Morphology prediction of dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50) crystal in different solvent systems using modified attachment energy model

In order to theoretically study the growth morphology of dihydroxylammonium 5,5’-bistetrazole-1,1’-dio late(TKX-50)crystal in different solvent systems,crystal–solvent models were established,and then molecular dynamics(MD)methods were adopted as a means to simulate particle motion.Modified attachment energy(MAE)model was employed to calculate the growth morphology of TKX-50.The simulation results demonstrate that COMPASS force field and RESP charge are suitable for molecular dynamics simulation of TKX-50.The morphologically dominant growth surfaces of TKX-50 in vacuum are(020),(011),(11–1),(100)and(120),respectively.In water(H_(2)O)and N,N-dimethylformamide(DMF)solvents,the(11–1)face is the largest in the habit face,the growth rate of(020)face becomes faster.With the increase of temperature,the aspect ratios of TKX-50 crystal in DMF solvent increase,and the areas of the(120)faces decrease.In ethylene glycol/H_(2)O mixed solvent system with volume ratio of 1/1,aspect ratio of TKX-50 is relatively small.In formic acid/H_(2)O mixed solvents with different volume ratios(1/4,1/3,1/2,1/1 and 2/1),aspect ratio of TKX-50 is relatively small when volume ratio is 1/2.

Energy-Efficient Approaches for a Machine Tool Building in a University through Field Measurement and Energy Modelling

The heating,ventilating,and air conditioning(HVAC)system consumes nearly 50%of the building’s energy,especially in Taiwan with a hot and humid climate.Due to the challenges in obtaining energy sources and the negative impacts of excessive energy use on the environment,it is essential to employ an energy-efficient HVAC system.This study conducted the machine tools building in a university.The field measurement was carried out,and the data were used to conduct energymodelling with EnergyPlus(EP)in order to discover some improvements in energy-efficient design.The validation between fieldmeasurement and energymodelling was performed,and the error rate was less than 10%.The following strategies were proposed in this study based on several energy-efficient approaches,including room temperature settings,chilled water supply temperature settings,chiller coefficient of performance(COP),shading,and building location.Energy-efficient approaches have been evaluated and could reduce energy consumption annually.The results reveal that the proposed energy-efficient approaches of room temperature settings(3.8%),chilled water supply temperature settings(2.1%),chiller COP(5.9%),using shading(9.1%),and building location(3.0%),respectively,could reduce energy consumption.The analysis discovered that using a well-performing HVAC system and building shading were effective in lowering the amount of energy used,and the energy modelling method could be an effective and satisfactory tool in determining potential energy savings.

Energy model based sensorless estimation method for operational temperature of braking resistor onboard metro vehicles

Purpose–This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor(BR)onboard the vehicle,which overcomes the vulnerability of having conventional temperature sensor.Design/methodology/approach–In this study,the energy model based sensorless estimation method is developed.By analyzing the structure and the convection dissipation process of the BR onboard the vehicle,the energy-based operational temperature model of the BR and its cooling domain is established.By adopting Newton’s law of cooling and the law of conservation of energy,the energy and temperature dynamic of the BR can be stated.To minimize the use of all kinds of sensors(including both thermal and electrical),a novel regenerative braking power calculation method is proposed,which involves only the voltage of DC traction network and the duty cycle of the chopping circuit;both of them are available for the traction control unit(TCU)of the vehicle.By utilizing a real-time iterative calculation and updating the parameter of the energy model,the operational temperature of the BR can be obtained and monitored in a sensorless manner.Findings–In this study,a sensorless estimation/monitoring method of the operational temperature of BR is proposed.The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR,instead of adding dedicated thermal sensors.The results also validate the effectiveness of the proposal is acceptable for the engineering practical.Originality/value–The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks.The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.

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.

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.

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.

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.

Kinetic analysis and modeling of maize straw hydrochar combustion using a multi-Gaussian-distributed activation energy model

Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.

Stability Analysis of the Viscous Polytropic Dark Energy Model in Einstein Cosmology

The viscous polytropic gas model as one model of dark energy is hot-spot and keystone to the modern cosmology. We study the evolution of the viscous polytropic dark energy model interacting with the dark matter in the Einstein cosmology. Setting the autonomous dynamical system for the interacting viscous polytropic dark energy with dark matter and using the phase space analysis method to investigate the dynamical evolution and its critical stability, we find that the viscosity property of the dark energy creates a benefit for the stable critical dynamical evolution of the interaction model between dark matter and dark energy in the flat Friedmann-Robertson-Walker universe and the viscosity of dark energy will soften the coincidence problem just like the interacting dark energy model.

Dynamical Study of a Constant Viscous Dark Energy Model in Classical and Loop Quantum Cosmology

Dynamical behaviors and stability properties of a flat space Friedmann-Robertson-Walker universe filled with pressureless dark matter and viscous dark energy are studied in the context of standard classical and loop quantum cosmology. Assuming that the dark energy has a constant bulk viscosity, it is found that the bulk viscosity effects influence only the quintessence model case leading to the existence of a viscous late time attractor solution of de- Sitter type, whereas the quantum geometry effects influence the phantom model case where the big rip singularity is removed. Moreover, our results of the Hubble parameter as a function of the redshift are in good agreement with the more recent data.

New initial condition of the new agegraphic dark energy model

The initial condition Ωde（zini）=n^2（1＋zini）^-2/4 at zini = 2000,widely used to solve the differential equation of the density of the new agegraphic dark energy（NADE） Ωde,makes the NADE model a single-parameter dark-energy cosmological model.However,we find that this initial condition is only applicable in a flat universe with only dark energy and pressureless matter.In fact,in order to obtain more information from current observational data,such as the cosmic microwave background（CMB） and the baryon acoustic oscillations（BAO）,we need to consider the contribution of radiation.For this situation,the initial condition mentioned above becomes invalid.To overcome this shortcoming,we investigate the evolutions of dark energy in matter-dominated and radiation-dominated epochs,and obtain a new initial condition de（zini）=n2（1＋zini）-2（1＋F（zini））2/4 at z ini = 2000,where F（z）≡Ωr0（1＋z）/[Ωm0＋Ωr0（1＋z）] with Ωr0 and Ωm0 being the current density parameters of radiation and pressureless matter,respectively.This revised initial condition is applicable for the differential equation of Ωde obtained in the standard Friedmann-Robertson-Walker（FRW） universe with dark energy,pressureless matter,radiation,and even spatial curvature,and can still keep the NADE model as a single-parameter model.With the revised initial condition and the observational data of type Ia supernova（SNIa）,CMB,and BAO,we finally constrain the NADE model.The results show that the single free parameter n of the NADE model can be constrained tightly.

Improvement of energy model based on cubic interpolation curve

In CAGD and CG, energy model is often used to control the curves and surfaces shape. In curve/surface modeling, we can get fair curve/surface by minimizing the energy of curve/surface. However, our research indicates that in some cases we can＇t get fair curves/surface using the current energy model. So an improved energy model is presented in this paper. Examples are also included to show that fair curves can be obtained using the improved energy model.

Energy model of projected transfer with additional mechanical force in the welding process

Based on the theory of electrodynamics and other relational subjects,through introducing “Surface Evolver” as the means of FEM analysis, by computing and describing the energy (electromagnetic, gravity, and so on) in the droplet transfer system, an energy model was accomplished for studying the mechanism of projected transfer mode.Furthermore, the behavior of droplet transfer was studied by analyzing its menisci with FEM, and the theoretical results coincide well with the experiment results.

Dark Energy Model with Non-Minimal Coupling and Cosmological Constant Boundary

In this paper,we study a kind of dark energy models in the framework of the non-minimal coupling.With this kind of models,dark energy could cross the cosmological constant boundary,and at early time,dark energy could have 'tracking' behavior.

Assessment of Sustainable Energy Strategy with Long-Term Global Energy Model Incorporating Nuclear Fuel Cycle

This paper investigates long-term energy strategy compatible with significant reduction of world carbon dioxide （CO2） emissions, employing a long-term global energy model, Dynamic New Earth 21 （called DNE21）. The model seeks the optimal energy mix from 2000 to 2100 that minimizes the world total energy system cost under various kinds of energy and technological constraints, such as energy resource constraints, energy supply and demand balance constraints, and CO2 emissions constraints. This paper discusses the results of primary energy supply, power generation mix, CO2 emission, CCS （carbon capture and storage） and total system costs for six regions including world as a whole. To evaluate viable pathways forward for implementation of sustainable energy strategies, nuclear power generation is a viable source of clean and green energy to mitigate the CO2 emissions. Present research shows simulation results in two cases consisting of no CO2 regulation case （base case） and CO2 REG case （regulation case） which halves the world CO2 emissions by the year 2050. Main findings of this research describe that renewable and nuclear power generation will contribute significantly to mitigate the CO2 emission worldwide.

Development of a time-dependent energy model to calculate the mining-induced stress over gates and pillars

Generally, longwall mining-induced stress results from the stress relaxation due to destressed zone that occurs above the mined panel. Knowledge of induced stress is very important for accurate design of adjacent gateroads and intervening pillars which helps to raise the safety and productivity of longwall mining operations. This study presents a novel time-dependent analytical model for determination of the longwall mining-induced stress and investigates the coefficient of stress concentration over adjacent gates and pillars. The model is developed based on the strain energy balance in longwall mining incorporated to a rheological constitutive model of caved materials with time-varying parameters. The study site is the Tabas coal mine of Iran. In the proposed model, height of destressed zone above the mined panel, total longwall mining-induced stress, abutment angle, induced vertical stress, and coefficient of stress concentration over neighboring gates and intervening pillars are calculated. To evaluate the effect of proposed model parameters on the coefficient of stress concentration due to longwall mining, sensitivity analysis is performed based on the field data and experimental constants. Also, the results of the proposed model are compared with those of existing models. The comparative results confirm a good agreement between the proposed model and the in situ measurements. According to the obtained results, it is concluded that the proposed model can be successfully used to calculate the longwall mining-induced stress. Therefore, the optimum design of gate supports and pillar dimensions would be attainable which helps to increase the mining efficiency.

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.

The potential of remote sensing and GIS in urban building energy modelling

As the world continues to urbanize at an unprecedented rate,the energy demand in cities is rising.Buildings account for over 75%of all the energy consumed in cities and are responsible for over two-thirds of the emissions.Assessment of energy demand in buildings is a highly integrative endeavour,bringing together the interdisciplinary fields of energy and urban studies,along with a host of technical domains namely,geography,engineering,economics,sociology,and planning.In the last decade,several urban building energy modelling tools(UBEMs)have been developed for estimation as well as prediction of energy demand in cities.These models are useful in policymaking as they can evaluate future urban energy scenarios.However,data acquisition for generating the input database for UBEM has been a major challenge.In this review,a comprehensive assessment of the potential of remote sensing and GIS techniques for UBEM has been presented.Firstly,the most common input variables of UBEM have been identified by reviewing recent publications on UBEM and then studies related to the acquisition of data corresponding to these variables have been explored.More than 140 research papers and review articles relevant to remote sensing and GIS applications for building level data extraction in urban areas and UBEM applications have been investigated for this purpose.After going through level of details required for each of the input components of UBEM and studying the possibility of acquiring some of those data using remote sensing,it has been inferred that satellite remote sensing and Unmanned Aerial Vehicles(UAVs)have a strong potential in enhancing the input data space for UBEM but their applicability has been limited.Further,the challenges of the usage of these technologies and the possible solutions have also been presented in this study.It is recommended to utilise the existing methodologies of extracting information from remote sensing and GIS for UBEM,along with newer techniques such as machine learning and artificial intelligence.

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.