Dynamics and synchronization of neural models with memristive membranes under energy coupling

Dynamical modeling of neural systems plays an important role in explaining and predicting some features of biophysical mechanisms.The electrophysiological environment inside and outside of the nerve cell is different.Due to the continuous and periodical properties of electromagnetic fields in the cell during its operation,electronic components involving two capacitors and a memristor are effective in mimicking these physical features.In this paper,a neural circuit is reconstructed by two capacitors connected by a memristor with periodical mem-conductance.It is found that the memristive neural circuit can present abundant firing patterns without stimulus.The Hamilton energy function is deduced using the Helmholtz theorem.Further,a neuronal network consisting of memristive neurons is proposed by introducing energy coupling.The controllability and flexibility of parameters give the model the ability to describe the dynamics and synchronization behavior of the system.

Estimation of Landfill Gas and Its Renewable Energy Potential from the Polesgo Controlled Landfill Using First-Order Decay (FOD) Models

Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical energy production and potential carbon credits from avoided CH4 emissions) from its proper management in a municipal solid waste landfill located in Ouagadougou, Burkina Faso. The modeling was carried out using two first-order decay (FOD) models (LandGEM V3.02 and SWANA) using parameters evaluated on the basis of the characteristics of the waste admitted to the landfill and weather data for the site. At the same time, production data have been collected since 2016 in order to compare them with the model results. The results obtained from these models were compared to experimental one. For the simulation of methane production, the SWANA model showed better consistency with experimental data, with a coefficient of determination (R²) of 0.59 compared with the LandGEM model, which obtained a coefficient of 0.006. Thus, despite the low correlation values linked to the poor consistency of experimental data, the SWANA model models methane production much better than the LandGEM model. Thus, despite the low correlation values linked to the poor consistency of the experimental data, the SWANA model models methane production much better than the LandGEM V3.02 model. It was noted that the poor consistency of the experimental data justifies these low coefficients, and that they can be improved in the future thanks to ongoing in situ measurements. According to the SWANA model prediction, in 27 years of operation a biogas plant with 33% electrical efficiency using biogas from the Polesgo landfill would avoid 1,340 GgCO2e. Also, the evaluation of revenues due to electricity and carbon credit gave a total revenue derived from methane production of US$27.38 million at a cost of US$10.5/tonne CO2e.

Assessment of rockburst hazard by quantifying the consequence with plastic strain work and released energy in numerical models

Quantifying the rockburst consequence is of critical importance to reduce the hazards with preventative measures in underground mines and deep tunnels. Contours of energy components within a pillar model are plotted at different rockmass damage stages, and plastic strain work and released energy are proposed as indicators of rockmass damage consequence. One pillar model under different loading stiffness is simulated to assess indicators of pillar burst and the resulting damages. The results show the rockmass damage under soft loading stiffness has larger magnitude of plastic strain work and released energy than that which is under stiff loading stiffness, indicating the rockburst consequence can be quantified with plastic strain work and released energy in numerical models. With the quantified rockburst consequence,preventative measures can be taken to avoid severe hazards to mine safety.

Impact of mechanical ventilation control strategies based on non-steady-state and steady-state Wells-Riley models on airborne transmission and building energy consumption

Ventilation is an effective solution for improving indoor air quality and reducing airborne transmission.Buildings need sufficient ventilation to maintain a low infection risk but also need to avoid an excessive ventilation rate,which may lead to high energy consumption.The Wells-Riley(WR)model is widely used to predict infection risk and control the ventilation rate.However,few studies compared the non-steady-state(NSS)and steady-state(SS)WR models that are used for ventilation control.To fill in this research gap,this study investigates the effects of the mechanical ventilation control strategies based on NSS/SS WR models on the required ventilation rates to prevent airborne transmission and related energy consumption.The modified NSS/SS WR models were proposed by considering many parameters that were ignored before,such as the initial quantum concentration.Based on the NSS/SS WR models,two new ventilation control strategies were proposed.A real building in Canada is used as the case study.The results indicate that under a high initial quantum concentration(e.g.,0.3 q/m^(3))and no protective measures,SS WR control underestimates the required ventilation rate.The ventilation energy consumption of NSS control is up to 2.5 times as high as that of the SS control.

A Review of Energy-Related Cost Issues and Prediction Models in Cloud Computing Environments

With the expansion of cloud computing,optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important,since it directly affects providers’revenue and customers’payment.Thus,providing prediction information of the cloud services can be very beneficial for the service providers,as they need to carefully predict their business growths and efficiently manage their resources.To optimize the use of cloud services,predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs.However,such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine(PM)but also at the level of the Virtual Machine(VM)in order to make improved cost decisions.Therefore,this paper presents a comprehensive literature review on the subject of energy-related cost issues and prediction models in cloud computing environments,along with an overall discussion of the closely related works.The outcomes of this research can be used and incorporated by predictive resource management techniques to make improved cost decisions assisted with energy awareness and leverage cloud resources efficiently.

Consistency and Validity of the Mathematical Models and the Solution Methods for BVPs and IVPs Based on Energy Methods and Principle of Virtual Work for Homogeneous Isotropic and Non-Homogeneous Non-Isotropic Solid Continua

Energy methods and the principle of virtual work are commonly used for obtaining solutions of boundary value problems (BVPs) and initial value problems (IVPs) associated with homogeneous, isotropic and non-homogeneous, non-isotropic matter without using (or in the absence of) the mathematical models of the BVPs and the IVPs. These methods are also used for deriving mathematical models for BVPs and IVPs associated with isotropic, homogeneous as well as non-homogeneous, non-isotropic continuous matter. In energy methods when applied to IVPs, one constructs energy functional (I) consisting of kinetic energy, strain energy and the potential energy of loads. The first variation of this energy functional (δI) set to zero is a necessary condition for an extremum of I. In this approach one could use δI = 0 directly in constructing computational processes such as the finite element method or could derive Euler’s equations (differential or partial differential equations) from δI = 0, which is also satisfied by a solution obtained from δI = 0. The Euler’s equations obtained from δI = 0 indeed are the mathematical model associated with the energy functional I. In case of BVPs we follow the same approach except in this case, the energy functional I consists of strain energy and the potential energy of loads. In using the principle of virtual work for BVPs and the IVPs, we can also accomplish the same as described above using energy methods. In this paper we investigate consistency and validity of the mathematical models for isotropic, homogeneous and non-isotropic, non-homogeneous continuous matter for BVPs that are derived using energy functional consisting of strain energy and the potential energy of loads. Similar investigation is also presented for IVPs using energy functional consisting of kinetic energy, strain energy and the potential energy of loads. The computational approaches for BVPs and the IVPs designed using energy functional and principle of virtual work, their consistency and validity are also investigated. Classical continuum mechanics (CCM) principles i.e. conservation and balance laws of CCM with consistent constitutive theories and the elements of calculus of variations are employed in the investigations presented in this paper.

Runtime Energy Savings Based on Machine Learning Models for Multicore Applications

To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to maximize energy savings under a given performance degradation. Machine learning techniques were utilized to develop performance models which would provide accurate performance prediction with change in operating core-uncore frequency. Experiments, performed on a node (28 cores) of a modern computing platform showed significant energy savings of as much as 26% with performance degradation of as low as 5% under the proposed strategy compared with the execution in the unlimited power case.

Power Allocation for Wireless Powered MIMO Transmissions with Non-Linear RF Energy Conversion Models

We study a radio frequency(RF) wireless energy transfer(WET) enabled multiple input multiple output(MIMO) system. A time slotted transmission pattern is considered. Each slot can be divided into two phases, downlink(DL) WET and uplink(UL) wireless information transmission(WIT). Since energy conversion efficiency of the energy harvesting circuits are non.linear, the conventional linear model leads to a mismatch for resource allocation. In this paper, the power allocation algorithm considering the practical non.linear energy harvesting circuits is studied. The optimization problem is formulated to maximize the energy efficiency of system with multiple constraints, i.e., the transmission power, the received power and the minimum harvested energy, which is a non.convex problem. We transform the objective function from fractional form into an equivalent objective function in subtractive form and provide an iterative power allocation algorithm to achieve the optimal solution. Numerical results show that our proposed algorithm with the non.linear RF energy conversion models can achieve much better performance than the algorithm with the conventional linear model.

Review of multi-objective optimization in long-term energy system models

Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multi-objective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multi-objective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed.

Research on Calculation Models of Coal Comminution Energy Consumption

在总结粉碎功耗规律的研究进展的基础上，分析了单一粒度颗粒的粉碎功耗预测理论，介绍了粉碎功耗理论的3种著名假说体积假说、面积假说、裂缝假说及其修正计算方法，并进行了比较，描述了粉碎功耗计算的通用关系式和近年来提出的新机制，包括原生裂纹假说、突变理论及分形理论等；进而针对具有复杂粒度分布物料的粉碎功耗，将给料与产品粒度分布作为参数引入能耗计算中，获得了当粒度分布分别满足G．S分布、R—R分布、分形分布时的各种粉碎功耗理论预测结果。此外，还列出了部分常用的粉碎功耗经验关联式并进行了比较。文中提出在研究煤的粉碎功耗规律时，采用Walker计算式结合分形粒度分布或R-R分布的能耗模型及Morrell经验式是可行的。

A review of uncertain factors and analytic methods in long-term energy system optimization models

A larger number of uncertain factors in energy systems influence their evolution.Owing to the complexity of energy system modeling,incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource allocation.This study focusses on long-term energy system optimization model.The important uncertain parameters in the model are analyzed and divided into policy,economic,and technical factors.This study specifically addresses the challenges related to carbon emission reduction and energy transition.It involves collecting and organizing relevant research on uncertainty analysis of long-term energy systems.Various energy system uncertainty modeling methods and their applications from the literature are summarized in this review.Finally,important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed,and future research directions are proposed.

Thermo-hydro-mechanical (THM) coupled simulation of the land subsidence due to aquifer thermal energy storage (ATES) system in soft soils

Aquifer thermal energy storage(ATES)system has received attention for heating or cooling buildings.However,it is well known that land subsidence becomes a major environmental concern for ATES projects.Yet,the effect of temperature on land subsidence has received practically no attention in the past.This paper presents a thermo-hydro-mechanical(THM)coupled numerical study on an ATES system in Shanghai,China.Four water wells were installed for seasonal heating and cooling of an agriculture greenhouse.The target aquifer at a depth of 74e104.5 m consisted of alternating layers of sand and silty sand and was covered with clay.Groundwater level,temperature,and land subsidence data from 2015 to 2017 were collected using field monitoring instruments.Constrained by data,we constructed a field scale three-dimensional(3D)model using TOUGH(Transport of Unsaturated Groundwater and Heat)and FLAC3D(Fast Lagrangian Analysis of Continua)equipped with a thermo-elastoplastic constitutive model.The effectiveness of the numerical model was validated by field data.The model was used to reproduce groundwater flow,heat transfer,and mechanical responses in porous media over three years and capture the thermo-and pressure-induced land subsidence.The results show that the maximum thermoinduced land subsidence accounts for about 60%of the total subsidence.The thermo-induced subsidence is slightly greater in winter than that in summer,and more pronounced near the cold well area than the hot well area.This study provides some valuable guidelines for controlling land subsidence caused by ATES systems installed in soft soils.

Distribution of Mass and Energy in Five General Cosmic Models

Distributions of the universe horizon distance and universe horizon volume were investigated in the light of five general cosmic models which were constructed in a previous study. Both distributions increase so slowly up to t ≈ 21.5444 Myr, then they start raising very fast up to t ≈ 60 Gyr. Afterwards, they increase again very slowly until t ≈ 124 Gyr. Distributions of mass of radiation, matter and dark energy within the horizon volume of the universe were also studied in the five general cosmic models. The masses of both radiation and matter decrease gradually with time while the mass of dark energy increases. The mass of radiation prevailed in the early universe up to t ≈ 34627.5 - 55916.2 yr, where it becomes equal to the mass of matter. Then the mass of matter dominated until t ≈ 9.4525 - 10.0632 Gyr, where it becomes equal to the mass of dark energy. Thenceforward, the mass of dark energy prevails the universe. The cosmic space becomes approximately matter empty in the so far future of the universe.

Accelerating dark energy models with anisotropic fluid in Bianchi type Ⅵ_0 space-time

Motivated by the increasing evidence for the need of a geometry that re- sembles Bianchi morphology to explain the observed anisotropy in the WMAP data, we have discussed some features of Bianchi type VI0 universes in the presence of a fluid that has an anisotropic equation of state （EoS） parameter in general relativity. We present two accelerating dark energy （DE） models with an anisotropic fluid in Bianchi type VI0 space-time. To ensure a deterministic solution, we choose the scale factor a（t） = √tnet, which yields a time-dependent deceleration parameter, representing a class of models which generate a transition of the universe from the early decelerating phase to the recent accelerating phase. Under suitable conditions, the anisotropic mod- els approach an isotropic scenario. The EoS for DE co is found to be time-dependent and its existing range for derived models is in good agreement with data from recent observations of type Ia supernovae （SNe Ia） （Knop et al. 2003）, SNe Ia data com- bined with cosmic microwave background （CMB） anisotropy and galaxy clustering statistics （Tegmark et al. 2004a）, as well as the latest combination of cosmological datasets coming from CMB anisotropies, luminosity distances of high redshift SNe Ia and galaxy clustering. For different values of n, we can generate a class of physically viable DE models. The cosmological constant A is found to be a positive decreasing function of time and it approaches a small positive value at late time （i.e. the present epoch）, which is corroborated by results from recent SN Ia observations. We also ob- serve that our solutions are stable. The physical and geometric aspects of both models are also discussed in detail.

Techno-Financial Analysis of Energy Access through Hybrid System with Solar PV under the Various Rural Community Models for State of Uttarakhand, India

Uttarakhand state comes under special category state where approximately 69.45% population lived in rural area under the population density with varied range of 37 to 607 persons per sq.km. Although Uttarakhand is having per capita consumption of 1112.29 kWh which is higher than national average per capita consumption of 779 kWh as till date, but remote communities, villages are not able to access clean, cheep and good quality of energy due to uneven terrain, lack of proper transmission & distribution lines [1]. 100% villages are electrified under the RGGVY scheme as per the Ministry of Power Government of India, but due to poor loading of transformer, lack of grid infrastructure and natural calamities, remote house owners are not able to get good quality of power thus affect the livelihood and source of income generation in various means [2]. As Uttarakhand state having future plans to be make state energy sufficient and energy access to all by year 2016-2017, so major ground level initiative have been taken by Government of Uttarakhand. The government of Uttarakhand has incorporated innovative business model to provide good quality of power with non-conventional energy source. Under the initiative invlovement of local people and village level, panchayats have ownership and responsibility to operate these clean energy business model to improve livelihood in remote hilly places of Uttarakhand. Under this analysis, five different type of community models are categorized as Community 1, Community 2, Community 3, Standalone 1 & Standalone 2 for rural &remote communities based on number of unclustered households with the distance covered between 200 m to 20 km, and electrical loads i.e. lighting, fan, mobile chargers, television along with time of day energy consumption patterns. These community models are for remote hilly location where grid integration and distribution lines are not feasible to built due to hilly terrain, low soil strength and huge expenses for expanding power cables for supplying good quality power. The preliminary studies and simulations has been done in HOMER tool by considering the various composite source of power, i.e. Solar PV with battery bank, Solar PV with battery Bank & Generator, and Solar PV along with DG. These three hybrid source of power generation with Solar PV as base source under five different community models, the techno-commercial feasibility has been analyzed in terms of load sharing proposition with Solar PV and battery, DG, Energy production through PV, load consumption per year, Excess and unmet energy monitoring, battery sizing to meet the load during nights, DG operation when the solar energy not available due to weather condition and non availability of sunshine in night. Financial feasibility has been examined in terms of levelized cost of energy, cost summary and O&M cost per year of three integrated sources of energy generation with Solar PV under each community model. Solar PV power plant , which is the best renewable source of energy to cater energy access issue in remote hilly places. The Uttarakhand receives good amout of daily average radiation level of 5.14 - 5.50 kWh/m2/day. Financial feasible community models for different hilly region based on their energy consumption need to be implemented with the help of local community by providing ownership to local people, panchayat, for it not only caters energy access issue but also provides clean, cheep, uninterruptable energy and improves livelihood standard to locals by engaging them into operation maintenance and tariff or rent collection. The study shows that Solar PV power plant with battery bank is the optimal solution considering life cycle cost of hybrid system. It is feasible due to low operation and maintenance cost, price declination of battery and Solar PV module, battery prices at time of replacement.

A UNIFIED ENERGY APPROACH TO A CLASS OF MICROMECHANICS MODELS FOR COMPOSITE MATERIALS

Several micromechanics models for the determination of composite moduli are investigated in this paper,including the dilute solution,self-consistent method,generalized self-consistent method,and Mori-Tanaka's method.These mi- cromechanical models have been developed by following quite different approaches and physical interpretations.It is shown that all the micromechanics models share a common ground,the generalized Budiansky's energy-equivalence framework.The dif- ference among the various models is shown to be the way in which the average strain of the inclusion phase is evaluated.As a bonus of this theoretical development,the asymmetry suffered in Mori-Tanaka's method can be circumvented and the applica- bility of the generalized self-consistent method can be extended to materials contain- ing microcracks,multiphase inclusions,non-spherical inclusions,or non-cylindrical inclusions.The relevance to the differential method,double-inclusion model,and Hashin-Shtrikman bounds is also discussed.The application of these micromechanics models to particulate-reinforced composites and microcracked solids is reviewed and some new results are presented.

How Flat Space Cosmology Models Dark Energy

Equations of Flat Space Cosmology (FSC) are utilized to characterize the model’s scalar temporal behavior of dark energy. A table relating cosmic age, cosmological redshift, and the temporal FSC Hubble parameter value is created. The resulting graph of the log of the Hubble parameter as a function of cosmological (or galactic) redshift has a particularly interesting sinuous shape. This graph greatly resembles what ΛCDM proponents have been expecting for a scalar temporal behavior of dark energy. And yet, the FSC Rh = ct model expansion, by definition, neither decelerates nor accelerates. It may well be that apparent early cosmic deceleration and late cosmic acceleration both ultimately prove to be illusions produced by a constant-velocity, linearly-expanding, FSC universe. Furthermore, as discussed herein, the FSC model would appear to strongly support Freedman et al. in the current Hubble tension debate, if approximately 14 Gyrs can be assumed to be the current cosmic age.

The impact of industrial transformation on green economic efficiency:New evidence based on energy use

Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency changes and analyze the impact mechanism and realization path of industrial transformation on green economic efficiency. The research results show that advanced industrial structure has a positive influence on green economic efficiency nationwide, while energy utilization structure and energy utilization efficiency have positive partial intermediary effects in the influence path;industrial structure rationalization is also significantly positively related to green economic efficiency nationwide, and the mediating effect of energy utilization is positive. The impact of industrial transformation on green economic efficiency has regional heterogeneity, and the mediating effect of energy use also differs. Among them, the impact effect in the eastern region is basically consistent with the national sample, but is negative in the central and western regions. This paper proposes countermeasures in terms of adjusting the industrial structure, improving energy efficiency, and perfecting industrial and energy policies, which can provide theoretical and practical references for promoting the transformation and upgrading of regional industrial structure, optimizing energy utilization, and advancing the efficiency of the national and regional green economy.

Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability

Memristors are extensively used to estimate the external electromagnetic stimulation and synapses for neurons.In this paper,two distinct scenarios,i.e.,an ideal memristor serves as external electromagnetic stimulation and a locally active memristor serves as a synapse,are formulated to investigate the impact of a memristor on a two-dimensional Hindmarsh-Rose neuron model.Numerical simulations show that the neuronal models in different scenarios have multiple burst firing patterns.The introduction of the memristor makes the neuronal model exhibit complex dynamical behaviors.Finally,the simulation circuit and DSP hardware implementation results validate the physical mechanism,as well as the reliability of the biological neuron model.

eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

Building energy performance is a function of numerous building parameters.In this study,sensitivity analysis on twenty parameters is performed to determine the top three parameters that have the most significant impact on the energy performance of buildings.Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in the Quick Energy Simulation Tool(eQUEST).The model is calibrated using the Normalized Mean Bias Error(NMBE)and Coefficient of Variation of Root Mean Square Error(CV(RMSE))method.The model satisfies the NMBE and CV(RMSE)criteria set by the American Society of Heating,Refrigeration,and Air-Conditioning(ASHRAE)Guideline 14,Federal Energy Management Program(FEMP),and International Performance Measurement and Verification Protocol(IPMVP)for building energy model calibration.The values of the parameters are varied in two levels,and then the percentage change in output is calculated.Fractional factorial analysis on eight parameters with the highest percentage change in energy performance is performed at two levels in a statistical software JMP.For building A,the top 3 parameters from the percentage change method are:Heating setpoint,cooling setpoint and server room.From fractional factorial design,the top 3 parameters are:heating setpoint(p-value=0.00129),cooling setpoint(p-value=0.00133),and setback control(p-value=0.00317).For building B,the top 3 parameters from both methods are:Server room(pvalue=0.0000),heating setpoint(p-value=0.00014),and cooling setpoint(p-value=0.00035).If the best values for all top three parameters are taken simultaneously,energy efficiency improves by 29%for building A and 35%for building B.