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.

Systematic review of the efficacy of data-driven urban building energy models during extreme heat in cities:Current trends and future outlook

Energy demand fluctuations due to low probability high impact(LPHI)micro-climatic events such as urban heat island effect(UHI)and heatwaves,pose significant challenges for urban infrastructure,particularly within urban built-clusters.Mapping short term load forecasting(STLF)of buildings in urban micro-climatic setting(UMS)is obscured by the complex interplay of surrounding morphology,micro-climate and inter-building energy dynamics.Conventional urban building energy modelling(UBEM)approaches to provide quantitative insights about building energy consumption often neglect the synergistic impacts of micro-climate and urban morphology in short temporal scale.Reduced order modelling,unavailability of rich urban datasets such as building key performance indicators for building archetypes-characterization,limit the inter-building energy dynamics consideration into UBEMs.In addition,mismatch of resolutions of spatio-temporal datasets(meso to micro scale transition),LPHI events extent prediction around UMS as well as its accurate quantitative inclusion in UBEM input organization step pose another degree of limitations.This review aims to direct attention towards an integrated-UBEM(i-UBEM)framework to capture the building load fluctuation over multi-scale spatio–temporal scenario.It highlights usage of emerging data-driven hybrid approaches,after systematically analysing developments and limitations of recent physical,data-driven artificial intelligence and machine learning(AI-ML)based modelling approaches.It also discusses the potential integration of google earth engine(GEE)-cloud computing platform in UBEM input organization step to(i)map the land surface temperature(LST)data(quantitative attribute implying LPHI event occurrence),(ii)manage and pre-process high-resolution spatio-temporal UBEM input-datasets.Further the potential of digital twin,central structed data models to integrate along UBEM workflow to reduce uncertainties related to building archetype characterizations is explored.It has also found that a trade-off between high-fidelity baseline simulation models and computationally efficient platform support or co-simulation platform integration is essential to capture LPHI induced inter-building energy dynamics.

Dark Energy Models and Cosmic Acceleration with Anisotropic Universe in f(T) Gravity

This paper is devoted to studing the accelerated expansion of the universe in context of f（T） theory of gravity. For this purpose, we construct different f（T） models and investigate their cosmological behavior through equation of state parameter by using holographic, new agegraphic and their power-law entropy corrected dark energy models. We discuss the graphical behavior of this parameter versus redshif~ for particular values of constant parameters in Bianchi type I universe model. It is shown that the universe lies in different forms of dark energy, namely quintessence, phantom, and quintom corresponding to the chosen scale factors, which depend upon the constant parameters of the models.

Ranking parameters in urban energy models for various building forms and climates using sensitivity analysis

Urban Building Energy Modelling(UBEM)allows us to simulate buildings’energy performances at a larger scale.However,creating a reliable urban-scale energy model of new or existing urban areas can be difficult since the model requires overly detailed input data,which is not necessarily publicly unavailable.Model calibration is a necessary step to reduce the uncertainties and simulation results in order to develop a reliable and accurate UBEM.Due to the concerns over computational resources and the time needed for calibration,a sensitivity analysis is often required to identify the key parameters with the most substantial impact before the calibration is deployed in UBEM.Here,we study the sensitivity of uncertain input parameters that affect the annual heating and cooling energy demand by employing an urban-scale energy model,CitySim.Our goal is to determine the relative influence of each set of input parameters and their interactions on heating and cooling loads for various building forms under different climates.First,we conduct a global sensitivity analysis for annual cooling and heating consumption under different climate conditions.Building upon this,we investigate the changes in input sensitivity to different building forms,focusing on the indices with the largest Total-order sensitivity.Finally,we determine First-order indices and Total-order effects of each input parameter included in the urban building energy model.We also provide tables,showing the important parameters on the annual cooling and heating demand for each climate and each building form.We find that if the desired calibration process require to decrease the number of the inputs to save the computational time and cost,calibrating 5 parameters;temperature set-point,infiltration rate,floor U-value,avg.walls U-value and roof U-value would impact the results over 55%for any climate and any building form.

Impacts of gravitational-wave standard siren observations from Einstein Telescope and Cosmic Explorer on weighing neutrinos in interacting dark energy models

Multi-messenger gravitational wave(GW)observation for binary neutron star merger events could provide a rather useful tool to explore the evolution of the Universe.In particular,for the third-generation GW detectors,i.e.the Einstein Telescope(ET)and the Cosmic Explorer(CE),proposed to be built in Europe and the U.S.,respectively,lots of GW standard sirens with known redshifts could be obtained,which would exert great impacts on the cosmological parameter estimation.The total neutrino mass could be measured by cosmological observations,but such a measurement is model-dependent and currently only gives an upper limit.In this work,we wish to investigate whether the GW standard sirens observed by ET and CE could help improve the constraint on the neutrino mass,in particular in the interacting dark energy(IDE)models.We find that the GW standard siren observations from ET and CE can only slightly improve the constraint on the neutrino mass in the IDE models,compared to the current limit.The improvements in the IDE models are weaker than those in the standard cosmological model.Although the limit on neutrino mass can only be slightly updated,the constraints on other cosmological parameters can be significantly improved by using the GW observations.

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.

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.

Energy-Efficient and Cost-Effective Approaches through Energy Modeling for Hotel Building

Hotel buildings are currently among the largest energy consumers in the world.Heating,ventilation,and air conditioning are the most energy-intensive building systems,accounting for more than half of total energy consumption.An energy audit is used to predict the weak points of a building’s energy use system.Various factors influence building energy consumption,which can be modified to achieve more energy-efficient strategies.In this study,an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year.Energy modeling is conducted by using Autodesk Revit 2025.It was discovered from the results that arranging the lighting schedule based on the ASHRAE Standard 90.1 could save up to 8.22%of energy consumption.And then the results also revealed that changing the glazing of the building into double-layer lowemissivity glass could reduce energy consumption by 14.58%.While the energy consumption of the building could also be decreased to 7.20%by changing the building orientation to the north.Meanwhile,moving the building location to Northern Taiwan could also minimize the energy consumption of the building by 3.23%.The results revealed that the double layer offers better thermal insulation,and low-emissivity glass can lower energy consumption,electricity costs,and CO_(2)emissions by up to 15.27%annually.While adjusting orientation and location can enhance energy performance,this approach is impractical for existing buildings,but this could be considered for designing new buildings.The results showed the relevancy of energy performance to CO_(2)emission production and electricity expenses.

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.

Determination of energy coupling to material in laser welding by a novel “sandwich” method

A mathematical energy coupling model was developed to analyze the light transmission in the keyhole and energy distribution on the keyhole wall.The main characteristics of the model include：1） a prototype of the keyhole and the inverse Bremsstrahlung absorption coefficient in the keyhole plasma are obtained from the experiments;2） instead of using a parallel incident beam,a focused laser beam with real Gaussian intensity distribution is implemented;3） both Fresnel absorption and inverse Bremsstrahlung absorption during multiple reflections are considered.The calculation results show that the distribution of absorbed laser intensity by the keyhole wall is not uniform.The maximum laser energy is absorbed by the bottom of the keyhole,although no rays irradiate directly onto the bottom.According to analysis of beam focusing characteristics,the location of the focal plane plays a more important role in the laser energy absorption by the front wall than by the rear wall.

Warm inflation triggered by entropies of some recent dark energy models within f(Q)gravity

This manuscript aims to study cosmic warm inflation(WI)in the framework of f(Q)-gravity,where Q represents the nonmetricity(NM)scalar.To accomplish this task,we introduce the Tsallis,Renyi,and Barrow holographic dark energy(HDE)entropies into the standard Friedmann equations.Utilizing the slow-roll(SR)approximation,we find exact analytic solutions for the inflaton field,the effective potential necessary to produce inflation,and the scale factor for both low-and high-dissipative regimes.We calculate key parameters,including SR parameters,the number of e-folds,the scalar spectral index and its running,and finally tensor-to-scalar ratio to assess the accuracy of the chosen DE models in light of the published observational data.The allowed ranges of the involved free parameters are found from the limits on inflationary observables imposed by the Planck data.It is concluded that the obtained results are consistent with proposed theoretical predictions up to the 2σ confidence level.

Accurate energy model for WSN node and its optimal design

With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.

Prospects of key technologies of integrated energy systems for rural electrification in China

Owing to increasing environmental concerns and resource scarcity, integrated energy system shave become widely used in communities. Rural energy systems, as one of the important links of the energy network in China, suffer from low energy efficiency and weak infrastructure. Therefore, it is particularly important to increase the proportion of electricity consumption and build an integrated energy system for rural electrification in China(IESREIC) with a rural distribution network as the core, in line with national conditions. In this study, by analyzing the Chinese regional differences and natural resource endowments, the development characteristics of the IESREIC are summarized. Then, according to the existing rural energy problems, key technologies are proposed for the IESREIC, such as those for planning and operation, value sharing, infrastructure, and a management and control platform. Finally, IESREIC demonstration projects and business models are introduced for agricultural production, rural industrial systems, and rural life. The purpose is to propose research concepts for the IESREIC, provide suggestions for the development of rural energy, and provide a reference for the construction of rural energy systems in countries with characteristics similar to those of China.

Structure and Properties of Hydrotalcite Using Electrostatic Potential Energy Model

The electrostatic potential energy model of hydrotalcites was based on the theory of crystallography. The anionic potential energy of MgAl-hydrotalcites, with 20 layers and 2107 anions per layer, was calculated, and the anionic stability of the hydrotalcites was investigated. The charge density of the layer and the distance between the adjacent anions varied with the molar ratio of Al^3＋/（Mg^2＋ ＋ Al^3＋）. Anionic potential energy depended on the charge and size of the anions. Calculation results remained consistent with thermal stability and the ion exchange ability reported. This model is able to predict anionic stability of the hydrotalcites.

Energy Model for UAV Communications:Experimental Validation and Model Generalization

Wireless communication involving unmanned aerial vehicles(UAVs)is expected to play an important role in future wireless networks.However,different from conventional terrestrial communication systems,UAVs typically have rather limited onboard energy on one hand,and require additional flying energy consumption on the other hand.This renders energy-efficient UAV communication with smart energy expenditure of paramount importance.In this paper,via extensive flight experiments,we aim to firstly validate the recently derived theoretical energy model for rotary-wing UAVs,and then develop a general model for those complicated flight scenarios where rigorous theoretical model derivation is quite challenging,if not impossible.Specifically,we first investigate how UAV power consumption varies with its flying speed for the simplest straight-and-level flight.With about 12,000 valid power-speed data points collected,we first apply the model-based curve fitting to obtain the modelling parameters based on the theoretical closed-form energy model in the existing literature.In addition,in order to exclude the potential bias caused by the theoretical energy model,the obtained measurement data is also trained using a model-free deep neural network.It is found that the obtained curve from both methods can match quite well with the theoretical energy model.Next,we further extend the study to arbitrary 2-dimensional(2-D)flight,where,to our best knowledge,no rigorous theoretical derivation is available for the closed-form energy model as a function of its flying speed,direction,and acceleration.To fill the gap,we first propose a heuristic energy model for these more complicated cases,and then provide experimental validation based on the measurement results for circular level flight.

GLOBAL EXISTENCE AND ASYMPTOTIC BEHAVIOR FOR AN 1-D COMPRESSIBLE ENERGY TRANSPORT MODEL

In this article, the global existence and the large time behavior of smooth solutions to the initial boundary value problem for a degenerate compressible energy transport model are established.

Energy Efficiency in Internet of Things:An Overview

Energy efficiency is very important for the Internet of Things(IoT),especially for front-end sensed terminal or node.It not only embodies the node’s life,but also reflects the lifetime of the network.Meanwhile,it is also a key indicator of green communications.Unfortunately,there is no article on systematic analysis and review for energy efficiency evaluation in IoT.In this paper,we systemically analyze the architecture of IoT,and point out its energy distribution,Furthermore,we summarized the energy consumption model in IoT,analyzed the pros and cons of improving energy efficiency,presented a state of the art the evaluation metrics of energy efficiency.Finally,we conclude the techniques and methods,and carry out a few open research issues and directions in this field.

Two-state energy model and experimental study of coal adsorb methane

There are two states of methane existing in coal, free methane and adsorptive methane. The two states of methane exchanged with each other which need the energy exchange with outside. It is released heat when methane adsorption on coal, instead of absorbed heat. According to the gas molecules Boltzmann energy distribution, is obtained the equilibrium equations of the two states of methane in coal, as well as the heat of adsorption equation when exchanged into each other. At the same time, high temperature experiments of methane adsorption on coal have been certificated to the theoretical model. At last the experimental results presented that： the two-state energy model could be accurately described the distribution of the two states of methane in the coal; the adsorption heat is related to the initial equilibrium state of methane adsorption; the adsorption heats are different with different coal ranks.

Characteristics of land-atmosphere energy and turbulentfluxes over the plateau steppe in central Tibetan Plateau

The land-atmosphere energy and turbulence exchange is key to understanding land surface processes on the Tibetan Plateau(TP). Using observed data for Aug. 4 to Dec. 3, 2012 from the Bujiao observation point(BJ) of the Nagqu Plateau Climate and Environment Station(NPCE-BJ), different characteristics of the energy flux during the Asian summer monsoon(ASM) season and post-monsoon period were analyzed. This study outlines the impact of the ASM on energy fluxes in the central TP. It also demonstrates that the surface energy closure rate during the ASM season is higher than that of the post-monsoon period. Footprint modeling shows the distribution of data quality assessments(QA) and quality controls(QC) surrounding the observation point. The measured turbulent flux data at the NPCE-BJ site were highly representative of the target land-use type. The target surface contributed more to the fluxes under unstable conditions than under stable conditions. The main wind directions(180° and 210°) with the highest data density showed flux contributions reaching 100%, even under stable conditions. The lowest flux contributions were found in sectors with low data density, e.g., 90.4% in the 360° sector under stable conditions during the ASM season. Lastly, a surface energy water balance(SEWAB) model was used to gap-fill any absent or corrected turbulence data. The potential simulation error was also explored in this study. The Nash-Sutcliffe model efficiency coefficients(NSEs) of the observed fluxes with the SEWAB model runs were 0.78 for sensible heat flux and 0.63 for latent heat flux during the ASM season, but unrealistic values of-0.9 for latent heat flux during the post-monsoon period.