Explicit Dynamic Model Research Articles

Financial Instability and Banking Crises in a Small Open Economy

The present paper seeks to investigate the importance of financial instability during four banking crises, with focus on the small open economy of Norway. The crises elaborated on are the Post First world war crisis of the early 1920s, the mid 1920s Monetary crisis, the Great Depression of the 1930s and the Scandinavian banking crisis of 1987-1993. The paper firstly offers a brief description of the financial instability hypothesis as applied by Minsky, Kindleberger, and in a new explicit dynamic financial crisis model. Financial instability creation basically happens in times of overheating, overspending and over lending, i.e., during significant booms, and have devastating effects after markets have turned into a state of crises. Thereafter, the paper tests the validity of the financial instability hypothesis by using a quantitative structural time series model. The test reveals upheaval of financial and macroeconomic indicators prior to the crises, making the economy overheat and create asset bubbles due to huge growth in debt. These conditions caused the following banking crises. Finally, the four crises are discussed qualitatively. The conclusion is that significant increase in money supply and debt caused overheating, asset bubbles and finally financial and banking crises which spread to the real economy.

A price dynamic equilibrium model with trading volume weights based on a price-volume probability wave differential equation

Guided by a price-volume probability wave differential equation in a new mathematical method, we study intraday market dynamic equilibrium in stock market. We select intraday cumulative trading volume distribution over a price range as individual mental representation and determine a price equilibrium point by the maximum volume utility price. We propose the hypothesis that a stock price can deviate away from the equilibrium point in momentum and restore to it in reversal, and the volume distribution embodies market dynamic equilibrium. Then, we examine it by a set of explicit price dynamic equilibrium models with trading volume weights from the differential equation against a large number of the price-volume distribution using tick-by-tick high frequency data in Chinese stock market in 2019. It holds true. We can infer that the theory is applied for a broader scope because it embraces core mathematical components in expected utility theory, prospect theory, and reflexivity theory.

Data-Driven Control of Soft Robots Using Koopman Operator Theory

Controlling soft robots with precision is a challenge due to the difficulty of constructing models that are amenable to model-based control design techniques. Koopman operator theory offers a way to construct explicit dynamical models of soft robots and to control them using established model-based control methods. This approach is data driven, yet yields an explicit control-oriented model rather than just a “black-box” input-output mapping. This work describes a Koopman-based system identification method and its application to model predictive control (MPC) design for soft robots. Three MPC controllers are developed for a pneumatic soft robot arm via the Koopman-based approach, and their performances are evaluated with respect to several real-world trajectory following tasks. In terms of average tracking error, these Koopman-based controllers are more than three times more accurate than a benchmark MPC controller based on a linear state-space model of the same system, demonstrating the utility of the Koopman approach in controlling real soft robots.

A dynamic constitutive model of ultra high toughness cementitious composites

In this study, an explicit dynamic constitutive model was established for ultra high toughness cementitious composites (UHTCCs). The model, based on the Holmquist–Johnson–Cook (HJC) model, includes tensile and compressive damage evolution, hydrostatic pressure, strain rate, and the Lode angle effect. The proposed model was embedded in LS-DYNA software and then comprehensive tests were carried on a hexahedral brick element formulation under uniaxial, biaxial, and triaxial stress states to verify its rationality through comparisons with results determined by the HJC and Karagozian & Case (K&C) models. Finally, the proposed model was used to simulate the damage caused to UHTCC targets subjected to blast by embedded explosive and projectile penetration, and predictions were compared with corresponding experimental results. The results of the numerical simulations showed that our proposed model was more accurate than the HJC model in predicting the size of the crater, penetration depth, and the distribution of cracks inside the target following the blast or high-speed impact loading.

Experiment and simulation research of forklift roof guard dynamic load test based on LS-DYNA

In order to solve the problems that the driver is threatened by accidental falling objects during forklift operation, according to the requirements of international standard ISO 6055:2004 for dynamic load test of forklift roof guard, the explicit dynamic calculation model of dynamic load simulation test was established based on LS-DYNA, and the dynamic load test was carried out at the same time. The maximum permanent deformation of roof guard is 13.5mm and 11.8mm, respectively, in the simulation and test results of dynamic load. The simulation analysis and test results show that this forklift roof guard has good deformation resistance and safety performance. And the data consistency is good, both of which meet the requirements of test standards. The results provide more design schemes and references for the structure of forklift roof guard.

Feedback Analysis of Test Anxiety and Academic Performance Among Students

Previous research has shown that test anxiety among students affects academic performance. Understanding the feedback mechanisms underlying the dynamics of test anxiety and academic performance among students will inform the development of interventions to cut the prevalence of text anxiety. Many theories have been proposed to explain the underlying causes of text anxiety and academic performance. In this research, the authors sought to synthesize the dominate theories of test anxiety and academic performance (i.e., cognitive attention model, learning deficit model, dual deficit model, and social learning model) and translate it into an explicit system dynamic simulation model that captures the main feedback loops. Simulation experiments were implement using synthetic data and variation of few parameters in the experiments produced realistic trajectories of students' academic performance.

A Bayesian network approach to trophic metacommunities shows that habitat loss accelerates top species extinctions.

We develop a novel approach to analyse trophic metacommunities, which allows us to explore how progressive habitat loss affects food webs. Our method combines classic metapopulation models on fragmented landscapes with a Bayesian network representation of trophic interactions for calculating local extinction rates. This means that we can repurpose known results from classic metapopulation theory for trophic metacommunities, such as ranking the habitat patches of the landscape with respect to their importance to the persistence of the metacommunity as a whole. We use this to study the effects of habitat loss, both on model communities and the plant‐mammal Serengeti food web dataset as a case study. Combining straightforward parameterisability with computational efficiency, our method permits the analysis of species‐rich food webs over large landscapes, with hundreds or even thousands of species and habitat patches, while still retaining much of the flexibility of explicit dynamical models.

A Price Dynamic Equilibrium Model with Trading Volume Weights Based on a Price-Volume Probability Wave Differential Equation

Guided by a price-volume probability wave differential equation in a new mathematical method, we study intraday market dynamic equilibrium in stock market. We select intraday cumulative trading volume distribution over a price range for individual mental representation and determine a price equilibrium point by the maximum volume utility price. We propose the hypothesis that a stock price can deviate away from the equilibrium point in momentum and restore to it in reversal, and the volume distribution embodies market dynamic equilibrium. Then, we examine it by a set of explicit price dynamic equilibrium models with trading volume weights from the differential equation against a large number of the price-volume distribution using tick-by-tick high frequency data in Chinese stock market in 2019. It holds true. We can infer that the theory is applied for a broader scope because it embraces core mathematical components in expected utility theory, prospect theory, and reflexivity theory.

Modeling the Role of Root Exudation in Critical Zone Nutrient Dynamics

AbstractThe multifaceted interface of plant roots, microbes, water, and soil can be considered a critical zone within the Critical Zone as it is host to many important dynamically linked processes, including the promotion of nutrient cycling through absorption and rhizodeposition, interaction and feedbacks with microorganisms and fungi, root‐facilitated hydraulic redistribution, and soil carbon dynamics. Such important processes in the Critical Zone have not been fully characterized and modeled in an ecohydrologic framework linking above‐ground natural and/or anthropogenic processes to below‐ground biogeochemical cycling. Specifically, the relation between root exudates and nutrient cycling remains an open challenge. Here we present the model REWT (Root Exudation in Watershed‐scale Transport) to demonstrate the systematic modeling of root exudation in an interconnected ecohydrologic framework. REWT incorporates an explicit dynamic root exudation transport model, nutrient absorption, and coupled microbial processes within the framework of a validated ecohydrologic model. Model simulations demonstrate the influence of root exudation of glucose, a polysaccharide that serves as fuel for microbes, and flavonoids, which can act as a biological nitrification inhibitor on microbial processes linked to soil carbon and nitrogen cycling. To demonstrate the capabilities of this theoretical framework, we parameterize REWT for corn and soybean crops in the Midwestern United States, and simulations indicate that rates of nitrification and respiration were substantially altered compared to model simulations in which root exudation was not explicitly included. This work demonstrates the importance of systematically incorporating root exudates into hydrobiogeochemical models and can serve to inform experimental design for active root zone processes.

Development and application of numerical simulation and experiment for studying the compressive forming technology of transmission lines

In this paper, an explicit dynamic finite element model is built to study the compressive forming technology used in the metal connector of transmission lines of power system. Additionally, to improve the calculation accuracy, an optimized reversed calculation method for determining the equivalent friction coefficients is designed and coupled into the dynamic finite element model. It is validated with a carefully designed experiment that the coupled dynamic finite element model is effective in describing the plastic flow and in determining the grip strength of the compressive forming structure. Finally, with the dynamic finite element model, an optimized compressive forming process window is obtained for controlling the formation of edge flaws while keeping sufficient grip strength.

Design optimization of a business aircraft seat considering static and dynamic certification loading and manufacturability

A conceptual design for a lightweight business aircraft seat was developed using topology optimization in a 2-stage approach to consider both the static and dynamic certification test requirements of the Canadian Aviation Regulations (CARs) Section 525.561 and 525.562, respectively. Preliminary optimization was performed using static load requirements, and the interpretation of the optimization results was done considering key manufacturability metrics to reduce the cost of manufacturing components when using traditional subtractive manufacturing methods. A series of explicit dynamic models was run to predict the behavior of the seat during 14g and 16g certification tests and to estimate the maximum loads which the anthropomorphic test device (ATD) applies to the seat structure. Peak seatbelt loads were estimated at 9060 N and 8955 N for the left and right sides, respectively, and the asymmetry of the loads can be attributed to the 10° yaw of the aircraft required by the 16g certification test. Topology optimization was used to refine the design at the component level and further reduce weight using the loads determined in the dynamic modeling. The final conceptual design was 32% lighter when compared with the baseline structural components, and key manufacturability cost metrics were reduced by 24%.

Ecology of the collapse of Rapa Nui society.

Collapses of food producer societies are recurrent events in prehistory and have triggered a growing concern for identifying the underlying causes of convergences/divergences across cultures around the world. One of the most studied and used as a paradigmatic case is the population collapse of the Rapa Nui society. Here, we test different hypotheses about it by developing explicit population dynamic models that integrate feedbacks between climatic, demographic and ecological factors that underpinned the socio-cultural trajectory of these people. We evaluate our model outputs against a reconstruction of past population size based on archaeological radiocarbon dates from the island. The resulting estimated demographic declines of the Rapa Nui people are linked to the long-term effects of climate change on the island's carrying capacity and, in turn, on the ‘per-capita food supply’.

Model-Based and Model-Free Control of DC–DC Converters With High-Order Dynamics and Limited Measurements

This article introduces a control design framework for modern dc-dc topologies with high-order dynamics. In particular, model-based and model-free approaches using high-order controllers are introduced. The model-based approach permits the use of a minimum number of sensors, even for converters with a high number of components (e.g., multilevel, quadratic, input/output LC filter-based converters, etc.). This setting does not require estimation of state variables and its gain tuning can be achieved by selecting time-response specifications. The proposed model-free approach control exhibits the same, as well as some additional characteristics. Namely, controllers can be synthesized without the requirement of an explicit dynamic model, and gain tuning with guaranteed stability is directly achieved from measurement data. The latter controller is implemented in discrete time, which facilitates a digital implementation. The proposed approaches are validated through the control design and closed-loop implementation of a sixth-order topology.

Analytical dynamic modeling of Delta robot with experimental verification

In this paper, an explicit dynamic model of Delta robot is obtained analytically. The main contribution of this work is that, unlike existing prior work, the final dynamics model is given directly in the form of [Formula: see text], with explicit expressions for M, C and G. This is of great importance, since many advanced control techniques like Optimal Control need dynamic model in an explicit form, i.e. time derivative of state vector given explicitly in terms of the states and control vectors. To this goal, first, velocity and acceleration analysis is done by differentiating robot's geometrical loops directly. Then, Jacobian matrices are calculated to have kinematic relations in a more compact form. After that, principle of virtual work is implemented to derive the dynamic equations. In this part, Jacobian matrices are substituted into dynamic model. This is unlike other referenced works on Delta robot dynamics that need to continue the derivation in symbolic software or derive the model implicitly. Using Jacobians, dramatically simplifies the final explicit dynamic model. Therefore, the final dynamic equations are calculated in a straightforward manner without any use of symbolic calculation software. After all, the presented model is verified with an experimental setup. The model shows good accuracy in terms of torque prediction.

Influence of oceanic conditions in the energy transfer efficiency estimation of a micronekton model

Abstract. Micronekton – small marine pelagic organisms around 1–10 cm in size – are a key component of the ocean ecosystem, as they constitute the main source of forage for all larger predators. Moreover, the mesopelagic component of micronekton that undergoes diel vertical migration (DVM) likely plays a key role in the transfer and storage of CO2 in the deep ocean: this is known as the “biological pump”. SEAPODYM-MTL is a spatially explicit dynamical model of micronekton. It simulates six functional groups of vertically migrant (DVM) and nonmigrant (no DVM) micronekton, in the epipelagic and mesopelagic layers. Coefficients of energy transfer efficiency between primary production and each group are unknown, but they are essential as they control the production of micronekton biomass. Since these coefficients are not directly measurable, a data assimilation method is used to estimate them. In this study, Observing System Simulation Experiments (OSSEs) are used at a global scale to explore the response of oceanic regions regarding energy transfer coefficient estimation. In our experiments, we obtained different results for spatially distinct sampling regions based on their prevailing ocean conditions. According to our study, ideal sampling areas are warm and productive waters associated with weak surface currents like the eastern side of tropical oceans. These regions are found to reduce the error of estimated coefficients by 20 % compared to cold and more dynamic sampling regions.

Ecotone formation through ecological niche construction: the role of biodiversity and species interactions.

Rapid changes in species composition, also known as ecotones, can result from various causes including rapid changes in environmental conditions, or physiological thresholds. The possibility that ecotones arise from ecological niche construction by ecosystem engineers has received little attention. In this study, we investigate how the diversity of ecosystem engineers, and their interactions, can give rise to ecotones. We build a spatially explicit dynamical model that couples a multispecies community and its abiotic environment. We use numerical simulations and analytical techniques to determine the biotic and abiotic conditions under which ecotone emergence is expected to occur, and the role of biodiversity therein. We show that the diversity of ecosystem engineers can lead to indirect interactions through the modification of their shared environment. These interactions, which can be either competitive or mutualistic, can lead to the emergence of discrete communities in space, separated by sharp ecotones where a high species turnover is observed. Considering biodiversity is thus critical when studying the influence of species–environment interactions on the emergence of ecotones. This is especially true for the wide range of species that have small to moderate effects on their environment. Our work highlights new mechanisms by which biodiversity loss could cause significant changes in spatial community patterns in changing environments.

A power-type varying gain discrete-time recurrent neural network for solving time-varying linear system

Many practical engineering problems can be described as an online time-varying linear system (TVLS), and thus solving TVLS is very important in control theory and control engineering. In this paper, a novel power-type varying gain discrete-time recurrent neural network (PVG-DTRNN) is proposed to solve the TVLS problem. Compared with the state-of-art method, i.e., the fixed-parameter discrete-time zeroing neural network (FP-DTZNN), the proposed PVG-DTRNN has better convergent rate and higher accuracy. To do so, a vector error function is firstly defined. Secondly, a power-type gain implicit dynamic model is derived and needs to be further discretized. Thirdly, by using Euler forward-difference rule, a discretized dynamic model is designed. In order to get the explicit dynamic model, the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is utilized to estimate the inverse of the Hessian matrix. Comparisons of computer simulations verify the effectiveness and superiority of the proposed PVG-DTRNN models.

Operational modal analysis of a liquid-filled cylindrical structure with decreasing filling mass by multivariate stochastic parameter evolution methods

Variable mass structures exhibit non-stationary characteristics and the corresponding time-varying (TV) dynamics are difficult to represent by explicit dynamic equations or finite element models via mechanism analysis. Operational modal analysis of variable mass structures based on vector response measurements is considered in this paper. In order to solve the practical problem of operational modal analysis for variable mass structures, univariate stochastic parameter evolution (SPE) methods are extended to the multivariate case and validated by a numerical varying mass system. Thereafter, a laboratory liquid-filled cylindrical structure with decreasing filling mass is built and analyzed by using the conventional “frozen-configuration” technique and non-parametric time-frequency analysis method. Finally, the multivariate SPE method is applied to identify the liquid-filled cylindrical structure with decreasing filling mass, and identification results demonstrate that the proposed method is able to obtain the TV dynamic characteristics of variable mass structures under operating conditions by only using the available vector response measurements.

Design and bulletproof performance investigation on the ceramic/metal laminated composite

In the current study, seven types of laminated composites are designed to replace the existing 616 steel plate with 5 mm thickness for the bulletproof. An explicit dynamic finite element model is developed to simulate the bullet penetration process using ANSYS Workbench software. And a specific bulletproof coefficient, which considers the ultimate bulletproof speed and area density of the target plate, is proposed and calculated, and the overall bulletproof performances of the composites and 616 steel plate are compared. The specific bulletproof coefficients of seven composites are increased by 12.53%, 14.77%, 13.28%, 12.20%, 19.59%, 23.81%, and 20.67%, respectively. The type F is the optimal type among all the structures. Eventually, the optimal composites are validated under different bullet hit positions and double-bullet situations. Results show that all the seven composites and 616 steel with 5 mm thickness can effectively defend 5.62 mm bullets, and no damage or failure is observed. Although the impact stiffness and ultimate bulletproof speed are both decreased, the area density and density are also significantly decreased.

Stability analyses of large waste dumps via 3D numerical modelling considering cracks and earthquake loading: a case study of Zhujiabaobao waste dump

This paper uses a 3D model for stability assessment of Zhujiabaobao waste dump with ground cracks. The study data were gathered via reconnaissance, geomorphological analysis and laboratory experiment. A 3D finite extended element method model that can consider cracks was then used to calculate the factor of safety (FOS) of the waste dump via the strength reduction technique. The simulation shows the dump to have an FOS of 1.22 and both the position and depth of penetration of cracks in the waste dump have a crucial impact on the stability of the slope. Because the study area is located in a seismically active area, simulation and analysis of the dynamic response of the waste dump under different magnitudes of seismic waves (peak acceleration is 0.05, 0.15, 0.25 and 0.45g) were performed via an explicit dynamic model. The simulation shows that high steps in the slope are particularly responsive to earthquakes. The approach used here for analysing stability under static and dynamic loads is useful for hazard prevention and mitigation.