Inter-stage performance and energy characteristics analysis of electric submersible pump based on entropy production theory

The electric submersible pump(ESP) is a crucial apparatus utilized for lifting in the oil extraction process.Its lifting capacity is enhanced by the multi-stage tandem structure, but variations in energy characteristics and internal flow across stages are also introduced. In this study, the inter-stage variability of energy characteristics in ESP hydraulic systems is investigated through entropy production(EP) analysis,which incorporates numerical simulations and experimental validation. The EP theory facilitates the quantification of energy loss in each computational subdomain at all ESP stages, establishing a correlation between microscopic flow structure and energy dissipation within the system. Furthermore, the underlying causes of inter-stage variability in ESP hydraulic systems are examined, and the advantages and disadvantages of applying the EP theory in this context are evaluated. Consistent energy characteristics within the ESP, aligned with the distribution of internal flow structure, are provided by the EP theory, as demonstrated by our results. The EP theory also enables the quantitative analysis of internal flow losses and complements existing performance analysis methods to map the internal flow structure to hydraulic losses. Nonetheless, an inconsistency between the energy characterization based on EP theory and the traditional efficiency index when reflecting inter-stage differences is identified. This inconsistency arises from the exclusive focus of the EP theory on flow losses within the flow field, disregarding the quantification of external energy input to the flow field. This study provides a reference for the optimization of EP theory in rotating machinery while deeply investigating the energy dissipation characteristics of multistage hydraulic system, which has certain theoretical and practical significance.

The Correlation between the Power Quality Indicators and Entropy Production Characteristics of Wind Power+Energy Storage Systems

Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems.The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system,and to explore the correlation between systementropy generation and various indicators,so as to provide a theoretical basis for directly improving power quality by reducing loss.A steady-state experiment was performed by replacing the wind wheel with an electric motor,and the output power qualities of the wind power systemwith andwithout energy storagewere compared and analyzed.Moreover,the improvement effect of different energy storage devices on various indicatorswas obtained.Then,based on the entropy theory,the loss of the internal components of the wind power system generator is simulated and explored by Ansys software.Through the analysis of power quality evaluation indicators,such as current harmonic distortion rate,frequency deviation rate,and voltage fluctuation,the correlation between entropy production and each evaluation indicator was explored to investigate effective methods to improve power quality by reducing entropy production.The results showed that the current harmonic distortion rate,voltage fluctuation,voltage deviation,and system entropy production are positively correlated in the tests and that the power factor is negatively correlated with system entropy production.In the frequency range,the frequency deviationwas not significantly correlated with the systementropy production.

Enhanced Deep Reinforcement Learning Strategy for Energy Management in Plug-in Hybrid Electric Vehicles with Entropy Regularization and Prioritized Experience Replay

Plug-in Hybrid Electric Vehicles(PHEVs)represent an innovative breed of transportation,harnessing diverse power sources for enhanced performance.Energy management strategies(EMSs)that coordinate and control different energy sources is a critical component of PHEV control technology,directly impacting overall vehicle performance.This study proposes an improved deep reinforcement learning(DRL)-based EMSthat optimizes realtime energy allocation and coordinates the operation of multiple power sources.Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces.They often fail to strike an optimal balance between exploration and exploitation,and their assumption of a static environment limits their ability to adapt to changing conditions.Moreover,these algorithms suffer from low sample efficiency.Collectively,these factors contribute to convergence difficulties,low learning efficiency,and instability.To address these challenges,the Deep Deterministic Policy Gradient(DDPG)algorithm is enhanced using entropy regularization and a summation tree-based Prioritized Experience Replay(PER)method,aiming to improve exploration performance and learning efficiency from experience samples.Additionally,the correspondingMarkovDecision Process(MDP)is established.Finally,an EMSbased on the improvedDRLmodel is presented.Comparative simulation experiments are conducted against rule-based,optimization-based,andDRL-based EMSs.The proposed strategy exhibitsminimal deviation fromthe optimal solution obtained by the dynamic programming(DP)strategy that requires global information.In the typical driving scenarios based onWorld Light Vehicle Test Cycle(WLTC)and New European Driving Cycle(NEDC),the proposed method achieved a fuel consumption of 2698.65 g and an Equivalent Fuel Consumption(EFC)of 2696.77 g.Compared to the DP strategy baseline,the proposed method improved the fuel efficiency variances(FEV)by 18.13%,15.1%,and 8.37%over the Deep QNetwork(DQN),Double DRL(DDRL),and original DDPG methods,respectively.The observational outcomes demonstrate that the proposed EMS based on improved DRL framework possesses good real-time performance,stability,and reliability,effectively optimizing vehicle economy and fuel consumption.

Standard-state entropies and their impact on the potential-dependent apparent activation energy in electrocatalysis

The apparent activation energy,Eapp,is a common measure in thermal catalysis to discuss the activity and limiting steps of catalytic processes on solid-state materials.Recently,the electrocatalysis community adopted the concept of Eappand combined it with the Butler-Volmer theory.Certain observations though,such as potential-dependent fluctuations of Eapp,are yet surprising because they conflict with the proposed linear decrease in Eappwith increasing overpotential.The most common explanation for this finding refers to coverage changes upon alterations in the temperature or the applied electrode potential.In the present contribution,it is demonstrated that the modulation of surface coverages cannot entirely explain potential-dependent oscillations of Eapp,and rather the impact of entropic contributions of the transition states has been overlooked so far.In the case of a nearly constant surface coverage,these entropic contributions can be extracted by a dedicated combination of Tafel plots and temperature-dependent experiments.

Adaptive Short-Time Fractional Fourier Transform Based on Minimum Information Entropy

Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order to overcome the shortcomings,the STFrFT method with adaptive window function is proposed.In this method,the window function of STFrFT is ad-aptively adjusted by establishing a library containing multiple window functions and taking the minimum information entropy as the criterion,so as to obtain a time-frequency distribution that better matches the desired signal.This method takes into account the time-frequency resolution characteristics of STFrFT and the excellent characteristics of adaptive adjustment to window func-tion,improves the time-frequency aggregation on the basis of eliminating cross term interference,and provides a new tool for improving the time-frequency analysis ability of complex modulated sig-nals.

Relationship between Energy of Motion and D-Entropy in the Physics of Evolution

The purpose of the paper is to substantiate the possibility of constructing the physics of the evolution of matter based on the fundamental laws of physics. It is shown how this can be done within the framework of an extension of classical mechanics. Its expansion is based on the motion equation of a structured body. The fundamental difference between this equation and Newton’s motion equation is that instead of a model of a body in the form of a material point, it uses a structured body in the form of a system of potentially interacting material points. To obtain this equation, the principle of symmetry dualism, new for classical mechanics, was used. According to this principle, the dynamics of a body are determined not only by the symmetries of space, as in the case of a structureless body, but also by its symmetries. Thanks to this derivation of the equation, it takes into account the fact that the work of external forces, in addition to changing the body’s motion energy, also changes its internal energy. This change occurs due to the body’s motion energy when it moves in a non-uniform field of forces. It is shown why the motion equation of a structured body is irreversible. Its irreversibility made it possible to introduce the concept of D-entropy into extended classical mechanics. It is defined as the value of the relative increase in the body’s internal energy due to the motion energy. The relationship between the values of motion energy and D-entropy in the process of matter evolution is considered. It is shown how this connection is realized during the transition from one hierarchical level of matter to the next level. As a result, it was possible to prove that the evolution of the hierarchical structure of matter is characterized by the relationship between D-entropy and the motion energy of elements at each of its hierarchical levels.

Equilibrium Energy and Entropy of Vortex Filaments in the Context of Tornadogenesis and Tornadic Flows

In this work, we study approximations of supercritical or suction vortices in tornadic flows and their contribution to tornadogenesis and tornado maintenance using self-avoiding walks on a cubic lattice. We extend the previous work on turbulence by A. Chorin and collaborators to approximate the statistical equilibrium quantities of vortex filaments on a cubic lattice when both an energy and a statistical temperature are involved. Our results confirm that supercritical (smooth, “straight”) vortices have the highest average energy and correspond to negative temperatures in this model. The lowest-energy configurations are folded up and “balled up” to a great extent. The results support A. Chorin’s findings that, in the context of supercritical vortices in a tornadic flow, when such high-energy vortices stretch, they need to fold and transfer energy to the surrounding flow, contributing to tornado maintenance or leading to its genesis. The computations are performed using a Markov Chain Monte Carlo approach with a simple sampling algorithm using local transformations that allow the results to be reliable over a wide range of statistical temperatures, unlike the originally used pivot algorithm that only performs well near infinite temperatures. Efficient ways to compute entropy are discussed and show that a system with supercritical vortices will increase entropy by having these vortices fold and transfer their energy to the surrounding flow.

Energy Management

A new revised energy concept is proposed from relativistic approach using different kinds of spaces.It is not always feasible to implement a project for saving energy.It is not merely heating a stream and cooling another stream.The study includes other considerations.A total feasibility study should be performed.The cost and the income should be calculated.In this study it is shown how to perform such a feasibility study from scratch up to detailed implementation.It is an investment approach.There are two energy balances:one thermal and the other mechanical.They are not separated but they complete each other.The decision is upon rigorous energy balance.First the question where the energy will go shall be answered from 2nd law of thermodynamics.

Energy Entropy On-Demand Multipath Routing Protocol for Mobile Ad Hoc Networks

This paper provides a critical review of energy entropy theory in Mobile Ad Hoc Networks (MANETs) and proposes an Energy Entropy on Ad Hoc On-demand Distance Vector Multipath (EEAODVM) routing protocol. The essential idea of the protocol is to find every route which can minimize the node residual energy in the process of selecting path. It balances individual node battery energy utilization and hence prolongs the entire network lifetime. The results of simulation show that, with the proposed EEAODVM routing protocol, packet delivery ratio, routing overhead ratio, average end-to-end delay, network's lifetime and minimal residual energy ratio can be improved in most of cases. It is an available approach for multipath routing decision.

Superior corrosion resistance-dependent laser energy density in(CoCrFeNi)95Nb5 high entropy alloy coating fabricated by laser cladding

(CoCrFeNi)95Nb5 high entropy alloy(HEA)coatings were successfully fabricated on a substrate of Q235 steel by laser cladding technology.These(CoCrFeNi)95Nb5 HEA coatings possess excellent properties,particularly corrosion resistance,which is clearly superior to that of some typical bulk HEA and common engineering alloys.In order to obtain appropriate laser cladding preparation process parameters,the effects of laser energy density on the microstructure,microhardness,and corrosion resistance of(CoCrFeNi)95Nb5 HEA coating were closely studied.Results showed that as the laser energy density increases,precipitation of the Laves phase in(CoCrFeNi)95Nb5 HEA coating gradually decreases,and diffusion of the Fe element in the substrate intensifies,affecting the integrity of the(CoCrFeNi)95Nb5 HEA.This decreases the microhardness of(CoCrFeNi)95Nb5 HEA coatings.Moreover,the relative content of Cr2O3,Cr(OH)3,and Nb2O5 in the surface passive film of the coating decreases with increasing energy density,causing corrosion resistance to decrease.This study demonstrates the controllability of a high-performance HEA coating using laser cladding technology,which has significance for the laser cladding preparation of other CoCrFeNi-system HEA coatings.

Alcoholism Detection by Wavelet Energy Entropy and Linear Regression Classifier

Alcoholism is an unhealthy lifestyle associated with alcohol dependence.Not only does drinking for a long time leads to poor mental health and loss of self-control,but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs.Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health.As their drinking increases,they become dependent on alcohol and it affects their daily lives.Therefore,it is important to recognize the dangers of alcohol abuse and to stop drinking as soon as possible.To assist physicians in the diagnosis of patients with alcoholism,we provide a novel alcohol detection system by extracting image features of wavelet energy entropy from magnetic resonance imaging(MRI)combined with a linear regression classifier.Compared with the latest method,the 10-fold cross-validation experiment showed excellent results,including sensitivity 91.54±1.47%,specificity 93.66±1.34%,Precision 93.45±1.27%,accuracy 92.61±0.81%,F1 score 92.48±0.83%and MCC 85.26±1.62%.

Droplets diameter distribution using maximum entropy formulation combined with a new energy-based sub-model

The maximum entropy principle(MEP) is one of the first methods which have been used to predict droplet size and velocity distributions of liquid sprays. This method needs a mean droplets diameter as an input to predict the droplet size distribution. This paper presents a new sub-model based on the deterministic aspects of liquid atomization process independent of the experimental data to provide the mean droplets diameter for using in the maximum entropy formulation(MEF). For this purpose, a theoretical model based on the approach of energy conservation law entitled energy-based model(EBM) is presented. Based on this approach, atomization occurs due to the kinetic energy loss. Prediction of the combined model(MEF/EBM) is in good agreement with the available experimental data. The energy-based model can be used as a fast and reliable enough model to obtain a good estimation of the mean droplets diameter of a spray and the combined model(MEF/EBM) can be used to well predict the droplet size distribution at the primary breakup.

Re-examination of Fundamental Concepts of Heat, Work, Energy, Entropy, and Information Based on NGST

In order to use the framework of general system theory(GST)to unify the three mechanics subjects of classical mechanics,quantum mechanics,and relativistic mechanics,a new general system theory(NGST)is developed based on a new ontology of ether and minds as the fundamental existences in the world.Based on this new ontology,many fundamental concepts have been detected to be ambiguously defined nowadays and particularly lack of ontological support.In our previous work,some of the fundamental concepts such as universe,world,time,space,matter,ether,mind,life,field,force have been redefined.The purpose of this paper is to clarify the concepts of energy,heat,work,entropy,and information in our NGST.This is an important and necessary step in the development of the NGST.

Lattice Boltzmann simulation for the energy and entropy of excitable systems

The internal energy and the spatiotemporal entropy of excitable systems are investigated with the lattice Boltzmann method. The numerical results show that the breakup of spiral wave is attributed to the inadequate supply of energy, i.e., the internal energy of system is smaller than the energy of self-sustained spiral wave. It is observed that the average internal energy of a regular wave state reduces with its spatiotemporal entropy decreasing. Interestingly, although the energy difference between two regular wave states is very small, the different states can be distinguished obviously due to the large difference between their spatiotemporal entropies. In addition, when the unstable spiral wave converts into the spatiotemporal chaos, the internal energy of system decreases, while the spatiotemporal entropy increases, which behaves as the thermodynamic entropy in an isolated system.

CALCULATION OF CONFORMATIONAL ENTROPY AND FREE ENERGY OF POLYSILANE CHAIN

The conformational entropy S and free energy F were calculated by exact enumeration of polysilane chain up to 23 segments with excluded volume (EV) and long-range van der Waals (VW) interaction. A nonlinear relation between SEV+VW and chain length n was found though S-EV was found to vary linearly with n. We found that the second-order transition temperature of polysilane chain with VW interaction increases with the increase of chain length, while that of polysilane chain without VW interaction is chain length independent. Moreover, the free energies FEV+VW and F-EV are both linearly related with n, and FEV+VW < F-EV for all temperatures.

Ground-State Energy and Entropy for One-Dimensional Heisenberg Chain with Alternating D-Term

We study the ground-state information of one-dimensional Heisenberg chain with alternating D-term. Given the ground-state phase diagram, the ground-state energy and the entanglement entropy are obtained by tensor-net work algorithm. The phase transition points are shown in the entanglement entropy figure. The results are agreed with the phase diagram.

A New Energy-Efficient and Reliable Protocol for Stochastic WSNs Based on Back-Pressure and Entropy of Residual Energy

In this paper, a new energy-efficient and reliable routing protocol is introduced for WSNs including a stochastic traffic generation model and a wakeup/sleep mechanism. Our objective is to improve the longevity of the WSNs by energy balancing but providing reliable packet transfer to the Base Station at the same time. The proposed protocol is based on the principle of the back-pressure method and besides the difference of backlogs, in order to optimize energy consumption, we use a cost function related to an entropy like function defined over the residual energies of the nodes. In the case of two-hop routing the optimal relay node is selected as the one which has maximum backlog difference and keeps the distribution of residual energy as close to uniform as possible where the uniformity is measured by the change of the entropy of the residual energy of the nodes. The protocol assumes Rayleigh fading model. Simulation results show that the proposed algorithm significantly improves the performance of traditional back-pressure protocol with respect to energy efficiency, E2E delay and throughput, respectively.

Robot’s Emotion Decision by Energy and Entropy Concepts

This study is to introduce concepts of energy and entropy to describe a robot＇s emoton decisien. It chooses the dimensional approach based on factors of pleasure and arousal for the merit of the interpolation between enotions. Especially, Circumplex model which has also two axes： pleasure and arousal is used. Besides, the model indicates how emotions are distributed in the two-dimensional plane. Then by the definition of psychodynamicsthe energy states （mental energy and physical energy） are matched to pleasure and arousal respectively that are the basis of Circumplex model. The mental energy is updated by the result of Prospect theory which measures the value of gain and loss as pleasure factor. And the physical energy is updated by the result of hedonic scaling which measures levels of arousal from pleasure computed by Prospect theory, and the result of intensity of stimuli. Then the energy states are fed by entropy. The feedback loop by entropy satisfies the 2nd law of thermodynamics. The energy states generated by stimuli and fed by entropy take a position in the plane of Circumplex model. Then distances between the current position and other emotions are cornputed to get a level of each emotion, proportional to the inverse of the distance.

Entropy Production and Fractal Dimensions in Heavy Ion Nuclear Reaction at Intermediate Energies

The characteristics of the nonlinear dynamics in the Heavy Ion Collision (HIC) at intermediate energies have been studied by evaluating the productions of the Generalized Entropy (GE) and the Multifragmentation Entropy (ME) as well as the features of the information and fractal dimensions within the Isospin Quantum Molecular Dynamical Model compensated by the lattice methods. Results demonstrate from various views that the existence of deterministic chaos in the dynamical process of reaction.

考虑最小平均包络熵负荷分解的最优Bagging集成超短期多元负荷预测

多元负荷预测技术是保证综合能源系统(integrated energy system,IES)供需平衡与稳定运行的关键基石。但具有强随机性与波动性的IES负荷加剧了超短期多元负荷准确预测的难度。为此,提出考虑最小平均包络熵负荷分解的最优Bagging集成超短期多元负荷预测方法。构建基于最小平均包络熵的变分模态分解参数优化模型,将IES多元负荷分解为本征模态分量集合;基于统一信息系数法筛选多元负荷预测的日历、气象与负荷强相关特征;结合负荷本征模态分量集合、日历规则、气象环境与负荷数据,构建Bagging集成超短期多元负荷预测模型,并建立基于平均绝对百分比误差与决定系数的集成策略优化模型,进而得到最优集成策略与最终预测结果。以美国亚利桑那州立大学坦佩校区IES为对象展开仿真验证,结果表明,所提方法的电、热、冷负荷预测平均绝对百分比误差分别为1.9486%、2.0585%、2.5331%,相比其他预测方法具有更高准确率。