A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

The Altitudinal Belts of Subalpine Virgin Forest on Mt.Gongga Simulated by a Succession Model

How to accurately simulate the distribution of forest species based upon their biological attributes has been a traditional biogeographical issue.Forest gap models are very useful tools for examining the dynamics of forest succession and revealing the species structure of vegetation.In the present study,the GFSM(Gongga Forest Succession Model) was developed and applied to simulate the distribution,composition and succession process of forests in 100 m elevation intervals.The results indicate that the simulated results of the tree species,quantities of the different types of trees,tree age and differences in DBH(diameter at breast height) composition were in line with the actual situation from 1400 to 3700 MASL(meters above sea level) on the eastern slope of Mt.Gongga.Moreover,the dominant species in the simulated results were the same as those in the surveyed database.Thus,the GFSM model can best simulate the features of forest dynamics and structure in the natural conditions of Mt.Gongga.The work provides a new approach to studying the structure and distribution characteristics of mountain ecosystems in varied elevations.Moreover,the results of this study suggest that the biogeochemistry mechanism model should be combined with the forestsuccession model to facilitate the ecological model in simulating the physical and chemical processes involved.

A succession and silviculture model for the broad-leaved Korean pine forests of Changbai Mountain Area

A succession and silviculture model (ZELIG.CBA) for broad-leaved Korean pine forest of Changbai Moutain Area was developed based on the framework of ZELIG model and characteristics of Broad-leaved Korean pine forests of Changbai area. ZELIG.CBA model consists four sub-models: growth model simulating annual increment of individual tree in forest, regeneration model simulating annual establishment of different tree species, mortality model simulating annual agerelated and stress-related morality; and silviculture model simulating the forest response to different silviculture scenario. The validation of the ZELIG.CBA showed that the accuracy of the model for the forest growth was more than 95%. The succession from clear cutting site simulating showed that the ZELIG.CBA model was stable for long term simulation. And selective cutting experiment showed that the optimal scenario for broad-leaved Korean pine forests was removal volume 30% combining with 30a rotation.

Simulating responses of Northeastern China forests to potential climate change

A simulation study on the responses of forests in Northeastern China to possible climate change was done by running NEWCOP, a computer model of forest stands “gap” dynamics with a set of parameters of 24 tree species. Based on the simulation, climate change will continue to make coniferous trees less and less and deciduous trees more and more. By the end of 100a transient process and 100a equilibrium climate period, forest biomass is reduced by a total of 6,531 million t dry material for the whole region of NE China. There is only a small area in the north on which there stands more biomass than without climate change. Korean pine will be first tree species which decrease by the most amount. In the northern part of NE China, oak forest will cover much more area with climate change and the larch forest may cover less area than it does at present. In the middle part areas, coniferous and broad-leaved mixed forest will remain, but the portion of deciduous species in composition of forest will increase. In the southem part areas, Korean pine will become companion tree species and its distribution area will greatly decrease.

Succession Features and Dynamic Simulation of Subalpine Forest in the Gongga Mountain, China

The Gongga Mountain of eastern Tibet Plateau is a representative of the alpine regions with high peaks and deep valleys. Climate change over the last thousand years has controlled the dynamics of glacier and debris flow occurrence, which resulted in substantial changes in the mountainous environment. The authors surveyed the community structure of primary forests in Gongga Mountain and forest succession processes in woodland plots. The changing features in the subalpine environment are discussed in this paper. Tree species and sizes between the glacier shrinking areas and debris flow fans in Hailuogou Valley are compared. The pioneer species that settle in debris flow fans and the glacier shrinking areas are Salix spp. and Populus purdomii. Abies fabri and Picea brachytyla are the climax tree species. The succession process of primary vegetation in Hailuogou (2700 ~ 3200 m) can be divided into four stages: Slash surface (20~ 200 yr) Salix-Populus seeding community (10 ~ 30 yr) Populus-Salix sapling community (30 ~ 100 yr) Populus-Abies mixed community (50 ~ 100 yr) Abies-Picea climax In a natural and undisturbed environment, trees compete for light, water and nutrients. Disaster disturbance in mountains is a very important driving factor for regeneration of woody plants. Repeated destruction of forests by glacier movement or debris flows generated additional forest gaps that allow young plants to grow. In this study the Gongga Forest Succession Model (GFSM) was developed for simulation of forest community succession processes on different scales in Gongga Mountain. A soil succession module was added to the GFSM model to simulate soil formation and chemical element change of woodland. In order to represent major features of forests in Southwestern China, many field works has been done to identify ecological parameters of various trees in the subalpine region. On the basis of simulation of tree life history, the GFSM combines forest succession with soil change in both material components and nutrition content. The Monte-Carlo method was applied to simulate random weather fluctuation and the uncertainty of tree death. These modeled processes agreed with the field investigation results in this region. The elevation distribution of different tree species was also simulated; and the results are consistent with field observations of ecological features of tree species. The modeling approach reflects well the succession dynamics of primary forests in Southwestern China. These results are very useful for improving the management policies and prediction technology for restoration and conservation of primary forests in Southwestern China.

Simulating sensitivities of Changbai Mountain forests to potential climate change

Changbai Mt. forest in the northeastern China is both a very important timber resource of China and one of the most typical and less disturbed temperate mixed evergreen coniferous-deciduous forest in the world.In this paper, NEWCOP. a gap class model of forest growth and succession was proposed to simulate the sensitivity of the forest in Changbai Mountain to elevate CO_2. warmer temperature and precipitation change. NEWCOP was tested on long term simulation behaviors and short term fitting ability to field data. About the response of forests of Changbai Mountain to possible climate change, NEWCOP suggested that forest landscape go up within long term and forest biomass comes down within short term because of dieback of forest trees.

Dynamic Control of Defective Gap Mode Through Defect Location

A one dimensional model is developed for defective gap mode（DGM）with two types of boundary conditions：conducting mesh and conducting sleeve.For a periodically modulated system without defect,the normalized width of spectral gaps equals to the modulation factor,which is consistent with previous studies.For a periodic system with local defects introduced by the boundary conditions,it shows that the conducting-mesh-induced DGM is always well confined by spectral gaps while the conducting-sleeve-induced DGM is not.The defect location can be a useful tool to dynamically control the frequency and spatial periodicity of DGM inside spectral gaps.This controllability can be potentially applied to the interaction between gap eigenmodes and energetic particles in fusion plasmas,and optical microcavities and waveguides in photonic crystals.

A bi-directional gap model for simulating the directional thermal radiance of row crops

Row crops are a kind of typical vegetation canopy between discrete canopy and continuous canopy.Kimes et al.studied the directional thermal radiation of row crops using the geometrical optical model,which simplified row structure as'box'and neglected the gap among foliage and did not consider the emissivity effects.In this work we take account of the gaps along illumination and viewing directions and propose a bi-direction gap model on the basis of the idea of gap probability of discrete vegetation canopy introduced by'Li-Strahler'and inter-correlation of continuous vegetation developed by Kuusk.It can be used to explain'hot spot'effects in thermal infrared region.The gap model has been validated by field experiment on winter wheat planted in shape of rows and results show that the gap model is better than Kimes'model in describing the directionality of thermal infrared emission for row crops.

Gap Model for Dual Customer Values

The customer value, the key problem in customer relationship management （CRM）, was studied to construct a gap model for dual customer values. A basic description of customer values is given, and then the gaps between products and services in different periods for the customers and companies are analyzed based on the product or service life-cycle. The main factors that influence the perceived customer value were analyzed to define the ＂recognized value gap＂ and a gap model for the dual customer values was constructed to supply companies with a tool to analyze existing customer value gaps and improve customer relationship management.

The Proportional Hazards Model for Multiple Type Recurrent Gap Times

Recurrent events data and gap times between recurrent events are frequently encountered in many clinical and observational studies,and often more than one type of recurrent events is of interest.In this paper,we consider a proportional hazards model for multiple type recurrent gap times data to assess the effect of covaxiates on the censored event processes of interest.An estimating equation approach is used to obtain the estimators of regression coefficients and baseline cumulative hazard functions.We examine asymptotic properties of the proposed estimators.Finite sample properties of these estimators are demonstrated by simulations.

Using Huntingtin Knock-In Minipigs to Fill the Gap Between Mouse Models and Patients with Huntington's Disease

Huntington＇s disease （HD） is an inherited autosomal dominant neurodegenerative disease characterized by pro- gressive motor deficits, cognitive decline, and psychiatric symptoms. It is caused by a pathological expansion of CAG trinucleotide repeats in exon 1 of the HD gene, resulting in the translation of a mutant form of huntingtin protein （mutant Htt） with an expanded polyglutamine domain in the N-terminal region [1 ]. Despite great progress in understanding the pathogenesis of HD using multiple mouse models, the exact mechanisms by which mutant Htt induces neuronal dysfunction and death are still not completely clear, and there is no curative treatment for this disease. An important reason is that the mouse, which is the most widely used animal model in HD research, differs from the human in many aspects, including the physiology, drug metabolism, blood-brain barrier, life span, brain volume, and neuroanatomical organization [2]. Thus, it is necessary to establish HD models with higher species than rodents, such as the dog, pig, and non- human primate, so as to bridge the gap between preclinical mouse models and clinical studies.

Roll gap prediction in acceleration and deceleration process of cold rolling based on a data-driven method

Severe fluctuation of the effective roll gap in the acceleration and deceleration section of the cold rolling process is a significant factor causing thickness deviation.However,the conventional roll gap compensation method and control strategy do not meet the stringent strip quality requirements.The roll gap model in the acceleration and deceleration process is studied to increase the thickness control precision.In order to improve model accuracy,a roll gap prediction method based on data-driven is proposed.Given the complexities of the cold rolling process,the extreme gradient boosting(XGBoost)method is used to predict the roll gap model as the rolling speed changes.Meanwhile,support vector regression and neural network-based methods are taken to evaluate and compare the prediction performances.Based on the field data,the simulation experiments are carried out.It demonstrated that the prediction performance of the proposed method outperformed the other two methods.The values of root mean square error,determination coefficient value,mean absolute percentage error and mean absolute error obtained from the XGBoost model were equal to 0.000346,0.952,7.02,and 0.00028,respectively.In addition,the proposed method analyzed the contribution rates of the rolling affecting parameters on the roll gap.The data showed that in the controllable rolling parameters,the rolling speed is the most impacting factor that disturbs the roll gap model in the acceleration and deceleration process,which can provide a useful direction for actual roll gap adjustment.

On interest-rate risk management of postal savings bureau

This article analyzes interest-rate risks faced by the postal savings bureau （PSB） based on the complete balance sheet. It presents the extended gap model and the extended duration gap model to measure the interest-rate risk, and discusses the inner balance-sheet strategies and the off-balance-sheet strategies to manage the interest-rate risks.