Improved Diurnal Cycle of Precipitation on Land in a Global Non-Hydrostatic Model Using a Revised NSAS Deep Convective Scheme

In relatively coarse-resolution atmospheric models,cumulus parameterization helps account for the effect of subgridscale convection,which produces supplemental rainfall to the grid-scale precipitation and impacts the diurnal cycle of precipitation.In this study,the diurnal cycle of precipitation was studied using the new simplified Arakawa-Schubert scheme in a global non-hydrostatic atmospheric model,i.e.,the Yin-Yang-grid Unified Model for the Atmosphere.Two new diagnostic closures and a convective trigger function were suggested to emphasize the job of the cloud work function corresponding to the free tropospheric large-scale forcing.Numerical results of the 0.25-degree model in 3-month batched real-case simulations revealed an improvement in the diurnal precipitation variation by using a revised trigger function with an enhanced dynamical constraint on the convective initiation and a suitable threshold of the trigger.By reducing the occurrence of convection during peak solar radiation hours,the revised scheme was shown to be effective in delaying the appearance of early-afternoon rainfall peaks over most land areas and accentuating the nocturnal peaks that were wrongly concealed by the more substantial afternoon peak.In addition,the revised scheme enhanced the simulation capability of the precipitation probability density function,such as increasing the extremely low-and high-intensity precipitation events and decreasing small and moderate rainfall events,which contributed to the reduction of precipitation bias over mid-latitude and tropical land areas.

Effect of dry-wet cycles on dynamic properties and microstructures of sandstone:Experiments and modelling

Underground pumped storage power plant(UPSP)is an innovative concept for space recycling of abandoned mines.Its realization requires better understanding of the dynamic performance and durability of reservoir rock.This paper conducted ultrasonic detection,split Hopkinson pressure bar(SHPB)impact,mercury intrusion porosimetry(MIP),and backscatter electron observation(BSE)tests to investigate the dynamical behaviour and microstructure of sandstone with cyclical dry-wet damage.A coupling FEM-DEM model was constructed for reappearing mesoscopic structure damage.The results show that dry-wet cycles decrease the dynamic compressive strength(DCS)with a maximum reduction of 39.40%,the elastic limit strength is reduced from 41.75 to 25.62 MPa.The sieved fragments obtain the highest crack growth rate during the 23rd dry-wet cycle with a predictable life of 25 cycles for each rock particle.The pore fractal features of the macropores and micro-meso pores show great differences between the early and late cycles,which verifies the computational statistics analysis of particle deterioration.The numerical results show that the failure patterns are governed by the strain in pre-peak stage and the shear cracks are dominant.The dry-wet cycles reduce the energy transfer efficiency and lead to the discretization of force chain and crack fields.

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

Valve Dynamic and Thermal Cycle Model in Stepless Capacity Regulation for Reciprocating Compressor

The existing researches of stepless capacity regulation system by depressing the suction valve for reciprocation compressor always adopt hypothesis that the compressor valves are open or close instantaneously, the valve dynamic has not been taken account into thermal cycle computation, the influence of capacity regulation system on suction valves dynamic performance and cylinder thermal cycle operation has not been considered. This paper focuses on theoretical and experimental analysis of the valve dynamic and thermal cycle for reciprocating compressor in the situation of stepless capacity regulation. The valve dynamics equation, gas forces for normal and back flow, and the cylinder pressure varying with suction valve unloader moment during compression thermal cycle are discussed. A new valve dynamic model based on L-K real gas state equation for reciprocating compressor is first deduced to reduce the calculation errors induced by the ideal gas state equation. The variations of valve dynamic and cylinder pressure during part of compression stroke are calculated numerically. The calculation results reveal the non-normal thermal cycle and operation condition of compressor in stepless capacity regulation situation. The numerical simulation results of the valve dynamic and thermal cycle parameters are also verified by the stepless capacity regulation experiments in the type of 3L-10/8 reciprocating compressor. The experimental results agree with the numerical simulation results, which show that the theoretical models proposed are effective and high-precision. The proposed theoretical models build the theoretical foundation to design the real stepless capacity regulation system.

Dynamic grey model of verification cycle and lifecycle of measuring instrument and its application

Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination data and weighting method. By a specific case, i.e. vernier caliper, it is proved that the fit precision and forecast precision of the models are much higher, the cycles are obviously different under different working conditions, and the forecast result of the frequency sequence model is better than that of the time sequence model. Combining dynamic grey model and auto-manufacturing case the controlling and information subsystems of verification cycle and the lifecycle based on information integration, multi-sensor controlling and management controlling were given. The models can be used in production process to help enterprise reduce error, cost and flaw.

The El Ni?o-Southern Oscillation cycle simulated by the climate system model of Chinese Academy of Sciences

On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences （CAS-ESM-C） in simulating the E1 Nifio-Southern Oscillation （ENSO） cycle is evalu- ated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature （SST） in the tropical Pacif- ic, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the E1 Nino onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster develop- ment of an E1 Nino. During the decay stage, owing to a stronger E1Nino in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an E1 Nino decays into a La Nina through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attribut- ed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean.

Using hybrid modeling for life cycle assessment of motor bike and electric bike

Life-cycle assessment (LCA) is environmental evaluation of products, materials, and processes over their life cycle. Truncation uncertainty and corresponding uncertainty are main problems occurred in process life cycle assessment (PLCA) modeling and economic input-output life cycle assessment (EIOLCA) modeling. Through combination of these two modelings in different life cycle stage and use of an uncertainty reduction strategy, a hybrid life cycle assessment modeling method was proposed in this study. Case studies were presented on gasoline-powered motorbikes (M-bike) and electricity-powered electric bike (E-bike). Web-based software was developed to analyze process environmental impacts. Results show that the largest part of life cycle energy (LCE) is consumed at use stage. Less energy is consumed in life cycle of E-bike than that of M-bike. GWP (Global Warming Potential), CO (Carbon Monoxide), PM10 (particulate matter) emission of M-bike are higher than that of E-bike, especially at use stage, AP (acidification Potential) emission of E-bike is higher than that of M-bike. Comprehensively, E-bike is energy efficient and less emitting, and better choice for urban private transportation.

Chloride Ion Transmission Model under the Drying-wetting Cycles and Its Solution

The chloride ion transmission model considering diffusion and convection was established respectively for different zones in concrete by analyzing chloride ion transmission mechanism under the dryingwetting cycles. The finite difference method was adopted to solve the model. The equation of chloride ion transmission model in the convection and diffusion zone of concrete was discreted by the group explicit scheme with right single point （GER method） and the equation in diffusion zone was discreted by FTCS difference scheme. According to relative humidity characteristics in concrete under drying-wetting cycles, the seepage velocity equation was formulated based on Kelvin Equation and Darcy＇s Law. The time-variant equations of chloride ion concentration of concrete surface and the boundary surface of the convection and diffusion zone were established. Based on the software MATLAB the numerical calculation was carried out by using the model and basic material parameters from the experiments. The calculation of chloride ion concentration distribution in concrete is in good agreement with the drying-wetting cycles experiments. It can be shown that the chloride ion transmission model and the seepage velocity equation are reasonable and practical. Studies have shown that the chloride ion transmission in concrete considering convection and diffusion under the drying-wetting cycles is the better correlation with the actual situation than that only considering the diffusion.

Responses of the ocean carbon cycle to climate change: Results from an earth system climate model simulation

Based on simulations using the University of Victoria's Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic's ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean's ability to absorb CO2 from the atmosphere.

Glutathione Peroxidase Revisited—Simulation of the Catalytic Cycle by Computer-Assisted Molecular Modelling

Glutathione peroxidase, the first example of selenoproteins identified in mammals, was subjected to force field calculations and molecular dynamics in order to enable a clearer comprehension of enzymatic selenium catalysis. Starting from the established X-ray structure of bovine GPX, all kinetically defined intermediates and enzyme substrate complexes were modelled. The models thus obtained support the hypothesis that the essential steps of the catalysis are three distinct redox changes of the active site selenium which, in the ground state, presents itself at the surface of selenoperoxidases as the center of a characteristic triad built by selenocysteine, glutarnine and tryptophan. In GPX, four arginine residues and a lysine residue provide an electrostatic architecture which, in each reductive step, directs the donor substrate GSH towards the catalytic center in such a way that 1ts sulfhydryl group must react with the selenium moiety. To this end, different equally efficient modes of substrate binding appear possible. The models are consistent with substrate specificity data, kinetic pattern and other functional characteristics of the enzyme. Comparison of molecular models of GPX with those of other members of the GPX superfamily reveals that the cosubstrate binding mechanisrns are unique for the classical type of cytosolic glutathione peroxidases but cannot operate e. g. in plasma GPX and phospholipid hydroperoxide GPX. The structural differences between the selenoperoxidases, shown to be relevant to their specificities, are discussed in terms of functional diversification within the GPX superfamily

Damage characteristics and new constitutive model of sandstone under wet–dry cycles

The mechanical properties of rock deteriorate under repeated wet-dry(WD)cycles,causing the deformation and failure of the rock mass.A reasonable damage constitutive model can truly reflect the whole process of rock deformation and failure.Therefore,it is of great significance to study the damage characteristics and constitutive behaviour of rock subjected to numerous WD cycles.First,sandstone from Tingliang tunnel was sampled for the WD cycle experiment,and uniaxial and triaxial tests were carried out on the rock samples after various numbers of WD cycles to analyze their macroscale damage characteristics.Then,the damage mechanisms of the rock samples under the action of WD cycling were identified by X-ray diffraction(XRD)and scanning electron microscopy(SEM).Finally,based on the test data,the WD cycle-induced damage variable,Weibull distribution function,damage threshold,Drucker-Prager(D-P)yield criterion and residual strength correction coefficient were introduced,a wet-dry loading(WDL)constitutive damage model that considers the cracking stress of rock masses was established,and the expressions of the corresponding parameters were given.The results show that an increasing number of WD cycles induces considerable variations in the macroscopic physical and mechanical parameters(such as the rock sample mass,saturated water content,longitudinal-wave velocity,compressive strength and elastic modulus),and the rate of change presents two stages,the inflection point of their rate of change is the 15th WD cycle.Microscopically,the rock sample structure changes from intact and dense to fragmented and unconsolidated;additionally,the surface roughness increases,and the mineral composition changes.The established constitutive damage model exhibited good agreement with the experimental data;thus,this model can reflect the deformation and failure of rocks under WDL conditions,and the physical meaning of each parameter is clear.

Simulation of terrestrial carbon cycle balance model in Tibet

Based on climate material, the simplified terrestrial carbon cycle balance (TCCB) model was established, which is semi-mechanism and semi-statistics. Through TCCB model, our estimate indicates that the southeastern part of the Tibetan Plateau has much higher carbon content, and we have calculated the litter carbon pool, NPP, carbon fluxes and described their spatial characteristics in this region. Based on the TCCB model simulation, NPP in Tibet is 1.73×10 8 tC/a, soil organic input rate is 0.66×10 8 tC/a, litter mineralization rate is 1.07×10 8 tC/a, vegetation litterfall rate is 1.73×10 8 tC/a, the litter carbon pool is 7.26×10 8 tC, and soil decomposition rate is 309.54×10 8 tC/a. The carbon budget was also analyzed based on the estimates of carbon pool and fluxes. The spatial distributions of carbon pools and carbon fluxes in different compartments of terrestrial ecosystem were depicted with map respectively in Tibet. The distribution of NPP, vegetation litterfall rate, litter, litter mineralization rate, soil organic input rate and the soil decomposition rate were abstracted with temperature, precipitation, fractional vegetation and land feature.

A discrete-event model to simulate the effect of truck bunching due to payload variance on cycle time, hauled mine materials and fuel consumption

Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.

Sensitivity of Nonlinearity on the ENSO Cycle in a Simple Air-Sea Coupled Model

In this paper,the influence of the El NioSouthern Oscillation (ENSO) cycle on the sensitivity of nonlinear factors in the numerical simulation is investigated by conducting numerical experiments in a simple air-sea coupled model for ENSO prediction.Two sets of experiments are conducted in which zonal nonlinear factors,meridional nonlinear factors,or both are incorporated into the governing equations for the atmosphere or ocean.The results suggest that the ENSO cycle is very sensitive to the nonlinear factor of the governing equation for the atmosphere or ocean.Thus,incorporating nonlinearity into air-sea coupled models is of exclusive importance for improving ENSO simulation.

A Two-Dimensional Zonally Averaged Ocean Carbon Cycle Model

An ocean carbon cycle model driven by a constant flow field produced by a two-dimensional thermohaline circulation model is developed. Assuming that the biogenic carbon in the oceans is in a dynamic equilibrium, the inorganic carbon cycle is investigated. Before the oceanic uptake of CO_2 is carried out, the investigation of 14C distributions in the oceans, including natural and bomb-produced 14C,is conducted by using different values of the exchange coefficient of CO_2for different flow fields (different vertical diffusivities) to test the performance of the model. The suitable values of the exchange coefficient and vertical diffusivities are chosen for the carbon cycle model. Under the forcing of given preindustrial atmospheric CO_2 concentration of 280 ppmv, the carbon cycle model is integrated for seven thousand years to reach a steady state. For the human perturbation, two methods including the prescribed atmospheric pCO_2 and prescribed industrial emissions are used in this work. The results from the prescribed atmospheric pCO_2 show that the oceans take up 36% of carbon dioxide released by human activities for the period of 1980-1989, while the results from the prescribed industrial emission rates show that the oceans take up 34% of carbon dioxide emitted by industrial sources for the same period. By using the simple method of subtracting industrial emission rate from the total atmosphere+ocean accumulating rate, it can be deduced that before industrial revolution a non-industrial source exists, while after 1940 an extra sink is needed, and that a total non-industrial source of 45 GtC is obtained for the period of 1790-1990.

Estimation of Building’s Life Cycle Carbon Emissions Based on Life Cycle Assessment and Building Information Modeling: A Case Study of a Hospital Building in China

Throughout the life cycle, the buildings emit a great deal of carbon dioxide into the atmosphere, which directly leads to aggravation in the greenhouse effect and becomes a severe threat to the environment and humans. Researchers have made numerous efforts to accurately calculate emissions to reduce the life cycle carbon emissions of residential buildings. Nevertheless, there are still difficulties in quickly estimating carbon emissions in the design stage without specific data. To fill this gap, the study, based on Life Cycle Assessment (LCA) and Building Information Modeling (BIM), proposed a quick method for estimating Building’s Life Cycle Carbon Emissions (BLCCE). Taking a hospital building in Chuzhou City, Anhui Province, China as an example, it tested its possibility to estimate BLCCE. The results manifested that: 1) the BLCCE of the project is 40,083.56 tCO2-eq, and the carbon emissions per square meter per year are 119.91 kgCO2-eq/(m2·y);2) the stage of construction, operational and demolition account for 7.90%, 91.31%, and 0.79% of BLCCE, respectively;3) the annual carbon emissions per square meter of hospital are apparently higher than that of villa, residence, and office building, due to larger service population, longer daily operation time, and stricter patient comfort requirements. Considering the lack of BLCCE research in Chinese hospitals, this case study will provide a valuable reference for the estimated BLCCE of hospital building.

Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model

Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI.

Stochastic Modelling of Vulnerability Life Cycle and Security Risk Evaluation

The objective of the present study is to propose a risk evaluation statistical model for a given vulnerability by examining the Vulnerability Life Cycle and the CVSS score. Having a better understanding of the behavior of vulnerability with respect to time will give us a great advantage. Such understanding will help us to avoid exploitations and introduce patches for a particular vulnerability before the attacker takes the advantage. Utilizing the proposed model one can identify the risk factor of a specific vulnerability being exploited as a function of time. Measuring of the risk factor of a given vulnerability will also help to improve the security level of software and to make appropriate decisions to patch the vulnerability before an exploitation takes place.

Nitrogen cycle model of agroecosystem in the karst region of Guizhou Province

According to the transport theory of soil solutes and the conditions of soil,geology and climate in the karst region of Guizhou Province,a numerical simulation model of edaphic nitrogen element transport under field conditions is initially established.In this model,NO-3 and NH+4 are regarded as soil solutes.Transformation mechanisms such as biological release,bio-immobilization,ammonium adsorption-desorption,nitration-denitrification and factors of crop root uptaking are considered in this model.It is hoped that the data from this model could directly be used to guide agricultural production in this region and offer feasible ways to improve the use of nitrogen element,sustainable development of agriculture in karst mountainous areas and natural environment.

Design of Fine Life Cycle Prediction System for Failure of Medical Equipment

The inquiry process of traditional medical equipment maintenance management is complex,which has a negative impact on the efficiency and accuracy of medical equipment maintenance management and results in a significant amount of wasted time and resources.To properly predict the failure of medical equipment,a method for failure life cycle prediction of medical equipment was developed.The system is divided into four modules:the whole life cycle management module constructs the life cycle data set of medical devices from the three parts of the management in the early stage,the middle stage,and the later stage;the status detection module monitors the main operation data of the medical device components through the normal value of the relevant sensitive data in the whole life cycle management module;and the main function of the fault diagnosis module is based on the normal value of the relevant sensitive data in the whole life cycle management module.The inference machine diagnoses the operation data of the equipment;the fault prediction module constructs a fine prediction system based on the least square support vector machine algorithm and uses the AFS-ABC algorithm to optimize the model to obtain the optimal model with the regularized parameters and width parameters;the optimal model is then used to predict the failure of medical equipment.Comparative experiments are designed to determine whether or not the design system is effective.The results demonstrate that the suggested system accurately predicts the breakdown of ECG diagnostic equipment and incubators and has a high level of support and dependability.The design system has the minimum prediction error and the quickest program execution time compared to the comparison system.Hence,the design system is able to accurately predict the numerous causes and types of medical device failure.