Improved Dynamic Ripple-Based Modeling Technique for a Toroid Inductor in PFC Rectifiers

An off-grid hybrid PV/diesel model as a planning and design tool, incorporating dynamic and ANN modelling techniques

In field development and reservoir surveillance planning, there is an absolute need to obtain reliable values for reservoir pressures, productivity indexes and other values on a continuous basis so that planning can be done reliably and production / recovery can be optimized. However, continuous data acquisition is often where we stumbled due to a combination of economic, operational/logistical constraints. An alternative is to derive these key parameters from surface data using dynamic well modeling techniques. Subsurface data acquisition will be replaced by surface data acquisition, reducing the number of well interventions and data acquisition costs. The major assumption in current PVT correlations in dynamic well modeling application is instantaneous transformation of one phase (gas) into another phase (oil). During shut-in, this assumption leads to inaccurate modeling of the gas/liquid distribution in the well and hence, an incorrect prediction of interphase level, in-situ density and pressure distribution in the well. The objectives of this research is to improve the current dynamic well modeling technique by incorporating the mass transfer rate model into current PVT model for a reliable well shut-in status description. This is a relatively new and unexplored technical method, which increases the understanding of well behavior. This novel PVT model is able to determine an accurate volume of each fluid phase at any node in the wellbore by incorporating the fluid segregation, mass transfer rate and fluid ingress in the reservoir during shut-in. This better description of wellbore dynamic behavior improves the accuracy of dynamic well modeling ensuring a reliable downhole data determination. This paper presents a status update in well performance modeling and the proposed scheme in developing the novel PVT model. A number of engineering conceptions were reviewed and all the elements that become the foundation of the well bore transient mechanics were discussed.

A rover’s performance on extraterrestrial terrain can be predicted by simulating the physical components of the rover, its environment, a nd all of the physical interactions in the rover -terrain system. Existing computer simulation software has two characteristics that can be improved upon. First, most simulations treat terrain as a solid geometric surface and use theoretical physics to pred ict interactions with a rover. However, since soil or sand is usually a semi -fluid solid, this modeling technique disregards some of the important material properties of the terrain. Second, simulations that do use physically based modeling with finite ele ment methods are very computationally intensive and require uncommonly powerful computers. The goal of this project is to create a physically based modeling software that runs on standard personal computers which can accurately simulate the interaction of Mars rovers with the Martian terrain and predict the performance of various rover designs on different terrain conditions. The simulation allows the user to set parameters such as the slope, friction, and other material properties of the surface, and give the rover initial conditions such as total available power and rover starting position. When running the simulation, the program can instantaneously extract rover performance data and output the data to a text file. The performance parameters of concern in clude the rover’s instantaneous position, velocity, and wheel slippage. The user has the option to choose from two methods to simulate the Martian soil. The first is the standard method that most existing simulation software uses, which treats the ground a s a large solid surface. The second method represents soil as a bed of line segments that can be deformed according to the interactions with the rover. Due to the semi -fluid nature of soil, the standard modeling technique is suspected to have difficulty in describing the motion of the soil as caused by the force of the rover’s wheels exerted on it, thereby creating inaccuracies in the model. In this study, we are particularly interested in determining whether this dynamic modeling technique gives a more acc urate simulation of real soil than the standard method.

This research investigates the optimization of operational efficiency and cost reduction through the enhancement of material flow management within production line stations. Departing from conventional static analyses, the study employs advanced simulation tools to pinpoint performance bottlenecks and inefficiencies via dynamic modelling techniques. The Ishikawa diagram serves as the primary tool for conducting root-cause analysis. Simultaneously, the 5S methodology is implemented to foster workplace organization, standardization, and hygiene practices. In contrast to traditional optimization frameworks, the proposed strategy integrates real-time performance tracking systems, complemented by adaptive feedback mechanisms. This integration permits ongoing assessment of the production process, facilitating iterative improvement cycles. Empirical data gathered from monitored cycle times, equipment utilization rates, and defect frequencies substantiate the validation of implemented changes. The resulting optimized system significantly minimizes downtime and waste, thereby advancing sustainable and scalable operations. Ultimately, this research demonstrates that the fusion of simulation-based insights with lean management principles leads to considerable improvements in manufacturing productivity and overall product quality.

During the morphing process, the dynamic modeling of the morphing wing aircraft presents the characteristics of rigid‐elastic coupling effects, moving boundaries, and low computational efficiency. Meanwhile, parameters such as aerodynamic forces/moments, center of pressure, center of mass, and moment of inertia would also change significantly, which would seriously affect the flight stability. Therefore, this paper mainly focuses on the rigid‐elastic coupling dynamic modeling of morphing wing aircraft. Based on the virtual power principle, a floating coordinate system and the modal synthesis method are adopted to establish a rigid‐elastic coupling dynamic model that accounts for the elasticity of the wings, which can accurately capture the cross‐scale coupling effects between the rigid‐body motion and the elastic deformation of the wings during the continuously morphing process. Considering the moving boundary problem between the fuselage and the wings during the continuously morphing process, a dynamic constraint modeling technique based on the Craig‐Bampton method and a node's life and death technique describing the constraint states are proposed, which can avoid the complex operations of reestablishing the finite element model of the elastic bodies for traditional methods. Moreover, a method of smoothing model for the rigid–elastic coupling system is developed, which can significantly improve the computational efficiency for the dynamic equation of the morphing wing aircraft. And by changing the value of the smoothing factor, preservation of specific high‐frequency components can be controlled. Finally, the numerical examples are carried out to verify the proposed rigid‐elastic coupling dynamic model for the morphing wing aircraft.

A methodology is developed to analyze the vortex-induced vibration of moored or towed cable systems. The fluctuating forces are considered as sources of energy which generate waves propagating through the cable-body system with dissipation and scattering in the process. Because of its emphasis on energy flow, this method facilitates the incorporation of various vortex models into dynamic cable analysis. INTRODUCTION Cables exposed to current in deep-ocean moors or used for towing bodies or arrays for ocean survey are subject to transverse oscillations from vortex-induced forces. This phenomenon, called strumming, has been under investigation for many years because it affects the fatigue life of the structure and the noise of any attached sensors. Experiments conducted in water channels indicate that the vortex-induced vibration can be substantially reduced by introducing hydrodynamic disturbances to the flow near the structure. For example, mechanical devices, such as splitter vanes, trailing ribbons and fairings, have been used to disturb the formation of the vortex flow, while spiral wrappings have been used to disturb their spanwise coherence. Other investigations have been made concerning the nature of the vortex flow and to model the vortex-induced cable vibrations. Wind tunnel and water channel experiments were carried out to measure the characteristics of vortex formation and cable responses. However, due to limitations of the experimental equipment, the motion of a full-scale system cannot easily be modeled experimentally. Thus, numerical modeling is probably the best way to analyze the dynamic motion of a cable system under strumming excitation. To this end, empirical models have been developed recently in which the fluid oscillation near the cable is represented by a non-linear, self-excited oscillator that is dynamically coupled to the structural member. These models can reproduce the synchronization effect as the shedding frequency approaches the natural frequencies of the structure. The models have been used to simulate the motion of an elastically mounted circular cylinder. The results are in good agreement with experimental data of the maximum amplitude in the resonant or entrained state when the vortex shedding frequency is equal to the natural frequencies of the vibrating cylinder. Studies are underway to couple the models to the equations of motion of a flexible cable to simulate the motion of a cable under vortex excitation. The purpose of this paper is to present the bond graph method as a modeling technique that can incorporate a dynamic model of vortex-induced forces in models of cable systems. Using this method, the response of a complete cable system under various environmental conditions is simulated. In the next section this modeling technique is compared with other cable dynamic modeling techniques. A review of oscillator models then is presented with some examples given to demonstrate the feasibility of the bond graph method as a modeling technique for vortex-induced cable system vibrations. DYNAMIC ANALYSIS OF CABLE-BODY SYSTEMS Since cable-body systems are being used in more and more ocean facilities, there is a strong interest in valid analytical tools which require development of analytical approaches supported by experimental validation. Mathematical modeling and numerical techniques have been used by l 2 3 many investigations.

The article presents the results of developing a methodology and implementing dynamic modeling in the SolidWorks Motion 2016 software environment for changing the body roll angle of the Gazelle Next van during active maneuvering and turning using a lever-electromagnetic stabilization system in comparison with a lever stabilizer system. A dynamic modeling technique was developed to analyze the change in the roll angle of the Gazelle NEXT all-metal van in the driving mode when turning and intensive maneuvering with a lever and using a lever-electromagnetic stabilization system). As a result of the research, a decrease in the roll angle of the Gazelle Next all-metal van was revealed in driving modes with active maneuvering and cornering using the lever-electromagnetic stabilization system relative to that installed on the example of the Gazelle NEXT — lever. The proposed method of dynamic modeling proved the effectiveness of using a lever-electromagnetic stabilization system when turning and active maneuvering, compared with standard lever stabilizers based on a comparison of the roll angles of the first and second options.

The study introduces three novel strategies for incorporating capabilities for dynamic modelling into multiblock regression methods by integrating sequentially orthogonalised partial least squares (SO‐PLS) with different dynamic modelling techniques. The study evaluates these strategies using synthetic datasets and an industrial example, comparing their performance in predictive ability, identification of process dynamics, and quantification of block contributions. Results suggest that these approaches can effectively model the dynamics with performance comparable to state‐of‐the‐art methods, providing, at the same time, insight into the dynamic order and block contributions. One of the strategies, sequentially orthogonalised dynamic augmented (SODA)–PLS, shows promise by ensuring that redundant information in the time dimension is not included, resulting in simpler and more easily interpretable dynamic models. These multiblock dynamic regression strategies have potential applications for improved process understanding in industrial settings, especially where multiple data sources and inherent time dynamics are present.

<div class="htmlview paragraph">Heterogeneous physical systems can often be considered as highly complex, consisting of a large number of subsystems and components, along with the associated interactions and hierarchies amongst them. The simulation of a large-scale, complex system can be computationally expensive and the dynamic interactions may be highly nonlinear. One approach to address these challenges is to increase the computing power or resort to a distributed computing environment. An alternative to improve the simulation computational performance and efficiency is to reduce CPU required time through the application of surrogate models. Surrogate modeling techniques for dynamic simulation models can be developed based on Recurrent Neural Networks (RNN).This study will present a method to improve the overall speed of a multi-physics time-domain simulation of a complex naval system using a surrogate modeling technique. For the purpose of demonstration, a small scale dynamic model of a power system has been developed as a monolithic implementation in Simulink®. The surrogate modeling technique will be evaluated by comparing time dependent responses of the surrogate against the original monolithic with respect to the approximation accuracy and computational performance.</div>

The Admonitions of the Instructress to the Court Ladies, a renowned masterpiece by Eastern Jin painter Gu Kaizhi, depicts the apparel styles of ancient court ladies. With the advancement of digital technology, the reconstruction of ancient artworks through digital means has become an essential direction in cultural heritage research. This study aims to digitally reconstruct the apparel depicted in The Admonitions of the Instructress to the Court Ladies and explore its applications and heritage value in the context of modern technological advancements. First, high-resolution image scanning and 3D modeling techniques are employed to accurately reconstruct the details of the apparel in the painting. By analyzing key elements such as fabric texture, color combinations, and structural features, and integrating historical apparel records, this study progressively reconstructs the historical apparel styles portrayed in the artwork. Additionally, virtual simulation and dynamic modeling techniques are applied to examine the appearance of the apparel in various postures and movements, aiming to capture their aesthetic characteristics in motion. The findings of this study not only provide a more intuitive and precise reconstruction of the apparel in The Admonitions of the Instructress to the Court Ladies, but also open new avenues for the digital preservation and research of ancient apparel, offering significant academic and cultural value.

This study analyzes land use changes due to human development in the Mkomazi Valley, Tanzania, and its impacts on nature using the SD–Modeling (System Dynamic modeling) technique. Ultimately this method relates environment and economy of society with regard to a seasonal rainfall–based agriculture practice and their harmonization with irrigation agriculture for development sustainability. VENSIM PLE (VENTANA SIMULATION ENVIRONMENT, PERSONAL LEARNING EDITION 2002) software, which simplified the assessment, was used to build a SD–model that accommodated changes in Population, Deforestation, Gross Domestic Product (GDP), and Basin Storage. Model results indicate groundwater behavior, deforestation, public opinion and decreased health of the farmers all relate to changes in land use (i.e., introduction of a rice development project) with its associated environment degradation, deforestation, and poverty due to deforestation. Moreover, these changes might be the cause of animal flight from the Mkomazi game reserve and an increase in human disease and deaths. Finally, it is concluded that uncontrolled human activities and behavior are the main causes of environmental degradation and therefore a brief summary is presented on challenges and opportunities for decision–makers on the sustainable development of the Mkomazi Valley.

Digital smartphone messaging can be used to promote physical activity to large populations with limited cost. It is not clear which psychological constructs should be targeted by digital messages to promote physical activity. This gap presents a challenge for developing optimal content for digital messaging interventions. The aim of this study is to compare affectively framed and social cognitively framed messages on subsequent changes in physical activity using dynamical modeling techniques. We conducted a secondary analysis of data collected from a digital messaging intervention in insufficiently active young adults (18-29 years) recruited between April 2019 and July 2020 who wore a Fitbit smartwatch for 6 months. Participants received 0 to 6 messages at random per day across the intervention period. Messages were drawn from 3 content libraries: affectively framed, social cognitively framed, or inspirational quotes. Person-specific dynamical models were identified, and model features of impulse response and cumulative step response were extracted for comparison. Two-way repeated-measures ANOVAs evaluated the main effects and interaction of message type and day type on model features. This early-phase work with novel dynamic features may have been underpowered to detect differences between message types so results were interpreted descriptively. Messages (n=20,689) were paired with valid physical activity monitoring data from 45 participants for analysis. Received messages were distributed as 40% affective (8299/20,689 messages), 39% social-cognitive (8187/20,689 messages), and 20% inspirational quotes (4219/20,689 messages). There were no statistically significant main effects for message type when evaluating the steady state of step responses. Participants demonstrated heterogeneity in intervention response: some had their strongest responses to affectively framed messages, some had their strongest responses to social cognitively framed messages, and some had their strongest responses to the inspirational quote messages. No single type of digital message content universally promotes physical activity. Future work should evaluate the effects of multiple message types so that content can be continuously tuned based on person-specific responses to each message type.

For electromagnetic suspension (EMS) type urban Maglev vehicles using a U-shaped electromagnet, the levitation and guidance forces are generated by only one electromagnet. Although the levitation force is actively controlled by changing the voltage of the electromagnet, the guidance force is passively determined by the levitation force. In addition, the curve negotiation performance of EMS-type urban Maglev vehicles using a U-shaped electromagnet must be considered, because an urban guideway may have some curves with shorter radii. It is, therefore, necessary to predict the curving performance with the greatest accuracy possible, in order to improve electromagnetic suspension and establish guideway design specifications. The objective is to establish a new dynamic modelling technique, so as to achieve more realistic curving simulation and thus to more accurately evaluate the curving performance of an EMS-type Maglev vehicle. The use of a full vehicle multibody dynamic model is proposed, and is applied to the evaluation of curving performance. Design changes are also investigated to obtain the bogie design directions for minimising variation in the lateral air gap, which is a criterion for curving performance.

In order to improve the effect of dance teaching action analysis, this paper uses dance action skill feature identification method to analyze dance teaching action and combines teaching and technology to simulate dance action. Moreover, this paper conducts dynamic modeling of dance movements and analyzes the typical properties of several dynamic modeling techniques. At the same time, this paper takes the double-joint dance movement limb as the control object for comparative analysis. The comparison shows that the fractional sliding mode approaching law has better smoothing properties. In addition, this paper selects the control method combining fractional calculus and sliding mode control theory to improve the tracking speed and following effect of the double joints of dance movements. Finally, this paper studies the variance virtual spindle cross-coupling control method based on fractional-order sliding mode to further improve the synchronization accuracy of dance movement limb joints. From the experimental data, it can be seen that the application effect of dance movement skill feature recognition in dance teaching movement analysis is very good.

The rapid growth of healthcare data in recent years calls for more advanced and efficient analytic techniques. Artificial intelligence facilitates finding insightful patterns in massive high-dimensional data. Considering the latest movements towards using machine learning and deep learning techniques in the medical domain, in this study, we focused on the publications in which researchers employed artificial intelligence techniques for cancer diagnosis and treatment. Using dynamic topic modeling and natural language processing techniques, we analyzed the contents and trends of more than 12,000 scientific publications within the period of 2000 to 2018, extracted from two different sources, i.e., Elsevier’s Scopus and PubMed. While drawing the landscape of cancer research, our results also shed light on the evolution of artificial intelligence techniques and algorithms used for cancer diagnosis and treatment. Our findings confirm that modern computer science algorithms are being widely applied to extract patterns from large-scale medical images to cure different types of cancer with a special focus on deep learning techniques in recent years.