Simulation Research Research Articles

Design of a Hybrid Excitation Controller for Multimachine Infinite Bus Power System

Abstract: A significant portion of contemporary power networks is still conventional power system that uses synchronous generators to produce electricity. Conventional power systems are operated under various operating situations by means of excitation systems and turbine-governor systems of synchronous generators. This paper proposes an excitation controller for synchronous generators (SGs) in a multi machine infinite bus (MMIB) power system through combining the idea of the nonlinear backstepping (BS) and partial feedback linearization methods. The model of third-order has been linearized into a second-order linearized system that is independent of the rotor angle which is unmeasurable, using the partial feedback linearization approach. In this case, the BS is applied to the partially linearized system. The idea is to find a control input that drives the system towards a desired behaviour while ensuring the transformed states converge to their target values. Lastly, simulation research is carried out on an MMIB system to analyse how the proposed control mechanism (BS-PFLC) performs in stabilizing the system under a three phase-to-ground fault conditions of power networks. To demonstrate the effectiveness of the BS-PFLC, an existing excitation controller has been used to compare the performance.

Advances in machine learning methods in copper alloys: a review.

Advanced copper and copper alloys, as significant engineering structural materials, have recently been extensively used in energy, electron, transportation, and aviation domains. Higher requirements urge the emergence of high-performance copper alloys. However, the traditional trial-and-error experimental observations and computational simulation research used to design and develop novel materials are time-consuming and costly. With the accumulation of material research and rapid development of computational ability, the thorough application of material genome engineering has sped up the development of novel materials and facilitates the process of systematic engineering application. This review summarizes the benefits of data-driven machine learning techniques and the state of the art of machine learning research in the area of copper alloys. It also displays the widely used computational simulation approaches (e.g., the first-principles calculation, molecular dynamics simulation, phase-field simulations, and finite element analysis) and their combined applications in material design and property prediction. Finally, the limitations of machine learning research methods are outlined, and future development directions are proposed.

Non-Condensation Turbulence Models with Different Near-Wall Treatments and Solvers Comparative Research for Three-Dimensional Steam Ejectors

Steam ejectors are important energy-saving equipment for solar thermal energy storage; however, a numerical simulation research method has not been agreed upon. This study contributes to a comprehensive selection of turbulence models, near-wall treatments, geometrical modeling (2-D and 3-D), solvers, and models (condensation and ideal-gas) in the RANS equations approach for steam ejectors through validation with experiments globally and locally. The turbulence models studied are k-ε Standard, k-ε RNG, k-ε Realizable, k-ω Standard, k-ω SST, Transition SST, and linear Reynolds Stress. The near-wall treatments assessed are Standard Wall Functions, Non-equilibrium Wall Functions, and Enhanced Wall Treatment. The solvers compared are pressure-based and density-based solvers. The root causes of their distinctions in terms of simulation results, applicable conditions, convergence, and computational cost are explained and compared. The complex phenomena involving shock waves, choking, and vapor condensation captured by different models are discussed. The internal connections of their performance and flow phenomena are analyzed from the mechanism perspective. The originality of this study is that both condensation and 3-D asymmetric effects on the simulation results are considered. The results indicate that the k-ω SST non-equilibrium condensation model coupling the low-Re boundary conditions has the most accurate prediction results, best convergence, and fit for the widest range of working conditions. A 3-D asymmetric condensation model with a density-based solver is recommended for simulating steam ejectors accurately.

Turning Research Ideas into Reality: A Guide to Developing a Simulated Research Protocol using Administrative Data

Objectives Demonstrate the translation of a research idea into a protocol with an analytic plan, including discussion on requirements for administrative data (AD) analysis, e.g., governance, time estimation. Foster discussion on processes for conducting AD research to enable learning and collaboration. ApproachParticipants were guided through three sections, and each alternated between presentations, group participation and discussion sessions. An overview of the Manitoba Centre for Health Policy (MCHP) Data Repository was presented to use as the framework for the AD discussion. Our chosen topic of discussion was: “How do health history and family history affect risk of poor outcomes for people with diabetes?” In small groups, participants discussed issues arising from translating the idea into a research plan. For example, define a cohort of people with diabetes, examine cardiovascular events as the outcome using survival analysis, and control for demographics, treatment compliance and family history of diabetes and cardiovascular events. We evaluated the feasibility of using AD to measure these variables. We discussed a method to estimate the time to conduct this proposed using AD, i.e., time for programming and analysis. Finally, we discussed data approvals and requirements when conducting research using AD. Conclusions and ImplicationsWe discussed the benefits and cautions of using AD and shared knowledge regarding research opportunities and obstacles across jurisdictions to identify commonalities and areas of opportunity for growth. The workshop was informative and interactive. It generated much discussion and was well-received among participants, with many asking for further information after the workshop concluded.

Deep reinforcement learning for collision avoidance of autonomous ships in inland river

Due to the characteristics of large inertia, large time delay, and nonlinearity in ship motion, the maneuverability of ships is an important issue related to the safety of ship navigation. The manipulation of ships significantly affects the safety of ship navigation, and its importance will gradually increase with the development of autonomous ships. Collision accidents are common due to the complexity of inland waterways and density of the ships. Herein, an autonomous learning framework with deep reinforcement learning (DRL) is constructed for autonomous driving tasks. The state space, action space, reward function and neural network structure of DRL are designed based on the ship’s maneuvering characteristics and control requirements. A DDPG algorithm is then used to implement the controller. Finally, some representative route segments of the inland waterway is selected for simulation research based on the virtual simulation environment. The designed DRL controller can quickly converge from the training and learning process to meet the control requirements. By comparing with the previous experimental results, the effectiveness of this algorithm is verified. Therefore, this study provides a reference for future research on the collision avoidance technology of autonomous ships in inland rivers.

Military Medical Simulations-Scoping Review.

The military employs a wide variety of training paradigms to prepare a ready medical force. Simulation-based training is prominently used in the military for all roles of care to provide the knowledge, skills, and abilities needed to render care from the battlefield to the hospital. The purpose of this scoping review is to synthesize the body of research in military healthcare simulation, highlight trends in the literature, and identify research gaps. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis process, the databases of PubMed, Google Scholar, and targeted conferences were searched for articles focused on simulation-based training in the military healthcare community. Inclusion criteria required that the studies assessed a healthcare simulation intervention and had military participants. Data were gathered on population parameters (branch of service and provider level) as well as study parameter (simulation modality, medical domain, and outcome measures). Outcome measures were categorized according to the Kirkpatrick model of training evaluation. A total of 43 articles met inclusion criteria. Article summaries and descriptive data on the participant populations and study parameters are provided in Tables1, 2, and Supplementary Table S1. Participant populations were inclusive of all the services and roles of care, suggesting appropriate representation of the broad military healthcare community. The majority of literature has studied physical simulations, such as manikins or task trainers. Few studies employed augmented or virtual reality as the training intervention, likely because of the nascency of the technology. Trauma care was the focus of 65% of the studies; this is attributable to the criticality of trauma care within battlefield medicine and casualty response. Related to study outcomes, participant reactions, such as usability and user acceptance, and immediate learning outcomes were heavily studied. Retention and behavioral changes were rarely studied and represent a significant research gap. Future research assessing mixed reality technologies would be beneficial to determine whether the technology warrants inclusion in programs of instruction. Finally, studies with outcome measures including long-term knowledge and skills retention, behavioral change, or patient outcomes are strongly recommended for future research.

Advanced Machine Learning and Experimental Studies of Polypropylene Based Polyesters Tribological Composite Systems for Sustainable Recycling Automation and Digitalization

Digitalization and automation are emerging solutions to the complex problems of recycling. In this research work, the experimental and Python based Archard deep learning wear rate models are introduced regarding recycling automation and composite tribological systems optimization. The optimum polyester fibers (PESF) of length of 3-3.5 mm were used for fabrication of polypropylene (PP)-PESF composite systems. The deformation, high texture, asperities, and micro-cracks were observed during scanning electron microscope and machine-learning studies. The lowest experimental value of abrasive wear of 3.0 × 10-6 mm3/Nm was observed for PP. Comparatively, higher experimental values of abrasive wear of the PP-PESF composites are found in the range of 4.35 × 10-6 to 4.7 × 10-6 mm3/Nm due to presence micro-defects on the surface of composites. The experimental values of Coefficient of friction (COF) of PP and PP-PESF are found in the range of 0.70 - 0.8 and 1.1 - 1.3, respectively. The experimental values of abrasive wear and COF are found compatible with literature. Similarly, the simulated values of abrasive wear of PP and PP-PESF composites are predicted in the range of 4.8×10-7 to 3.75×10-7 mm3/Nm, respectively. The predicted values of PP and PP-PESF composite show better resistance towards abrasive wear. The proposed experimental and simulated (in terms of Python coding, machine learning, image processing, artificial intelligence, and deep learning studies) research work can be introduced industrially for automation as well as digitalization of grinding of PES waste, processing, tribological testing, and SEM characterization evaluations.

Ply-ply friction behavior between unidirectional thermoplastic prepreg plies during thermoforming: Characterization and modeling

The ply-ply friction behavior of unidirectional carbon fiber reinforced polyphenylene sulfide (UD CF/PPS) prepreg in thermoforming was investigated through an improved pull-through testing system. The effects of temperature, normal force and slipping velocity were considered in testing. The results indicated the existence of three key mechanisms underlying slipping: namely the resin shear, fiber–fiber contact and fiber-resin interaction. A three-stage division of the experimental curve was proposed, and several factors were defined to establish a quantitative definition of the ply-ply friction behavior. The results showed that the influence of slipping velocity is particularly evident. Its post-yield stress (12.8 kPa), steady-state CoF (0.118) and residual stress (0.705 kPa) were the highest, exhibiting the largest changes of 957.9 %, 736.9 % and 47.2 %, respectively. This indicated the strong contribution of resin in ply-ply friction. In addition, the Stribeck analysis also suggested the dominance of hydrodynamic lubrication condition in slipping. Based on the experimental results, a simple phenomenological model was proposed based on experimental curves to accurately describe the effects of processing parameters. This work presents a comprehensive characterization of the ply-ply friction behavior of UD CF/PPS prepreg in thermoforming, providing a substantial experimental foundation for the subsequent simulation research.

Pressure Drop in a Metal Foam Centrifugal Breather: A Simulation Approach

One of the main issues faced in the operation of a metal foam centrifugal breather is the high pressure drop. This study investigates the pressure drop of a metal foam centrifugal breather. The numerical simulation research method is adopted. The DPM model is used to calculate the two-phase flow field of the metal foam breather, and the porous medium model is used to replace the metal foam at the breather. The resistance caused by the metal foam is replaced by a distributed resistance added to the fluid. The effects of flow rate, rotational speed, porosity, PPI (pores per inch), and temperature on the pressure drop of the breather are analyzed. The results indicate that rotational speed, flow rate, porosity, and PPI significantly influence the resistance of the metal foam centrifugal breather. The resistance of the breather is directly proportional to the rotational speed, flow rate, temperature, and metal foam pore density, and inversely proportional to the porosity. Temperature has a minor impact on the resistance of the metal foam centrifugal breather. Therefore, the metal foam centrifugal breather is more suitable for low-speed operating conditions.

Order-difference of normalized square envelope spectrum and its applications in early chatter detection of roll grinder

Roll grinder is widely demanded in grinding the surface of rolls that will be used to mill steel strips for high-quality automobile outer panels. The grinding chatter generally leads to poor machining accuracy and massive economic losses. The significance of roll grinder vibration monitoring is to detect the early grinding chatter. However, in harsh working conditions, some chatter detection methods inevitably confuse the fault components and interference components in vibration signals and the chatter feature information cannot be extracted exactly. The dynamical model of roll grinder system reveals that the spectrums of vibration signals contain intrinsic frequency components and chatter frequency components under health and chatter conditions. Based on the analytical modelling, a new health index order-difference of normalized square envelope spectrum (ODNSES) is proposed to detect early chatter and evaluate the health degradation of the roll grinder. The normalized square envelope spectrum (SES) is used as the pretreatment of ODNSES to compare the frequency components in vibration signals under health and early chatter conditions. Furthermore, order-difference of normalized SES is proposed to suppress the noise interference and to enable ODNSES to characterize the grinding chatter process. The detailed simulation research is performed to verify three important properties of ODNSES. The experimental results show that ODNSES would not be interfered by background noise significantly and it is on average 29.12% more sensitivity to impulse amplitudes than classical health indexes. The testing results on actual roll grinder exhibit that ODNSES can detect the early chatter and quantify the abnormal vibration in the grinding process.

Emulsification and interfacial characteristics of different surfactants enhances heavy oil recovery: experimental evaluation and molecular dynamics simulation study

The high viscosity and poor fluidity of heavy oil challenge its extraction, leading to the widespread use of surfactant emulsification to reduce viscosity and enhance recovery. This study evaluated three surfactants—sodium dodecyl sulfate (SDS), sodium oleate (SO), and APG0810—for their suitability and effectiveness in the X reservoir. The solution properties of these surfactants were analyzed and their micro-mechanisms investigated using MD calculations. The effects of surfactant concentration and additives on emulsification and viscosity reduction were elucidated. Ultimately, a system for emulsification and viscosity reduction was selected for physical simulation research. The experimental findings show that SO reduces interfacial tension from 52.4 mN/m to 0.0027 mN/m, transforming lipophilic surfaces into hydrophilic. MD analyses reveal SO’s optimal interfacial properties, with the lowest interfacial energy of −6423.4 kcal/mol, maximum interfacial thickness of 2.56 nm, and minimal diffusion coefficient of 0.4087 Å2/ps at the oil-water interface. These findings align with experimental results, confirming SO’s superior interfacial properties. Combining 0.3% SO with 0.5% n-pentanol results in a 98% viscosity reduction. The emulsion shows excellent stability, with no water separation in the first 30 min and only 8.3% after 2 h. Physical simulation results show that in high(low) permeability core displacement experiments, system flooding and subsequent water flooding can increase recovery rates by 15.39%(36.91%), indicating the system’s potential for enhancing oil recovery in Reservoir X. The findings suggest that the implementation of this system not only boosts the crude oil recovery rate but also carries economic significance in the industry.

A Passenger Ship Emergency Evacuation Line Efficiency Evaluation Operator Considering Safety Capacity and its Application

Introduction: Aiming at evaluating the efficiency of passenger ship emergency evacuation routes, this study proposes an evaluation operator for passenger ship emergency evacuation routes, and then conducts simulation research on the passenger ship evacuation process. Method: The main innovations of this study are as follows. Firstly, this study proposes an evaluation operator for passenger ship emergency evacuation lines based on consideration of the passage capacity, ship heeling effect, traffic flow obstruction, personnel evacuation mood, accident location, and other factors. Secondly, this study discretizes the emergency evacuation path of passenger ships into a three-dimensional topological network structure and uses simulation data to calculate the traffic capacity between nodes. By comparing the calculated value with the simulated value, a risk assessment method for emergency evacuation is given. Thirdly, this study takes the three-story ro-ro passenger ship in the European "SAFEGUARD" project as an example and gives three passenger ship evacuation simulation processes under different passenger flow densities. Result: The results of the calculation example show that the risk-prone areas are mainly concentrated in the passenger ship stairs, and the risk value increases with the passenger flow. Conclusion: The calculation results verify the effectiveness of the emergency evacuation line efficiency evaluation operator proposed in this study.

Simulation Research on the Dual-Electrode Current Excitation Method for Distance Measurements While Drilling

Based on a comprehensive analysis of the existing methods for measuring adjacent well distances, along with their advantages and disadvantages, this study employs theoretical analysis, simulation experiments, and other comprehensive research methods to investigate a distance measurement method based on current excitation. In response to the need for measuring and controlling the connection of relief wells, a method utilizing dual-electrode current excitation during drilling is proposed. This approach facilitates synchronous excitation measurements while drilling, significantly reducing both time and costs while ensuring safety and efficiency, making it particularly suitable for the connection operation of relief wells that involve safety risks. Firstly, this paper establishes a drilling with measurement model corresponding to the excitation mode, which derives the calculation formulas for the target casing current amplitude attenuation, as well as the induced magnetic field distribution within the formation. Additionally, it provides the calculation methods for determining the target well distance and azimuth direction. Lastly, the impact levels of various key factors are verified through numerical calculations and simulation analyses, which confirm the correctness and effectiveness of this distance measurement method. The findings from this research establish both a core theoretical foundation and a technological basis for the real-time measurement of adjacent well distances during relief well operations.

Barrel rifling node offset detection and subsequent optimization based on thin film in-mold decoration characteristics of the Johnson–Cook model

In this paper, a nodal detection method for the detection and optimization of barrel helix offsets is proposed. The barrel used in this experiment is a 6-helix barrel. Moreover, the special properties of the film of Polyetheretherketone (PEEK) material are used to cover the surface of the barrel helix with a virtual in-mold decoration (IMD) film, and the unique nature of the film die offset in the IMD is utilized to detect the position of the barrel helix. The area with a large die index is the area with a large helix offset in the barrel, and the IMD die index is introduced to quantify the data. The IMD die index is used to determine the helix offset of the damaged barrel. The novelty of this work is that each node can use the die index to efficiently detect the position of the barrel helix deviation, carry out subsequent optimization and repair work through the optimization of the injection molding parameters and the design optimization of the barrel and verify the experiment by comparing the results. Through the steady-state simulation research mode, different permutations and combinations of the two process parameters are simulated to study their effects. Quantitative reference indicators include but are not limited to dependent variables such as the fluid flow velocity, shear rate, temperature distribution and phase transition, and the shear heating process of the injection screw is taken into account in the mold flow analysis to ensure that the die index value is more accurate. It can be seen from the analysis results that the temperature of the barrel changes after the groove depth and groove width are changed, and the effect ratio of the groove depth is lower than that of the groove width in the same degree of size change.

Simulation Design and Research of Flame Generation in Virtual Fire Scene Based on Unity3D

Since the 21st century, with the continuous development and progress of science and technology, the possibility of fire danger is also rising, the requirements of public fire safety management have also been improved accordingly, and the problems in its fire safety management work make it difficult to meet the management requirements. The selection of firefighters has also become the top priority of management, good psychological quality of firefighters can keep calm in the face of fire explosions and various emergencies, and can make the most correct choice to complete the rescue and fire fighting work. In this paper, a building in a certain location is selected as the location to simulate the scene of fire. Through human-computer interaction to judge the psychological quality of firefighters. First use major modeling software such as 3ds Max, Adobe Fusecc, or find material in the Unity3D store to create models of fire scenes and people and import them into Unity3D. Using Unity3D's own particle system component to build flame models, adding collision body components to all models to detect their collision detection mechanism and the mechanism of flame spreading combustion. A Scenario-based Communication Ability Evaluation System Based on Traditional Cognitive Behavior Measurement and Advanced Eye Movement, EEG and NIR Acquisition Techniques.

Molecular insights of DGEBA/MeTHPA three-dimensional resin network from design to heat transfer mechanism: Dynamic simulation and experimental research

The epoxy resin composed of bisphenol A diglycidyl ether (DGEBA) and methyl tetrahydrophthalic anhydride (MeTHPA) has been found to enhance its thermal conductivity by increasing its molecular weight and crosslinking density. This was achieved through experiments and all-atom molecular dynamics simulations. Molecular dynamics was employed to calculate the root-mean-square displacement, free volume fraction, potential energy, density, and quantity of hydrogen bonds. The results showed the influence of molecular weight and crosslinking density on the system's thermal conductivity. The results showed that the high molecular weight epoxy resin system exhibited high thermal conductivity at elevated crosslinking densities. During the crosslinking process, the epoxy resin's thermal conductivity increased, starting with the center portion weakening and then strengthening. In addition, a simulation-verified free volume was found to have an inversely proportional connection with thermal conductivity. This study explored the thermal conductivity mechanism of epoxy resin by analyzing the structural changes at the micro level and correlating them with the changes in thermal conductivity at the macro level to enhance guidance for industrial production and practical application.

Simulation of lunar soil compressive strength performance test based on grey correlation analysis

Detecting water ice in the permanent shadow area of the lunar south pole is an important task of China's Chang'e-7. For this purpose, a simulation study was carried out under the earth environment, and a test sample of polar water-containing simulated lunar soil was prepared. The mechanical properties of the lunar soil simulant were tested under ultra-low temperature conditions, and the changes in water content, relative density, temperature, loading rate, and base material ratio with compressive strength were analyzed. The results show that the compressive strength of the frozen lunar soil simulant increases with the increase of water content, increases with the increase of density, and increases with the decrease of temperature. It is less affected by the change of loading rate. The order of compressive strength affected by different base material ratios is: 100%anorthosite, <90%anorthosite, +10%basalt <70%, +30%anorthosite <100%, basalt, lunar soil simulant. Finally, the correlation between the basic physical properties of lunar soil simulant such as water content, relative density, temperature, loading rate, and ratio and compressive strength is explored through grey correlation analysis. The correlation order is: water content> density> temperature> ratio> loading rate. This paper prepared and tested the mechanical properties of hydrated lunar soil, and proposed a more systematic and standardized implementation plan. It serves as the basis for studying the properties of hydrated lunar soil in the polar region, and provides a theoretical basis and reference for subsequent lunar soil simulation research.

Simulation and experimental research on the propagation mechanisms of acoustic energy inside the pipeline to detect the leakage

Leakage from pipelines has negative impacts on property and environment. The diameters of internal acoustic detectors in pipelines are small and not easily blocked, making it suitable for pipelines under various working conditions. Studying the characteristics of pipeline leakage sound signal and the propagation mechanisms within pipelines is crucial for timely detection of small leaks. In this study, a 3D simulation model of pipeline leakage was established, and a CFD/CAA hybrid calculation method was used to obtain effective leakage flow field information via LES. The equivalent sound sources in the flow field were extracted based on the Lighthill acoustic analogy theory. Determine the characteristic frequency range of the leakage sound signal was 1–2 kHz. This study founded that an increase in the leakage pressure and aperture size both lead to an enhancement in the leakage sound signal, and the propagation of leakage sound signal in pipelines is affected by background flow. An experimental pipeline leakage system was designed, and the accuracy of the simulation results was verified experimentally.

Study on pedestrian evacuation simulation model considering group behavior

As a crowded place on the university campus, the cafeteria inevitably has many safety hazards, such as fire accidents caused by open flames and large appliances, stampede accidents caused by overcrowding during peak dining hours, etc. Therefore, studying pedestrian evacuation in university campus cafeterias is particularly necessary. Pedestrians on campus mostly travel in groups. Previous studies mainly used continuous models to discuss pedestrian group evacuation behavior. In this study, based on the cellular automaton pedestrian evacuation simulation model, the floor field calculation method was improved. A cellular automaton pedestrian evacuation simulation model considering group behavior was established and applied to the evacuation scenario of students in a university campus cafeteria. The study found that under the different group configurations, the pedestrian ratios, and the pedestrian densities, the pedestrian evacuation efficiency had significant differences. The results showed that when the different group configurations existed in the scenario, the higher the proportion of the pedestrians with three-person front-to-back group configurations, the higher the evacuation efficiency. When only one type of the group configuration existed in the scenario, at low pedestrian density, the evacuation efficiency of the individual pedestrian groups was higher compared to the other six group configurations. While at high pedestrian density, the evacuation efficiency of the three-person front-to-back group configurations was higher. These findings provided important references for pedestrian evacuation in university campus cafeterias and provided insights for the simulation research of group pedestrian evacuation models, contributing to enhancing campus safety management and ensuring the safety of teachers, students, and staff.

Simulation Research on the Control Method of Bow-Collapse in Gear Cold Roll-Beating

Bow-collapse is a type of geometric defect in the gear cold roll-beating process. In order to effectively control bow-collapse and improve material utilization, this paper calculates the cross-section radius of the blank according to the volume invariance principle of metal plastic deformation, and then performs FE simulation of the cold roll-beating process by using the cyclic beating of adjacent tooth spaces and intermittent blank feeding method. The flow state of metal particles is investigated, revealing that the movement of metal particles along the axial direction of the blank is the main reason for the formation of bow-collapse. This paper proposes a method to correct the cross-section radius of the blank and thus control for bow-collapse, where the loss coefficient K characterizes the state of metal particle loss in an infinitesimal thickness region on the cross-section. The analytical equation for calculating the corrected value of the cross-section radius is derived, and the corrected value is calculated. Conducted on the modified blank, cold roll-beating FE simulation results show that bow-collapse is effectively controlled, and the loss coefficient K correctly reflects the loss state of metal particles on the cross-section. The simulation results also show that after cold roll-beating, the gear teeth with standard face width and tooth depth can be obtained after two turning end faces and turning tip circle processes. The bow-collapse control method proposed in this paper effectively improves material utilization.