Dynamic flight stability of hovering model insects:theory versus simulation using equations of motion coupled with Navier-Stokes equations

In the present paper, the longitudinal dynamic flight stability properties of two model insects are predicted by an approximate theory and computed by numerical sim- ulation. The theory is based on the averaged model （which assumes that the frequency of wingbeat is sufficiently higher than that of the body motion, so that the flapping wings＇ degrees of freedom relative to the body can be dropped and the wings can be replaced by wingbeat-cycle-average forces and moments）; the simulation solves the complete equations of motion coupled with the Navier-Stokes equations. Comparison between the theory and the simulation provides a test to the validity of the assumptions in the theory. One of the insects is a model dronefly which has relatively high wingbeat frequency （164 Hz） and the other is a model hawkmoth which has relatively low wingbeat frequency （26 Hz）. The results show that the averaged model is valid for the hawkmoth as well as for the dronefly. Since the wingbeat frequency of the hawkmoth is relatively low （the characteristic times of the natural modes of motion of the body divided by wingbeat period are relatively large） compared with many other insects, that the theory based on the averaged model is valid for the hawkmoth means that it could be valid for many insects.

Research regarding coal-bed wellbore stability based on a discrete element model

Wellbore instability is a key problem restricting efficient production of coal-bed methane. In order to perform thorough and systematic research regarding coal-bed wellbore stability problems, a new discrete element model which fully considers the features of cleat coal-beds is established based on the Kirsch equation. With this model, the safe pipe tripping speed, drilling fluid density window and coal- bed collapse/fracture pressure are determined; in addition, the relationships between pipe tripping speed and pipe size, cleat size, etc. and wellbore stability are analyzed in the coal-bed drilling and pipe tripping processes. The case studies show the following results： the wellbore collapses （collapse pressure： 4.33 MPa） or fractures （fracture pressure： 12.7 MPa） in certain directions as a result of swab or surge pressure when the pipe tripping speed is higher than a certain value; the cleat face size has a great influence on wellbore stability, and if the drilling fluid pressure is too low, the wellbore is prone to collapse when the ratio of the face cleat size to butt cleat size is reduced; however, if the drilling fluid pressure is high enough, the butt cleat size has no influence on the wellbore fracture; the factors influencing coal-bed stability include the movement length, pipe size, borehole size.

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.

MULTI-AXLE VEHICLE STABILITY BASED ON WHOLE VEHICLE MODEL

From the analysis of experiment data of the multi-axle vehicle chassis searching process, it is less accurate to predict multi-axle vehicle dynamic characteristic with simplified two-axle vehicle model. So it is important to find out a more effective modeling method in the study of multi-vehicle stability. In the development of heat transfer fluid（HTF） six-axle vehicle, a whole vehicle multi-body dynamic model is built through collaborate flowchart using Teamcenter Engineering, UG NX3 and MSC.Adams. The modeling method of connected hydragas spring suspension is validated by running test results. Based on this whole vehicle model, a kinematical analysis of suspension is implemented to achieve optimized suspension geometry parameters according to the stable requirement. Then, different handling simulations are carried out with regard to various tire characteristics, driving con- figurations, and equipments. According to the evaluation of whole vehicle handling characteristic, some design rules are summarized to improve the stability of multi-axle vehicle.

On the Stability of the Solution to a Gonorrhea Diserete Mathematical Model

In this paper, the author studies the stability of the solution to a three-dimension-al gonorrhea discrete mathematical model by Liapunoy method. The parameter es-timator of the slability domain is obtained and the rationality of the model is ex-plained in a theoretic way.

Assessment of pipeline stability in the Gulf of Mexico during hurricanes using dynamic analysis

Pipelines are the critical link between major offshore oil and gas developments and the mainland. Any inadequate on-bottom stability design could result in disruption and failure, having a devastating impact on the economy and environment. Predicting the stability behavior of offshore pipelines in hurricanes is therefore vital to the assessment of both new design and existing assets. The Gulf of Mexico has a very dense network of pipeline systems constructed on the seabed. During the last two decades, the Gulf of Mexico has experienced a series of strong hurricanes, which have destroyed, disrupted and destabilized many pipelines. This paper first reviews some of these engineering cases. Following that, three case studies are retrospectively simulated using an in-house developed program. The study utilizes the offshore pipeline and hurricane details to conduct a Dynamic Lateral Stability analysis, with the results providing evidence as to the accuracy of the modeling techniques developed.

Investigation of stability of a tunnel in a deep coal mine in China

Stability level of tunnels that exist in an underground mine has a great influence on the safety,production and economic performance of mines.Ensuring of stability for soft-rock tunnels is an important task for deep coal mines located in high in situ stress conditions.Using the available information on stratigraphy,geological structures,in situ stress measurements and geo-mechanical properties of intact rock and discontinuity interfaces,a three-dimensional numerical model was built by using 3DEC software to simulate the stress conditions around a tunnel located under high in situ stress conditions in a coal rock mass in China.Analyses were conducted for several tunnel shapes and rock support patterns.Results obtained for the distribution of failure zones,and stress and displacement felds around the tunnel were compared to select the best tunnel shape and support pattern to achieve the optimum stability conditions.

Effects of switching frequency and leakage inductance on slow-scale stability in a voltage controlled flyback converter

The effects of both the switching frequency and the leakage inductance on the slow-scale stability in a voltage controlled flyback converter are investigated in this paper. Firstly, the system description and its mathematical model are presented. Then, the improved averaged model, which covers both the switching frequency and the leakage inductance, is established, and the effects of these two parameters on the slow-scale stability in the system are analyzed. It is found that the occurrence of Hopf bifurcation in the system is the main reason for losing its slow-scale stability and both the switching frequency and the leakage inductance have an important effect on this slow-scale stability. Finally, the effectiveness of the improved averaged model and that of the corresponding theoretical analysis are confirmed by the simulation results and the experimental results.

A car-following model with the anticipation effect of potential lane changing

In this paper, a new car-following model is presented, taking into account the anticipation of potential lane changing by the leading vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg-de Vries （KdV） equation is constructed and solved, and three types of traffic flow in the headway-sensitivity space, namely stable, metastable and unstable ones, are classified. Both the analytical and simu- lation results show that anxiety about lane changing does indeed have an influence on driving behavior and that a consideration of lane changing probability in the car-following model could stabilize traffic flows. The quantitative relationship between stability improvement and lane changing probability is also investigated.

Analysis on Stability of AC,GT and PC in Rice Varieties (Orzya sativa L.)

The investigation of rice varieties stability for amylose content (AC), gelatinization temperature (GT) and protein content (PC) was carried out using additive main effects and multiplicative interaction (AMMI) model in three locations and two years. Eighteen tested varieties were further clustered and evaluated based on the phenotypic values of three quality traits and their Di values from the AMMI analysis. The results showed that the genotype by environment interactions, the differences of phenotype and stability of AC, GT and PC among different genotypes and environments were all significant at 1% level. Also, only one variety, W002, had high stability for all the three quality traits. Additionally, in consideration with the phenotype of AC, GT and PC, and their stability in rice varieties, etc., four rice varieties, W002, Zaofeng 9, Guangling Xiangjing and Nanjing16, could be also applied as breeding parents to improve eating quality and stability of rice.

Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model（NPM）. We propose that a proportional-derivative（PD） type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM.

Stability analysis and control synthesis of uncertain Roesser-type discrete-time two-dimensional systems

We study the stability analysis and control synthesis of uncertain discrete-time two-dimensional（2D） systems.The mathematical model of the discrete-time 2D system is established upon the well-known Roesser model,and the uncertainty phenomenon,which appears typically in practical environments,is modeled by a convex bounded（polytope type） uncertain domain.The stability analysis and control synthesis of uncertain discrete-time 2D systems are then developed by applying the Lyapunov stability theory.In the processes of stability analysis and control synthesis,the obtained stability/stabilzaition conditions become less conservative by applying some novel relaxed techniques.Moreover,the obtained results are formulated in the form of linear matrix inequalities,which can be easily solved via standard numerical software.Finally,numerical examples are given to demonstrate the effectiveness of the obtained results.

Effectiveness of predicting tunneling-induced ground settlements using machine learning methods with small datasets

Prediction of tunneling-induced ground settlements is an essential task,particularly for tunneling in urban settings.Ground settlements should be limited within a tolerable threshold to avoid damages to aboveground structures.Machine learning(ML)methods are becoming popular in many fields,including tunneling and underground excavations,as a powerful learning and predicting technique.However,the available datasets collected from a tunneling project are usually small from the perspective of applying ML methods.Can ML algorithms effectively predict tunneling-induced ground settlements when the available datasets are small?In this study,seven ML methods are utilized to predict tunneling-induced ground settlement using 14 contributing factors measured before or during tunnel excavation.These methods include multiple linear regression(MLR),decision tree(DT),random forest(RF),gradient boosting(GB),support vector regression(SVR),back-propagation neural network(BPNN),and permutation importancebased BPNN(PI-BPNN)models.All methods except BPNN and PI-BPNN are shallow-structure ML methods.The effectiveness of these seven ML approaches on small datasets is evaluated using model accuracy and stability.The model accuracy is measured by the coefficient of determination(R2)of training and testing datasets,and the stability of a learning algorithm indicates robust predictive performance.Also,the quantile error(QE)criterion is introduced to assess model predictive performance considering underpredictions and overpredictions.Our study reveals that the RF algorithm outperforms all the other models with the highest model prediction accuracy(0.9)and stability(3.0210^(-27)).Deep-structure ML models do not perform well for small datasets with relatively low model accuracy(0.59)and stability(5.76).The PI-BPNN architecture is proposed and designed for small datasets,showing better performance than typical BPNN.Six important contributing factors of ground settlements are identified,including tunnel depth,the distance between tunnel face and surface monitoring points(DTM),weighted average soil compressibility modulus(ACM),grouting pressure,penetrating rate and thrust force.

A stability condition for turbulence model:From EMMS model to EMMS-based turbulence model

The closure problem of turbulence is still a challenging issue in turbulence modeling. In this work, a stability condition is used to close turbulence. Specifically, we regard single-phase flow as a mixture of turbulent and non-turbulent fluids, separating the structure of turbulence. Subsequently, according to the picture of the turbulent eddy cascade, the energy contained in turbulent flow is decomposed into different parts and then quantified. A turbulence stability condition, similar to the principle of the energy-minimization multi-scale （EMMS） model for gas-solid systems, is formulated to close the dynamic constraint equa- tions of turbulence, allowing the inhomogeneous structural parameters of turbulence to be optimized. We name this model as the ＂EMMS-based turbulence model＂, and use it to construct the corresponding turbulent viscosity coefficient. To validate the EMMS-based turbulence model, it is used to simulate two classical benchmark problems, lid-driven cavity flow and turbulent flow with forced convection in an empty room, The numerical results show that the EMMS-hased turbulence model improves the accuracy of turbulence modeling due to it considers the principle of compromise in competition between viscosity and inertia.

A spatial model for the assessment of debris flow susceptibility along the Kodaikkanal-Palani traffic corridor

Debris flow is one of the most destructive water related mass movements that affects the development of mountain terrains.A reliable assessment of debris flow susceptibility requires adequate data,but in most developing countries like India,there is a dearth of such extensive scientific records.This study presents a novel approach for assessing debris flow using the analytical network process(ANP)in data insufficient regions.A stretch of hill road between Kumburvayal and Vadakaunchi along the Kodaikkanal-Palani Traffic Corridor(M171)was considered for this study.Five significant factors including the nature of slope forming materials,hydraulic conductivity,slope,vegetation,and drainage density were identified from intense field surveys and inspections in order to assess the susceptibility of the terrain to debris flow.This model endorsed the interdependencies between the selected factors.The resulting debris flow susceptibility map delineated regions highly prone to debris flow occurrences,which constituted nearly 23%of the selected road stretch.

Experimental and model investigations of SPS casing treatment on a two-stage compressor

This paper will first carry out experimental investigations on a test compressor which is a large-scale,two-stage and low-speed axial one to evaluate the participation of a novel casing treatment(stall precursor-suppressed casing treatment,SPS CT).The compressor performance for its pressure rise characteristics and efficiency are tested and illustrated.Besides,the time-averaged steady and the time-resolved unsteady measurement in this paper finally lead to some further analyses about the stall evolution of this compressor tending to uncover the process of the stall evolution and the mechanism of the SPS CT.The overall performance results indicate that the SPS CT can extend the compressor stall margin by 3%e11%with very limited efficiency loss.And the mechanism for such casing treatment has also been revealed as stall-precursor suppression by observing the evolution of the inception waves.In addition,modeling work have been conducted subject to the effects of SPS CT on the test two-stage axial compressor.The compressor stability model is able to investigate the effects of different geometrical parameters on the compressor stability and then make an optimal design for the SPS CT when it is applied on the test compressor.

Qualitative analysis of a stochastic SEITR epidemic model with multiple stages of infection and treatment

We present a mathematical analysis of the transmission of certain diseases using a stochastic susceptible-exposed-infectious-treated-recovered(SEITR)model with multiple stages of infection and treatment and explore the effects of treatments and external fluctuations in the transmission,treatment and recovery rates.We assume external fluctuations are caused by variability in the number of contacts between infected and susceptible individuals.It is shown that the expected number of secondary infections produced(in the absence of noise)reduces as treatment is introduced into the population.By defining RT,n and R T,n as the basic deterministic and stochastic reproduction numbers,respectively,in stage n of infection and treatment,we show mathematically that as the intensity of the noise in the transmission,treatment and recovery rates increases,the number of secondary cases of infection increases.The global stability of the disease-free and endemic equilibrium for the deterministic and stochastic SEITR models is also presented.The work presented is demonstrated using parameter values relevant to the transmission dynamics of Influenza in the United States from October 1,2018 through May 4,2019 influenza seasons.

A dynamic two-zone model of continuous fluidized bed layering granulation with internal product classification

A dynamic two-zone model is proposed to address the formation of granulation and drying zones in fluidized bed layering granulation processes with internal product classification. The model assumes a constant volume for the granulation zone, but a variable overall volume for the fluidized bed to account for classified product removal. The model is used to study the effect of various process parameters on dynamics and process stability. Stability is shown to depend on the separation diameter of product removal and the flow rate of the injected liquid. A lower and upper range of separation diameters with stable process behavior are found. In an intermediate range instability in the form of self-sustained oscillations is observed. The lower stability boundary is in qualitative agreement with recent experimental observations （Schmidt, Bück, ＆ Tsotsas, 2015）; the upper boundary was reported in a theoretical paper by Vreman, Van Lare, and Hounslow （2009） based on a single zone model.