Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

An action-based Markov chain modeling approach for predicting the window operating behavior in office spaces

Reliable energy and performance prediction for building design and planning is important for newly-designed or retrofitted buildings.Window operating behavior has an important influence on the ventilation and energy consumption of these buildings under different realistic scenarios.Therefore,quantitatively describing this behavior and constructing a prediction model are important.In this work,an action-based Markov chain modeling approach for predicting window operating behavior in office spaces was proposed.Two summer measurement data(2016 and 2018)were used to verify the accuracy and validity of the modeling approach.The opening rate,outdoor temperature,time distribution,and on-off curve were proposed as four inspection standards.This study also compared the prediction performance between the action-based Markov chain modeling approach with the state-based Markov chain modeling approach,which is the most popular modeling approach to model occupant window operating behavior.This study proved that the yearly variation of occupants’behavior performed a form of action that remained unchanged during a certain period.Meanwhile,the results also proved that the action-based Markov chain modeling approach can reflect the actual window operating behavior accurately within an open-plan office,which is a beneficial supplement for energy-consumption simulation software in a window-state prediction module.The state-based Markov chain modeling approach showed better stability and accuracy in terms of the opening rate,whereas the action-based Markov chain modeling approach showed good consistency with the measurement data in the on-off curves and in situations with little data.For the on-off curves,the accuracy of action-based modeling approach in the prediction of window open-state is 20%higher.

A Piecewise Modeling Approach for Climate Sensitivity Studies:Tests with a Shallow-Water Model

In model-based climate sensitivity studies, model errors may grow during continuous long-term inte- grations in both the ＂reference＂ and ＂perturbed＂ states and hence the climate sensitivity （defined as the difference between the two states）. To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.

Influence of modeling approaches and structural parameters on impact resistance of the human porous cranium

Failure mechanism and impact resistance of a human porous cranium are studied in detail by means of theoretical and numerical methods.It is hypothesized that pore distribution of a cranium directly affects cranial energy absorption,and a stretched beam model and a real beam model are taken as the example for the verification.Meanwhile,for the purpose of comparison with numerical results,a theoretical model is also proposed for the prediction of residual velocity and contact force of the impactor for an impacted skull.Compared with the real beam model,the stretched beam model containing through-thickness pores is easily deformed under the impact,thereby buffering well the external impact energy.The energy absorption efficiency of both the stretched beam model and real beam model is concerned with the threshold velocity for penetration which is directly related to the size of the structural damage area.Overall,there is good agreement between numerical and theoretical results.In addition,the effect of structural geometric parameters(shape and size of the impactor)on the impact resistance of the skull bone is theoretically investigated.The study provides reference for the evaluation of the energy absorption and failure mechanism of the skull under impact loads.

Influence of grain size on strength of polymineralic crystalline rock: New insights from DEM grain-based modeling

Grain size effect on rock strength is a topic of great interest in geotechnical engineering.A consensus obtained from earlier laboratory tests is that rock strength generally decreases with the increase of grain size for both silicate and carbonate rocks;however,some recent numerical results conflict with such laboratory test results.To address this intriguing issue,the effect of grain size on strength of polymineralic crystalline rock with low porosity is investigated numerically using the grain-based modeling(GBM)approach in discrete element method(DEM)by interpreting micro-cracking process in response to loading.In agreement with some previous DEM simulation results,the simulated rock strength is found to increase with increasing grain size for both homogeneous and heterogeneous models,even when the number of assembled disks in one mineral grain changes.The mechanism of strength increase with increasing grain size is mainly associated with the number of assembled smooth-joint contacts along grain interfaces and the generation of grain boundary cracks in response to loading.The grain interfaces significantly weaken the integrity of the rock model,which is similar to effects of inherent defects in real rock.As the grain size increases,fewer grain interfaces are built in the model and the rock strength becomes much higher.Hence,by solely changing the mineral grain size in a model,the mechanism of grain size effect as observed in laboratory tests cannot be replicated.To address this issue,a method of degradation of grain boundary strength parameters is used to mimic the possible mechanism of grain size effect.The simulated strength using the method becomes comparable with those obtained from laboratory tests when the heterogeneity in the rock is considered.Degradation of grain boundary parameters with increasing grain size provides a plausible explanation for the grain size effect on rock strength.

An Agent-Oriented Modelling Approach for Agile Manufacturing

The dynamic variations in demand patterns and produ ct mix, driven by unpredictable changes in a global market, are placing manufactur ing systems under significant pressure. In order to remain competitive, manu facturing organisations must satisfy demands timely. This implies that companies must increase product varieties, reduce time-to-market, shorten product-life cycles and at the same time maintain good quality and reduce investment costs. Conventional methodologies for planning and control have been found to be inadeq uate in meeting these challenges. Agile manufacturing is the state-of-the-art concept that provides enterprises with the opportunity to react rapidly and cos t-effectively to changes that occur in their environment. Several paradigms suc h as Holonic Manufacturing Systems (HMS), Bionic Manufacturing Systems (BMS) and Fractal Factory have been developed to enable manufacturing systems achieve agi lity by integrating manufacturing activities into a coordinated framework. Despi te the differences in their origin (HMS from social organisation, BMS from biolo gy and Fractal Factory from Mathematics), these paradigms have overlapping conce pts and one of the most important is hierarchical organisational structure. This paper presents a conceptual hierarchically structured multi-agent architec ture for manufacturing systems’ modelling. Multi-Agent Systems (MAS) provide su itable techniques for implementing the above concepts and as a branch of Distrib uted Artificial Intelligence (DAI), have characteristics that have been explored in various applications. Such characteristics include self-organisation, flexi bility, scalability, and robustness. The proposed architecture provides a suit able decision-making framework where each agent represents a node in the hier archic tree of manufacturing systems such as the company as whole, each plant wi thin the company, each cell or line within the plant, each machine in a cell or line. Each agent has the ability to perceive and evaluate changes that occur in the manufacturing environment, interact with other agents in the system in order to reach an optimal decision, and act based on that decision. In other words, agents respond timely to unexpected changes by continuously co-ordinating t heir activities, and allocating manufacturing resources dynamically based on act ual shop-floor situation. The flexibility of this architecture also lies in its ability to accommodate both homogenous and heterogeneous agents, and its capabi lity for the dynamic addition and removal of agents using a conceptual intellige nt communication mechanism similar to the blackboard messaging system. A Bidding -Based Scheme (BBS) would be used to generate and evaluate alternative scenario at run-time. In addition, this architecture can be extended to meet the requir ements of enterprise integration.

Possible Modular Structure of Matter Based on the “YY Model” Approach —An Overview of the Construction Rules for Quarks and Atomic Nuclei with Configurative Examples for Neutron, Proton, Deuteron and Dineutron

The newly developed YY model contains a set of constitutive rules to describe the structures of atomic nuclei and subatomic particles, by using two elementary sub-quark particles, the Yin and Yang fermions of charge 1/3 forming all the particles of the Standard Model. This model suggests a modular structure of the universe, in which two elementary constituents recursively form all the matter. The advantage of this hypothesis is that it provides a total symmetry and a noticeably clear conceptual understanding. Moreover, it justifies the cosmological formation of a limited number of atoms, e.g., H and Li with their isotopes, considering that matter can be produced as a free agglomerate of semi-stable neutrons, which would lead to the feeding of baryonic matter in the universe. In this current article, some further theoretical aspects are proposed as an evolution of the YY model. They cover correlation paths between interacting quarks, the considerations of color forces between yin-yang elementary elements. Moreover, an agreement of the YY model with the Teplov approach based on harmonic quarks and oscillators is established, and the mass of Yin and Yang is considered. Two example nuclei are used for the analysis: a radioactively stable deuteron (containing a neutron and a proton) and a possible semi-stable dineutron (roughly “consisting of two neutrons”), which is purely theoretical, represent a very natural and legal nuclear state within YY model. Based on the results obtained here, some indications are given for a possible simple experimental verification providing proof for the stability or instability of the dineutron.

Earthquake motion input and its dissemination via the Internet

Objectives of this task are to conduct research on seismic hazards,and to provide relevant input on the expected levels of these hazards to other tasks.Other tasks requiring this input include those dealing with inventory,fragility curves, rehabilitation strategies and demonstration projects.The corresponding input is provided in various formats depending on the intended use:as peak ground motion parameters and/or response spectral values for a given magnitude,epicentral distance and site conditions;or as time histories for scenario earthquakes that are selected based on the disaggregated seismic hazard mapped by the U.S.Geological Survey and are incorporated in building codes.The user community for this research is both academic researchers and practicing engineers who may use the seismic input generated by the synthesis techniques that are developed under this task for a variety of applications.These include ground motions for scenario earthquakes,for developing fragility curves and in specifying ground motion input for critical facilities (such as hospitals) located in the eastern U.S.

Loss of Certified Maize (<i>Zea mays</i>L.) and Cowpea (<i>Vigna unguiculata</i>(L.) Walp.) Seed Viability during Storage in a Sub-Saharan Region: Analysis of Environmental Factors

The objective of this study was to characterize environment factors involved in loss of seed viability during storage in open granaries. The temperature and relative humidity of the granary as well as the equilibrium moisture content of seeds were determined monthly. Their effects on the loss of viability of maize (Zea mays L.) and cowpea (Vigna unguiculata (L.) Walp.) seeds were examined. The results showed that relative humidity levels > 65% associated with temperatures > 25°C (conditions in the open granary) do not guarantee safe storage of maize lots for a period of 9 to 12 months. Based on these data and the results of seed viability analysis, local environmental conditions in Gandajika (DR-Congo) and seed genetic background are the main factors for the rapid deterioration of seeds during storage. The germination rate correlated negatively with storage duration (-0.94) and temperature (-0.57) while it correlates positively with the relative humidity (0.58) for both lots of maize analyzed. The same trend was observed with the two-cowpea varieties studied (IT82D-889 and Diamant). Similar work using more varieties in other granaries is required to validate key factors involved in seed viability during storage in targeted regions.

Progress in the study of animal models of atherosclerosis

Atherosclerosis is corporate in clinical practice,and it can cause a series of complications such as coronary heart disease,which seriously threatens human health.Due to the relatively complex factors of its treatment,there is no exact etiology at present.It is essential to establish an animal model of atherosclerosis that can be evaluated and reproducible to study its pathogenesis and clinical treatment guidance.This article reviews the selection of atherosclerotic model animals and the established methods of models to explore more in-depth research and clinical practice of atherosclerosis.

A Novel FPSM Controller for DC-DC Switching Converters

This paper presents a novel fuzzy pulse skip modulation （FPSM） controller for switching direct current to direct current （DC-DC） converters based on fuzzy ratiocination modeling approach. Owing to the optimal consideration during the design and the nonlinear characteristics of the controller, improved dynamic responses of the FPSM controller can be achieved over conventional controllers. Compared with conventional proportion integral derivative （PID） control, FPSM control has 60% lower overshoot and 10% lower setting time under the same input voltage and output load change. The presented approach is general and can be applied to other types of DC-DC converters.

Nonlinear System Identification with Unknown Piecewise Time-Varying Delay

Identification of nonlinear systems with unknown piecewise time-varying delay is concerned in this paper.Multiple auto regressive exogenous(ARX) models are identified at different process operating points,and the complete dynamics of the nonlinear system is represented by using a combination of a normalized exponential function as the probability density function with each of the local models.The parameters of the local ARX models and the exponential functions as well as the unknown piecewise time-varying delays are estimated simultaneously under the framework of the expectation maximization(EM) algorithm.A simulation example is applied to demonstrating the proposed identification method.

AN APPROACH TO MATHEMATICAL MODELING OF PIPING SYSTEM WITH FLUID-STRUCTURE INTERACTION

The present paper studies the dynamic pehaviour of a complex piping system containing internal fluid flow.A generalized complex modal decomposition method is proposed for modeling the piping structure.A characteristic impedance transfer matrix of piping flow with a frequency-dependent friction is employed for describing the model of fluid flow,which is coupled to the structural model by means of an approach similar to that used in the structural modal synthesis.The coupled model is practicable for the detecting,monitoring,controlling or predicting of piping vibrations,and for the studying of fluid dynamic characteristics under the influence of structural vibration,also for the diagnosticating of the piping system.

Resonances for positron–helium and positron–lithium systems in kappa-distribution plasma

S-wave resonances of positron–helium and positron–lithium systems in kappa-distribution plasmas are investigated using Hylleraas-type wave functions in the framework of the stabilization method. A model potential approach is used to represent the interactions between the outer electron, the positron and the core. The resonance parameters(position and width) of positron–helium and positron–lithium systems below the Ps(2s) threshold are reported as a function of screening parameter and spectral index of plasma.

WHU-Grace01s:A new temporal gravity field model recovered from GRACE KBRR data alone

A new temporal gravity field model called WHU-Grace01s solely recovered from Gravity Recovery and Climate Experiment （GRACE） K-Band Range Rate （KBRR） data based on dynamic integral approach is presented in this paper. After meticulously preprocessing of the GRACE KBRR data, the root mean square of its post residuals is about 0.2 micrometers per second, and seventy-two monthly temporal solutions truncated to degree and order 60 are computed for the period from January 2003 to December 2008. After applying the combi- nation filter in WHU-Grace01s, the global temporal signals show obvious periodical change rules in the large-scale fiver basins. In terms of the degree variance, our solution is smaller at high degrees, and shows a good consistency at the rest of degrees with the Release 05 models from Center for Space Research （CSR）, GeoForschungsZentrum Potsdam （GFZ） and Jet Pro- pulsion Laboratory 0PL）. Compared with other published models in terms of equivalent water height distribution, our solution is consistent with those published by CSR, GFZ, JPL, Delft institute of Earth Observation and Space system （DEOS）, Tongji University （Tongji）, Institute of Theoretical Geodesy （ITG）, Astronomical Institute in University of Bern （AIUB） and Groupe de Recherche de Geodesie Spatiale （GRGS}, which indicates that the accuracy of WHU-Grace01s has a good consistency with the previously published GRACE solutions.

Design and modeling of a novel soft parallel robot driven by endoskeleton pneumatic artificial muscles

Owing to their inherent great flexibility, good compliance, excellent adaptability, and safe interactivity, soft robots have shown great application potential. The advantages of light weight, high efficiency, non-polluting characteristic, and environmental adaptability provide pneumatic soft robots an important position in the field of soft robots. In this paper, a soft robot with 10 soft modules, comprising three uniformly distributed endoskeleton pneumatic artificial muscles, was developed. The robot can achieve flexible motion in 3D space. A novel kinematic modeling method for variable-curvature soft robots based on the minimum energy method was investigated, which can accurately and efficiently analyze forward and inverse kinematics. Experiments show that the robot can be controlled to move to the desired position based on the proposed model. The prototype and modeling method can provide a new perspective for soft robot design, modeling, and control.

A Sliding Mode Observer for Uncertain Nonlinear Systems Based on Multiple Models Approach

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters＇ variations of the nonlinear system. Linear matri~ inequalities （LMIs） have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.

A model-driven approach to semi-structured database design

Recently XML has become a standard for data representation and the preferred method of encoding struc- tured data for exchange over the Internet. Moreover it is fre- quently used as a logical format to store structured and semi- structured data in databases. We propose a model-driven and configurable approach for modeling hierarchical XML data using object role modeling （ORM） as a flat conceptual model. First a non-hierarchical conceptual schema of the problem domain is built using ORM and then different hierarchical views of the conceptual schema or parts of it are specified by the designer using transformation rules. A hierarchical mod- eling notation called H-ORM is proposed to show these hier- archical views and model more complex semi-structured data constructs and constraints. We also propose an algorithm to map hierarchical H-ORM views to XML schema language.

Modeling of two-phase particulate flows in a confined jet with a focus on two-way coupling

A computational fluid dynamics model is used for the simulation of laminar flow ofwater-Al2O3 nanofluid in a confined slot impinging jet. The （steady-state and two-dimensional） Eulerian-Lagrangian model is used considering fluid-particle and particle-wall interactions （i.e., two-way coupling）. A collocated grid and the SIMPLE algorithm are used for the coupling of pressure and velocity fields. The deposition model is used to investigate the effect of particle deposition on the impingement surface. Results indicate that the particle trajectory becomes stable farther from the jet with a rising Reynolds number and jet- impingement surface distance ratio. The heat transfer coefficient of the mixture model is higher than that of the Eulerian-Lagrangican model.

A comprehensive review on coupled processes and mechanisms of soil-vegetation-hydrology, and recent research advances

Research on the coupling of soil,vegetation,and hydrological processes is not only a research hotspot in disciplines such as pedology,ecohydrology and Earth system science but also important for achieving sustainable development.However,scientists from different disciplines usually study the coupling mechanism of soil-vegetation-hydrological processes at very different space and time scales,and the mechanistic connections between different scales are quite few.This article reviewed research advances in coupled soil-vegetation-hydrological processes at different spatial scales—from leaf stomata to watershed and regional scales—and summarized the spatial upscaling methods and modeling approaches of coupled soil-vegetationhydrological processes.We identify and summarize the following coupling processes:(1)carbon-water exchange in leaf stomata and root-soil interface;(2)changes in soil aggregates and profile hydraulic properties caused by plant roots and water movement;(3)precipitation and soil moisture redistribution by plant canopy and root;(4)interactions between vegetation patches and local hydrological process;(5)links between plant community succession and soil development;and(6)links between watershed/regional water budget and vegetation phenology and production.Meanwhile,the limitations and knowledge gaps in the observations,mechanisms,scaling methods,and modeling approaches of coupled soil-vegetation-hydrological processes were analyzed.To achieve a deep integration of various coupling processes across different spatiotemporal scales,future work should strengthen multiscale,multifactor and multiprocess soil-vegetation-hydrology coupling observations and mechanism studies,develop new scaling methods,identify different feedback pathways,and take time-variable plant behavior and soil hydraulic properties into account during modeling.