolysis can be utilized for reducing iron ore, the goal of low-carbon production with controllable costs can be achieved. However, the release of volatile content in coal has a significant impact on the pyrolysis process and final products. Therefore, in this study, the pyrolysis characteristics and gaseous products of four types of coal with different volatile matter content was investigated by thermogravimetry-mass spectrometry (TG-MS) technology. The results showed that coals with higher volatile matter content demonstrated stronger reactivity during pyrolysis. As the volatile matter content in coal increased, the starting temperature for releasing the reducing gases decreased, leading to a significant increase in the released gas volume. In addition, the three kinetic factors were calculated by isoconversional method, distribution of the activation energy model (DAEM) and Coats-Redfern (CR) method respectively, and the pyrolysis reaction mechanism function suitable for all coal types was reconstructed based on common solid reaction models. Finally, a predictive model based on a GA-improved back-propagation neural network (BPNN) was developed, which useing 21 input parameters to predict the TG curves, activation energy (E), lnA and mechanism function (fα) and achieving R2 values above 0.95. This study contributes to a comprehensive understanding of the pyrolysis mechanism of coals with different volatile matter content, providing scientific guidance for effective utilization.

Box2Mask: Box-Supervised Instance Segmentation via Level-Set Evolution.

In contrast to fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of simple box annotations, which has recently attracted increasing research attention. This paper presents a novel single-shot instance segmentation approach, namely Box2Mask, which integrates the classical level-set evolution model into deep neural network learning to achieve accurate mask prediction with only bounding box supervision. Specifically, both the input image and its deep features are employed to evolve the level-set curves implicitly, and a local consistency module based on a pixel affinity kernel is used to mine the local context and spatial relations. Two types of single-stage frameworks, i.e., CNN-based and transformer-based frameworks, are developed to empower the level-set evolution for box-supervised instance segmentation, and each framework consists of three essential components: instance-aware decoder, box-level matching assignment and level-set evolution. By minimizing the level-set energy function, the mask map of each instance can be iteratively optimized within its bounding box annotation. The experimental results on five challenging testbeds, covering general scenes, remote sensing, medical and scene text images, demonstrate the outstanding performance of our proposed Box2Mask approach for box-supervised instance segmentation. In particular, with the Swin-Transformer large backbone, our Box2Mask obtains 42.4% mask AP on COCO, which is on par with the recently developed fully mask-supervised methods.

A semi-analytical spectral element model for guided wave propagation in composite laminated conical shells

The conical shell is a typical non-uniform waveguide with its circumferential radius varies linearly. This work aims to provide physical insights for the composite laminated conical shell in terms of waves. A semi-analytical spectral element model is presented, which adopts the Fourier series in the circumferential direction and the higher-order shape functions in the axial direction. The first-order shear deformation theory and Hamilton principle are employed to derive the energy functions of the conical shell, and they are discretized using the spectral elements to achieve a weak-form variational problem. The dispersion equation and the group velocity expression are derived via the piecewise approximation concept and Bloch's periodic theorem. The accuracy of the developed spectral element is verified by comparison with published results. The deformation evolution mechanisms of the composite conical shell are revealed, and the wave propagation characteristics of uniform and ply drop-off composite conical shells are investigated. The results demonstrated that wavenumber distribution at 0-5kHz is spatially dependent, and wavenumber becomes cut off and bifurcate near the cone vertex. When the frequency exceeds 2kHz, the deformation of conical shell changes from rigid to flexible, and the structure tends to be a uniform waveguide. Compared to the geometric curvature effect, the asymmetric lay-up leads to more significant mode coupling.

Legendre–Ritz solutions for vibration characteristics of three-dimensional double-layer lattice truss sandwich plates

In this paper, Legendre–Ritz solutions for vibration characteristics of double-layer lattice truss sandwich plates are proposed based on three-dimensional (3-D) elasticity theory. Double-layer lattice truss sandwich plates consist of three face sheets and two cores. The face sheets are composed of fiber-reinforced composites and the cores are composed of pyramidal lattice trusses made of isotropic materials. The pyramidal lattice core is equated to a homogeneous plate according to equivalence principle. Based on 3-D elasticity theory and pseudo excitation method (PEM), each layer's energy expressions of double-layer lattice truss sandwich plates are constructed. After that, Legendre polynomials are adopted to describe displacement components in length, width and thickness directions. On this basis, the Rayleigh-Ritz method is used to solve energy functions to obtain motion equations of double-layer lattice truss sandwich plates. The accuracy and validity of the present method are corroborated by comparisons with references and finite element method (FEM). Additionally, in order to find out effects of relevant parameters on dynamical characteristics of double-layer lattice truss sandwich plates, parametric studies are carried out by means of some numerical examples.

Non-linear analysis of anisotropic coated fabric utilizing Variational Asymptotic Method

The dimensional reduction of a hyperelastic coated fabric from 3D to 2D is accomplished asymptotically using the Variational Asymptotic Method (VAM). This method integrates constrained calculus of variations and asymptotics. The VAM bifurcates the analysis into two: a 1D through-the-thickness analysis and a 2D reference surface analysis. The 1D analysis leads to the derivation of an asymptotically correct 3D warping functions and a 2D non-linear constitutive law. The 2D non-linear reference surface analysis utilizes the derived 2D non-linear constitutive law to obtain 2D displacements and strains through the 2D non-linear FEA. The classification of 3D strain energy density into distinct orders is enabled by introducing two intrinsic small parameters: 1) a geometric small parameter denoted by the ratio of thickness to characteristic length (h/l≪1), and 2) a physical small parameter that ensures the largest component of 3D strain is restricted to 20 percent, which is less than 1. The model takes into account both geometric and material nonlinearities. The strain energy function, which describes the anisotropic characteristics of the coated fabric has contributions from the strain energies of fiber, matrix, and fiber-fiber interaction. The findings of the study include analytically derived 3D warping functions, a 2D nonlinear constitutive law, and the prediction of warp and weft stresses and strain for a biaxial loaded tensile specimen. These findings align with the experimental outcomes.

A discrete-to-continuum model for the human cornea with application to keratoconus.

We introduce a discrete mathematical model for the mechanical behaviour of a planar slice of human corneal tissue, in equilibrium under the action of physiological intraocular pressure (IOP). The model considers a regular (two-dimensional) network of structural elements mimicking a discrete number of parallel collagen lamellae connected by proteoglycan-based chemical bonds (crosslinks). Since the thickness of each collagen lamella is small compared to the overall corneal thickness, we upscale the discrete force balance into a continuum system of partial differential equations and deduce the corresponding macroscopic stress tensor and strain energy function for the micro-structured corneal tissue. We demonstrate that, for physiological values of the IOP, the predictions of the discrete model converge to those of the continuum model. We use the continuum model to simulate the progression of the degenerative disease known as keratoconus, characterized by a localized bulging of the corneal shell. We assign a spatial distribution of damage (i.e. reduction of the stiffness) to the mechanical properties of the structural elements and predict the resulting macroscopic shape of the cornea, showing that a large reduction in the element stiffness results in substantial corneal thinning and a significant increase in the curvature of both the anterior and posterior surfaces.

Graph-neural-network potential energy surface to speed up Monte Carlo simulations of water cluster anions

Regression of potential energy functions stands as one of the most prevalent applications of machine learning in the realm of materials simulation, offering the prospect of accelerating simulations by several orders of magnitude. Recently, graph-based architectures have emerged as particularly adept for modeling molecular systems. However, the development of robust and transferable potentials, leading to stable simulations for different sizes and physical conditions, remains an ongoing area of investigation. In this study, we compare the performance of several graph neural networks for predicting the energy of water cluster anions, a system of fundamental interest in Chemistry and Biology. Following the identification of the graph attention network as the optimal aggregation procedure for this task, we obtained an efficient and accurate energy model. This model is then employed to conduct Monte Carlo simulations of clusters across different sizes, demonstrating stable behavior. Notably, the predicted surface-to-interior state transition point and the bulk energy of the system are consistent with findings from other investigations, at a computational cost three-orders of magnitude lower.

A multiaxial multiscale compressive thermo-mechanical damage model for Fiber Reinforced Cementitious Composites (FRCC)

In the current study, a multiaxial multiscale compressive stress-strain model for Fiber Reinforced Cementitious Composites (FRCC) was innovatively developed. The proposed model was on the basis of the theory of thermodynamics, multiscale theory and internal variable theory. The free energy function and dissipation function were established to characterize the elastic and plastic deformation of FRCC, respectively. The multiscale behaviors of FRCC in meso-scale and macro-scale was taken into account. In meso-scale, the energy dissipation functions of fiber in tension and bond-slip deformation in the interface transition zone (ITZ) were established. The resistance to cracking of cementitious matrix through the fiber bond stress were taken into account. In macro-scale, the thermo-mechanical coupling contributions of plastic damage, thermal damage, yield surface and hardening evolution were creatively considered in the potential function within thermodynamics framework. The influence of types and volume fractions of fibers on the reinforcement mechanism was discussed. When the temperature is higher than the melting point of fiber, the fiber influence coefficients was employed. The sensitivity of yield surface was discussed. The numerical predictions of this developed model were carried out for validation. The nonlinear stress-strain responses of concrete were accurately captured at temperatures ranges from 20 °C to 800 °C compared with the experimental data, which indicates the accuracy and applicability of the proposed model.

A rational multiscale nonlinear constitutive model for freeze–thaw rocks under triaxial compression

The stability and durability of rocks in cold regions are significantly impacted by the degradation of mechanical properties caused by freeze–thaw (F–T) environment. In this work, we shall propose a rational multiscale nonlinear constitutive model based on thermodynamics, micromechanics, and fractional calculus theory to describe the complete deformation and failure process of F–T rocks under triaxial compression. The F–T rocks at the mesoscale are regarded as consisting of porous matrix and cracks, while porous matrix is composed of the micropores and elastic solid grains at the microscale. According to experimental observations, we assume the F–T action mainly causes micropores growth and cracks opening, and mechanical damage is resulted from the initiation and propagation of cracks. In this context, the effects of F–T and mechanical damage on effective elastic properties of rocks can be quantitatively analyzed by using the two-step Mori–Tanaka (M-T) homogenization method. After subtly deriving the total free energy function of F–T rocks under compression, we systematically develop specific criteria for describing open cracks closure deformation, mechanical damage evolution and frictional sliding induced plastic distortion. Note that to correctly capture the plastic deformation characteristics, the non-orthogonal flow rule based on fractional differential calculations is employed. Following that, analytical analyses and numerical implementation of the proposed model are conducted. The performance of the model is evaluated by the simulations with experimental data on two kinds of F–T rocks, and discussions on parameters sensitivity and effects of fractional order are followed.

Dynamic analysis of extensible beam with multiple cracks

We present the governing equation and study vibrations of multiple crack beams undergoing large deflections subject to transverse loads. First, the primary motion equation is derived using Hamilton’s principle applied to energy functions accounting for cracks. Then we derive a normalized equation governing the vibration of the extensible cracked beam. Single and multiple crack beam examples are considered and analyzed numerically to verify the validity of the derived equations. We propose a modified cracked extensible beam model accounting for the axial force by considering the reduced cross-sectional area. It is expressed by a new reduction parameter. Using the proposed model, we numerically investigate how the cracked extensible beam’s natural frequencies change depending on various model parameters.

A novel active contour model based on features for image segmentation

Active contour model is an extraordinarily valuable technique in image segmentation, which is essential for image analysis and understanding. Active contour model has been widely studied because it delineates closed and smooth contours or surfaces of target objects. However, traditional active contour models underperform on complex natural images. To tackle this problem, we propose a novel active contour model framework, called FeaACM. We introduce the feature energy function into the conventional energy functional to minimize the energy functional to maintain the consistency of the object region and account for different distributions of objects and backgrounds in the feature space. To demonstrate the advantages of our method, we compare our method with the state-of-the-art methods, and show that our method achieves competitive performance. In addition, we utilize AutoEncoder technology to extract the feature of the image verifying the generality of our framework. Extensive and numerous experiments indicate that our method can segment complex natural images effectively. Our code is available at https://github.com/xuepeng1234/FeaACM.

Intraband Cooling and Auger Recombination in Weakly to Strongly Quantum-Confined CsPbBr3 Perovskite Nanocrystals.

Semiconductor nanocrystals (NCs) with size-tuned energy gaps present unique and desirable properties for optoelectronic applications. Recent synthetic advancements offer routes to spheroidal CsPbBr3 perovskite NCs in the strong quantum confinement regime with narrow size dispersion. Using tunable femtosecond laser pulses, we examine intraband carrier relaxation using transient absorption spectroscopy and show that, across the transition from weak to strong confinement, hot carrier lifetime increases compared to larger bulk-like particles. However, further increases of confinement subsequently lead to a reduction of the hot carrier lifetime and increase of the non-radiative Auger recombination rate. Finally, we show that hot carrier lifetimes increase as a function of excess energy above the band gap less sensitively under high confinement in comparison to the bulk. Understanding such unique trends is important for maximizing hot carrier lifetimes for use in next-generation hot carrier devices as well as evaluating the transition from weak to strong confinement.

Dynamical Analysis of A New Memristive Map with Offset Boosting and Extreme Multistability

Abstract In this paper, a chaotic circuit is designed based on a charge-controlled memristor, and the Hamilton energy function is obtained from the Helmholtz theorem. The system equation was discretized by redefining the variables to obtain a three-dimensional memristive map and the corresponding energy function. Then, the effects of parameters and initial values on the memristive map are analyzed using conventional dynamical analysis. There are multiple types of quasi-periodic and chaotic states of the memristive map under different parameters, and the energy evolution of different states is shown. In addition, offset boosting and homogeneous extreme multistability are found in the map, which can be controlled to offset the attractor by changing specific parameters and initial values. The complexity of the chaotic sequence is also analyzed as the parameters and initial values are varied over the chosen range. Finally, the map is implemented on PSIM circuit simulation and DSP digital circuit respectively. This research will provide a reference for secure communication.

Fractional differentiation-based variational level set model for noisy image segmentation without contour initialization

Abstract Noisy image segmentation is a hot topic in image analysis. In this paper, we present a novel methodology for tackling this issue through the integration of fractional differentiation in the frequency domain with a variational level set model (VLSM), which eliminates user-selected initial contours by incorporating the convex energy function. Additionally, the fractional differentiation reduces noises while preserving more detail information. Experiments on synthetic and real noisy images demonstrate that our proposed model surpasses other denoising VLSMs in terms of noise reduction, segmentation accuracy, and efficiency.

Dynamic Properties of Coupled Nonlinear Split-Ring Resonators

In this paper, we delve into the dynamics of two and three coupled SRRs models, exploring their nonlinear properties such as stability, periodicity, or chaos. Additionally, we examine the energy function Hamilton within the context of these models. Numerical examples are provided to illustrate the obtained results and demonstrate the applicability of our findings.

Motion segmentation with event camera: [formula omitted]-patches optical flow estimation and Pairwise Markov Random Fields

This paper proposes the N-patches optical flow estimation-based motion compensation for motion segmentation using event camera. The requirement for prior knowledge of the scenario to cluster events into different motion types is addressed by the N-patches optical flow estimation. The framework of motion segmentation combines motion compensation and Pairwise Markov Random Fields, which not only realize the alignment of events in space but also enhance the spatial correlation between events. The proposed approach aims to maximize the contrast of the images of warped events. It does so by minimizing a specially designed energy function that jointly estimates motion parameters and discrete label items. The problem of selecting the optimal value for N∗ when executing N-patches optical flow estimation is discussed in Section 4.2 of the experiments. Finally, the proposed approach is evaluated in several scenes involving high-speed motion, low-light conditions, occlusions, and multiple moving objects. The experimental results show that the proposed approach achieves better segmentation performance than the event-based motion segmentation by motion compensation.

A new "gold standard": Perturbative triples corrections in unitary coupled cluster theory and prospects for quantum computing.

A major difficulty in quantum simulation is the adequate treatment of a large collection of entangled particles, synonymous with electron correlation in electronic structure theory, with coupled cluster (CC) theory being the leading framework for dealing with this problem. Augmenting computationally affordable low-rank approximations in CC theory with a perturbative account of higher-rank excitations is a tractable and effective way of accounting for the missing electron correlation in those approximations. This is perhaps best exemplified by the "gold standard" CCSD(T) method, which bolsters the baseline CCSD with the effects of triple excitations using considerations from many-body perturbation theory (MBPT). Despite this established success, such a synergy between MBPT and the unitary analog of CC theory (UCC) has not been explored. In this work, we propose a similar approach wherein converged UCCSD amplitudes are leveraged to evaluate energy corrections associated with triple excitations, leading to the UCCSD[T] method. In terms of quantum computing, this correction represents an entirely classical post-processing step that improves the energy estimate by accounting for triple excitation effects without necessitating new quantum algorithm developments or increasing demand for quantum resources. The rationale behind this choice is shown to be rigorous by studying the properties of finite-order UCC energy functionals, and our efforts do not support the addition of the fifth-order contributions as in the (T) correction. We assess the performance of these approaches on a collection of small molecules and demonstrate the benefits of harnessing the inherent synergy between MBPT and UCC theories.

Evidence of multifunctional properties of ferromanganite La0.5Ca0.5Mn0.5Fe0.5O3

Synthesis and characterization of the magnetic and electrical properties of the perovskite-type ferro-magnetite La0.5Ca0.5Mn0.5Fe0.5O3 are reported. Structural analysis reveals crystallization of the material in an orthorhombic structure, space group Pbnm (#62). The optical response suggests semiconductor-type behavior with bandgap Eg=2.3 eV. Susceptibility curves as a function of temperature and magnetization as a function of applied field suggest a soft ferromagnetic type response below room temperature, with evidence of disorder characterized by magnetic irreversibility at low temperatures and low applied fields. Resistivity measurements as a function of temperature and corroborate the semiconductor nature of the material and hysteretic I-V curves enhance its applicability in programmable logic memory devices. Band structure calculations around the Fermi level result in two different band gap values for the two spin up and spin down polarizations, as expected in ferromagnetic semiconductor materials. The hybridizations observed in the density of states curves as a function of energy suggest that the ferromagnetic character is due to double exchange mechanisms, coexisting with antiferromagnetic super-exchange, which is essentially due to the disorder of Fe3+ and Mn4+ cations in the octahedra along the three crystallographic axes.

A comparative study of analytical representations of potential energy curves for CO in its ground electronic state

AbstractIn this work, a comparative study of four functional forms used to represent potential energy curves (PECs) is presented. The starting point is the Hulburt‐Hirschfelder, followed by the Extended Rydberg potential function, ending with two of the most recent potentials presented in the literature for diatomic systems: the Araújo‐Ballester potential and the Improved Extended Lennard‐Jones potential. The chosen potentials have in common the fact that all their parameters are algebraically calculated, without any fitting procedure, and all of them have direct dependence on Dunham's parameters. The mathematical behavior of these functions for the short‐ and long‐range regions is discussed. As study case, the diatomic system in its ground electronic state was selected. To quantify the accuracy of the potential energy functions, the least‐squares Z‐test method, proposed by Murrell and Sorbie, is used. Furthermore, the main spectroscopic constants and vibrational energy levels are calculated and compared for all potentials.