Dynamic Principle Research Articles

Research on Vehicle Hydrodynamic Turbine Atomization System Based on Single Chip Microcomputer Technology

A new type of mass flow detection technology for vehicle twin turbines with swirl correction characteristics is introduced. The basic structure, the principle of the moment of momentum and the realization process of the technology are introduced. The improved scheme of the second turbine under unsteady flow condition is presented. According to the principles of fluid dynamics and turbomachinery, the vehicle turbine atomizer is optimized by using Concepts NREC software. Using this scheme can not only save the development cost, shorten the development period, but also improve the stability and reliability of the equipment.

An innovatory approach for determining grinding media system to optimize fraction compositions of grinding products based on grinding dynamics principle

An innovatory approach for determining grinding media ratio and sizes to optimize fraction compositions of grinding products was created based on the principle of grinding dynamics by the single fraction tests, which were conducted with the ore from Yongping Copper mine (China) in a discontinuous conical ball mill (D × L 360 × 160 mm, China), and the results show that the optimal ball size for +8 mm fraction, −8 + 5 mm fraction, −5 + 0.45 mm fraction and −0.3 + 0.2 mm fraction are Φ70 mm, Φ60 mm, Φ50 mm and Φ30 mm, respectively. Furthermore this approach was supported from the point of view of collision energy between ore and media by discrete element method (DEM), wtih results illustrating that the materials are more active with the highest tangential collision energy with 2.23 J. In addition, the comparable tests of the full fraction feed were conducted with media system determined by this method, with the grinding technical efficiency 71.71%, being 7.61 and 1.63 percentage points higher than that under the scheme on site and the other scheme. Furthermore, applicability and feasibility were proved to be tremendously positive through the industrial tests, and results of industrial tests show that unit media consumption and unit energy consumption are reduced by 0.56 kW·h and 0.072 kg/t, respectively, what's more, not only the production capacity is promoted by 1.04 t/h, but also concentrate indexes are also improved with grade and recovery being increased by 1.01 and 2.61 percentage points compared with that before the test. This method is extremely promising and novel and could be used in most beneficiation plants to optimize the media system of ball mill to elevate indexes and promote production in all probability.

A non-zero-sum investment and reinsurance game between two mean–variance insurers with dynamic CVaR constraints

This paper is devoted to investigating a non-zero-sum game between two competing insurers. The insurers can diversify their insurance risks by purchasing proportional reinsurance and investing their collected premiums into a financial market composed of one risk-free asset and one stock. The reinsurance premiums charged by the reinsurer follow the generalized mean–variance premium principle. Moreover, the dynamic CVaR constraints are incorporated in the game problem to control risks. With the dynamic mean–variance objective, we introduce two forward deterministic auxiliary processes to represent the expectations of the insurers’ wealth processes and transform the original time inconsistent game problem into a standard time consistent game problem with two state variables for each insurer. By adopting the dynamic programming principle and the Lagrange duality method, we derive the Nash equilibrium investment–reinsurance strategies for the two insurers. Finally, the effects of several important model parameters on the optimal policies are analyzed by numerical examples.

Dynamic principle analysis of reinforced concrete replaceable coupling beam energy dissipation structure

Reinforced concrete shear wall is one of the most common structures in tall buildings. As an effective means to control structural vibration response, energy dissipation damping is widely applied to reinforced concrete shear wall structures. Replaceable steel coupling beams (RSCB) is a new technology in the energy dissipation damping field, and are being gradually adopted by construction projects since their introduction. However, current research on RSCB damping performance and space optimization has some shortcomings. This paper discusses RSCB working principles based on structural dynamics theory and derives damping performance curves of corresponding structures, and a primary evaluation of seismic response method for RSCB structures is proposed. Finally, the energy dissipation performance of a typical reinforced concrete shear wall structure is analyzed based on performance curves and formula of structural dynamics constructed by this paper. Relevant outcomes of this paper will provide theoretical support and technical guidance for construction design and in-depth research of RSCB.

Optimal investment and benefit payment adjustment strategies for the target benefit plan under partial information

This article investigates the optimal asset allocation and benefit adjustment problem for the target benefit plan (TBP) with predictable returns in an environment of partial information. We assume that the return rate of the stock depends on an observable and an unobservable state variables, and the pension manager estimates the unobservable component from known information through Bayesian learning. Under the criterion of expected exponential utility maximization, we obtain the optimal strategy in closed-form through the dynamic programming principle approach. Furthermore, numerical simulations are conducted by the Monte Carlo method to discuss the impacts of some parameters on the derived optimal strategy and to compare the optimal strategy with the suboptimal strategy when ignoring learning. It turns out that neglecting learning affects the optimal strategy seriously, thereby leading to significant utility losses.

Three-dimensional simulation of green soybean infrared-assisted spouted bed drying.

The current study introduces a novel infrared-assisted spouted bed drying technique for the dehydration of green soybeans, which aims to enhance the drying quality and efficiency. The investigation involves an examination of the flow pattern in the spouted bed to obtain relevant data, followed by an optimization of the entire drying process. The drying process of green soybeans was simulated using SolidWorks and ANSYS Fluent software, based on the principles of computational fluid dynamics. The simulation test results showed that the simulation outcomes were consistent with the experimental data. The optimal conditions for the process of green soybean infrared-assisted spouted bed drying were found to be an inlet speed of 8 m/s and a temperature of 50 °C with the wavelength and power settings of the infrared board at 10 μm and 500 W, respectively. The simulation method selected in this article, based on gas-solid two-phase flow dynamics, is feasible for green soybean infrared-assisted spouted bed drying process. © 2023 Society of Chemical Industry.

A stochastic target problem for branching diffusion processes

We consider an optimal stochastic target problem for branching diffusion processes. This problem consists in finding the minimal condition for which a control allows the underlying branching process to reach a target set at a finite terminal time for each of its branches. This problem is motivated by an example from fintech where we look for the super-replication price of options on blockchain-based cryptocurrencies. We first state a dynamic programming principle for the value function of the stochastic target problem. Next, we show that the value function can be simplified into a novel function with the use of a finite-dimensional argument through a concept known as the branching property. Under wide conditions, this last function is shown to be the unique viscosity solution to an HJB variational inequality.

GANs training: A game and stochastic control approach

AbstractTraining generative adversarial networks (GANs) are known to be difficult, especially for financial time series. This paper first analyzes the well‐posedness problem in GANs minimax games and the widely recognized convexity issue in GANs objective functions. It then proposes a stochastic control framework for hyper‐parameters tuning in GANs training. The weak form of dynamic programming principle and the uniqueness and the existence of the value function in the viscosity sense for the corresponding minimax game are established. In particular, explicit forms for the optimal adaptive learning rate and batch size are derived and are shown to depend on the convexity of the objective function, revealing a relation between improper choices of learning rate and explosion in GANs training. Finally, empirical studies demonstrate that training algorithms incorporating this adaptive control approach outperform the standard ADAM method in terms of convergence and robustness. From GANs training perspective, the analysis in this paper provides analytical support for the popular practice of “clipping,” and suggests that the convexity and well‐posedness issues in GANs may be tackled through appropriate choices of hyper‐parameters.

Insights into time fractional dynamics in the Belousov-Zhabotinsky system through singular and non-singular kernels

In the realm of nonlinear dynamics, the Belousov-Zhabotinsky reaction system has long held the fascination of researchers. The Belousov-Zhabotinsky system continues to be an active area of research, offering insights into the fundamental principles of nonlinear dynamics in complex systems. To deepen our understanding of this intricate system, we introduce a pioneering approach to tackle the time fractional Belousov-Zhabotinsky system, employing the Caputo and Atangana-Baleanu Caputo fractional derivatives with the double Laplace method. The solution we obtained is in the form of series which helps in investigating the accuracy of the proposed method. The primary advantage of the proposed technique lies in the low amount of calculations required and produce high degree of precision in the solutions. Furthermore, the existence and uniqueness of the solution are investigated thereby enhancing the overall credibility of our study. To visually represent our results, we present a series of 2D and 3D graphical representations that vividly illustrate the behavior of the model and the impact of changing the fractional order derivative and the time on the obtained solutions.

Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research.

We present a detailed argument for how to integrate, or bridge, systems science thinking and methods with implementation science. We start by showing how fundamental systems science principles of structure, dynamics, information, and utility are relevant for implementation science. Then we examine the need for implementation science to develop and apply richer theories of complex systems. This can be accomplished by emphasizing a causal mechanisms approach. Identifying causal mechanisms focuses on the "cogs and gears" of public health, clinical, and organizational interventions. A mechanisms approach focuses on how a specific strategy will produce the implementation outcome. We show how connecting systems science to implementation science opens new opportunities for examining and addressing social determinants of health and conducting equitable and ethical implementation research. Finally, we present case studies illustrating successful applications of systems science within implementation science in community health policy, tobacco control, health care access, and breast cancer screening.

Large deviation principle for quasi-stationary distributions and multiscale dynamics of absorbed singular diffusions

Large deviation principle for quasi-stationary distributions and multiscale dynamics of absorbed singular diffusions

Probing the underlying principles of dynamics in piano performances using a modelling approach.

Variations in dynamics are an essential component of musical performance in most instruments. To study the factors that contribute to dynamic variations, we used a model approaching, allowing for determination of the individual contribution of different musical features. Thirty monophonic melodies from 3 stylistic eras with all expressive markings removed were performed by 20 pianists on a Disklavier piano. The results indicated a relatively high agreement among the pianists (Cronbach's alpha = 0.88). The overall average dynamics (across pianists) could be predicted quite well using support vector regression (R2 = 66%) from a set of 48 score-related features. The highest contribution was from pitch-related features (37.3%), followed by phrasing (12.3%), timing (2.8%), and meter (0.7%). The highest single contribution was from the high-loud principle, whereby higher notes were played louder, as corroborated by the written feedback of many of the pianists. There were also differences between the styles. The highest contribution from phrasing, for example, was obtained from the Romantic examples, while the highest contribution from meter came from the Baroque examples. An analysis of each individual pianist revealed some fundamental differences in approach to the performance of dynamics. All participants were undergraduate-standard pianists or above; however, varied levels of consistency and predictability highlighted challenges in acquiring a reliable group in terms of expertise and preparation, as well as certain pianistic challenges posed by the task. Nevertheless, the method proved useful in disentangling some underlying principles of musical performance and their relation to structural features of the score, with the potential for productive adaptation to a wider range of expressive and instrumental contexts.

Model-based safety analysis with time resolution (MBSA-TR) method for complex aerothermal–mechanical systems of aero-engines

Current aero-engine safety assessments mostly rely on experience-based safety analysis methods such as Fault Tree Analysis (FTA) or Failure Modes and Effects Analysis (FMEA). The progressively significant dynamic characteristics of aero-engines during their transition between states render these methods incapable of providing accurate quantitative safety guidance, which is vital for complex aerothermal–mechanical systems. To solve this problem, a Model-Based Safety Analysis with Time Resolution (MBSA-TR) method was established, which included system modeling, fault modeling, and Safety Critical Parameter (SCP) identification. An integrated system model combining the main gas path and air system was built based on dynamics principles, and it was capable of reflecting the dynamic characteristics of aero-engines. The fault model included several time-resolved sub-modules and interacted bidirectionally with the system model at each time step to realize time-sequential fault propagation. SCPs were defined as parametric analysis objectives, and they were identified using an FTA-like identification framework. Finally, a case study of a typical turbofan engine with low-pressure compressor blade fractures as the primary fault was analyzed. The results showed that some hazard risks are incapable of detection without time resolution. Thus, time resolution is indispensable for the safety evaluation of complex aerothermal–mechanical systems of aero-engines.

Model of organizational, methodological and personnel support for educational activities in Russian in the Tanzanian education system as a theoretical construct

The article updates the importance of promoting the Russian language in foreign countries in modern geopolitical conditions, one of the tools of which is assistance to foreign partners in organizational, methodological and personnel support for teaching Russian as a foreign language. The importance of developing a model of organizational, methodological and personnel support for educational activities in Russian in the education system of the United Republic of Tanzania is substantiated. It is proved that the model developed is a normative model that reflects ideas on improving pedagogical activities for teaching Tanzanians Russian. The main functions of the model are explanatory, illustrative, informational and projective ones. The leading idea of the model is proposed: «Language is the best mediator for establishing friendship and harmony» (Erasmus of Rotterdam). The block structure of the model is substantiated and the content of the target, analytical-diagnostic, motivational, methodological, content-design, methodological and performance-prospective blocks is revealed. The interpretation of organizational, methodological and personnel support for educational activities in Russian in the education system of the Republic of Tanzania is argued as a set of educational resources and pedagogical conditions that ensure the effectiveness of educational activities in Russian in the Republic of Tanzania, both in terms of increasing the level of teaching Russian as a foreign language and in part of promoting the interest in the Russian language among Tanzanians. Scientific approaches to the development of organizational, methodological and personnel support for educational activities in Russian in the Tanzanian education system and the principles of their implementation are outlined, including systemic, communicative-active, competence-based and cultural approaches, the principle of integrity, the principle of structure, the principle of dynamism, the principle of completeness of information provision, the principle of compliance with the speech needs of students, the principle of didactic consistency, the principle of personal orientation, the principle of activity, the principle of dialogicity (dialogue of cultures), the principle of cultural conformity.

Dynamic programming principle for backward doubly stochastic recursive optimal control problem and sobolev weak solution of the stochastic Hamilton-Jacobi-Bellman equation

In this paper, we investigate a backward doubly stochastic recursive optimal control problem wherein the cost function is expressed as the solution to a backward doubly stochastic differential equation. We present the dynamical programming principle for this type of optimal control problem and establish that the value function is the unique Sobolev weak solution to the associated stochastic Hamilton-Jacobi-Bellman equation.

Design and Fabrication of a 3D-Printed Microfluidic Immunoarray for Ultrasensitive Multiplexed Protein Detection.

Microfluidic technology has revolutionized device fabrication by merging principles of fluid dynamics with technologies from chemistry, physics, biology, material science, and microelectronics. Microfluidic systems manipulate small volumes of fluids to perform automated tasks with applications ranging from chemical syntheses to biomedical diagnostics. The advent of low-cost 3D printers has revolutionized the development of microfluidic systems. For measuring molecules, 3D printing offers cost-effective, time, and ease-of-designing benefits. In this paper, we present a comprehensive tutorial for design, optimization, and validation for creating a 3D-printed microfluidic immunoarray for ultrasensitive detection of multiple protein biomarkers. The target is the development of a point of care array to determine five protein biomarkers for aggressive cancers. The design phase involves defining dimensions of microchannels, reagent chambers, detection wells, and optimizing parameters and detection methods. In this study, the physical design of the array underwent multiple iterations to optimize key features, such as developing open detection wells for uniform signal distribution and a flap for covering wells during the assay. Then, full signal optimization for sensitivity and limit of detection (LOD) was performed, and calibration plots were generated to assess linear dynamic ranges and LODs. Varying characteristics among biomarkers highlighted the need for tailored assay conditions. Spike-recovery studies confirmed the assay's accuracy. Overall, this paper showcases the methodology, rigor, and innovation involved in designing a 3D-printed microfluidic immunoarray. Optimized parameters, calibration equations, and sensitivity and accuracy data contribute valuable metrics for future applications in biomarker analyses.

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

Wheeled mobile robots (WMRs) have been a focus of research for several decades, particularly concerning navigation strategies in static and dynamic environments. This review article carefully examines the extensive academic efforts spanning several decades addressing navigational complexities in the context of WMR route analysis. Several approaches have been explored by various researchers, with a notable emphasis on the inclusion of stability and intelligent capabilities in WMR controllers attracting the attention of the academic community. This study traces historical and contemporary WMR research, including the establishment of kinetic stability and the construction of intelligent WMR controllers. WMRs have gained prominence in various applications, with precise navigation and efficient control forming the basic prerequisites for their effective performance. The review presents a comprehensive overview of stability analysis and navigation techniques tailored for WMRs. Initially, the exposition covers the basic principles of WMR dynamics and kinematics, explaining the different wheel types and their associated constraints. Subsequently, various stability analysis approaches, such as Lyapunov stability analysis and passivation-based control, are discussed in depth in the context of WMRs. Starting an exploration of navigation techniques, the review highlights important aspects including path planning and obstacle avoidance, localization and mapping, and trajectory tracking. These techniques are carefully examined in both indoor and outdoor settings, revealing their benefits and limitations. Finally, the review ends with a comprehensive discussion of the current challenges and possible routes in the field of WMR. The discourse includes the fusion of advanced sensors and state-of-the-art control algorithms, the cultivation of more robust and reliable navigation strategies, and the continued exploration of novel WMR applications. This article also looks at the progress of mobile robotics during the previous three decades. Motion planning and path analysis techniques that work with single and multiple mobile robots have been discussed extensively. One common theme in this research is the use of soft computing methods to give mobile robot controllers cognitive behaviors, such as artificial neural networks (ANNs), fuzzy logic control (FLC), and genetic algorithms (GAs). Nevertheless, there is still a dearth of applications for mobile robot navigation that leverage nature-inspired algorithms, such as firefly and ant colony algorithms. Remarkably, most studies have focused on kinematics analysis, with a small number also addressing dynamics analysis.

High spatial-resolved heat manipulating membrane heterogeneity alters cellular migration and signaling.

Plasma membrane heterogeneity is a key biophysical regulatory principle of membrane protein dynamics, which further influences downstream signal transduction. Although extensive biophysical and cell biology studies have proven membrane heterogeneity is essential to cell fate, the direct link between membrane heterogeneity regulation to cellular function remains unclear. Heterogeneous structures on plasma membranes, such as lipid rafts, are transiently assembled, thus hard to study via regular techniques. Indeed, it is nearly impossible to perturb membrane heterogeneity without changing plasma membrane compositions. In this study, we developed a high-spatial resolved DNA-origami-based nanoheater system with specific lipid heterogeneity targeting to manipulate the local lipid environmental temperature under near-infrared (NIR) laser illumination. Our results showed that the targeted heating of the local lipid environment influences the membrane thermodynamic properties, which further triggers an integrin-associated cell migration change. Therefore, the nanoheater system was further applied as an optimized therapeutic agent for wound healing. Our strategy provides a powerful tool to dynamically manipulate membrane heterogeneity and has the potential to explore cellular function through changes in plasma membrane biophysical properties.

Influence of Temperature and Incidence Angle on the Irradiation Cascade Effect of 6H-SiC: Molecular Dynamics Simulations.

SiC devices have been typically subjected to extreme environments and complex stresses during operation, such as intense radiation and large diurnal amplitude differences on the lunar surface. Radiation displacement damage may lead to degradation or failure of the performance of semiconductor devices. In this paper, the effects of temperature and incidence angle on the irradiation cascade effect of 6H-SiC were investigated separately using the principles of molecular dynamics. Temperatures were set to 100 K, 150 K, 200 K, 250 K, 300 K, 350 K, 400 K and 450 K. The incidence direction was parallel to the specified crystal plane, with angles of 8°, 15°, 30°, 45°, 60° and 75° to the negative direction of the Z-axis. In this paper, the six types of defects were counted, and the microscopic distribution images and trajectories of each type of defect were extracted. The results show a linear relationship between the peak of the Frenkel pair and temperature. The recombination rate of Frenkel pairs depends on the local temperature and degree of aggregation at the center of the cascade collision. Increasing the angle of incidence first inhibits and then promotes the production of total defects and Frenkel pairs. The lowest number of total defects, Frenkel pairs and antisite defects are produced at a 45° incident angle. At an incidence angle of 75°, larger size hollow clusters and anti-clusters are more likely to appear in the 6H-SiC.

A new propulsion enhancement mechanism in metachronal rowing at intermediate Reynolds numbers

Metachronal rowing is a biological propulsion mechanism employed by many swimming invertebrates (e.g. copepods, ctenophores, krill and shrimp). Animals that swim using this mechanism feature rows of appendages that oscillate in a coordinated wave. In this study, we used observations of a swimming ctenophore (comb jelly) to examine the hydrodynamic performance and vortex dynamics associated with metachronal rowing. We first reconstructed the beating kinematics of ctenophore appendages based on a high-speed video of a metachronally coordinated row. Following the reconstruction, two numerical models were developed and simulated using an in-house immersed-boundary-method-based computational fluid dynamics solver. The two models included the original geometry (16 appendages in a row) and a sparse geometry (8 appendages, formed by removing every other appendage along the row). We found that appendage tip vortex interactions contribute to hydrodynamic performance via a vortex-weakening mechanism. Through this mechanism, appendage tip vortices are significantly weakened during the drag-producing recovery stroke. As a result, the swimming ctenophore produces less overall drag, and its thrust-to-power ratio is significantly improved (up to 55.0 % compared with the sparse model). Our parametric study indicated that such a propulsion enhancement mechanism is less effective at higher Reynolds numbers. Simulations were also used to investigate the effects of substrate curvature on the unsteady hydrodynamics. Our results illustrated that, compared with a flat substrate, arranging appendages on a curved substrate can boost the overall thrust generation by up to 29.5 %. These findings provide new insights into the fluid dynamic principles of propulsion enhancement underlying metachronal rowing.