Simulation Module Research Articles

Influence of flaps deflection angle on aerodynamic performance of aircraft

Flaps, as one of the lift-augmentation devices installed on aircraft, provide sufficient lift during takeoff and landing phases. By installing flaps on the wing, the wing area can be increased, and the wing curvature can be modified. by adjusting the position of the flaps, the aircrafts aerodynamic characteristics can be regulated. This article focuses on studying the impact of forces on trailing edge flaps during takeoff. As finding the appropriate angle of deflection is a crucial factor in improving flight efficiency, this article primarily investigates the influence of flap deflection angles on the aerodynamic forces acting on the aircraft during low-speed flight. The Flow Simulation module is utilized for the analysis of the flow field. The relation between lift and tilt angle of the flap is obtained from numerical simulations. Through the analysis, for the chosen type of flaps configuration, the optimal flap angle for takeoff is 45. This article may offer a reference for the design of flaps.

Simulation Of Startup Speed of DC Motor Using PI And PID Control

Proportional-Integral (PI) control and Proportional-Integral-Derivative (PID) control have found widespread application across various disciplines. This article focuses on the impact of PI and PID control on the startup speed of the Direct-Current (DC) motor. By setting up a simulation circuit and simulation module, the gain parameters of the control module are adjusted to obtain different output results. The simulation circuit will involve the DC motor, the control module, and the desired speed input. By adjusting the gain parameters of the control module, the behavior of the motor's startup speed can be simulated and observed. For PI control, increasing both the proportional gain and the integral gain proportionally can lead to shorter settling time and smaller overshoot in the output response. For PID control, increasing the derivative gain can significantly reduce the settling time without causing a significant change in the overshoot. When comparing PI and PID controllers, the addition of the derivative term can improve the output performance. By simulating different control modules and adjusting the gains, it is possible to qualitatively identify controllers with better control performance and more suitable gain parameters. This provides insights for the future design and application of DC motor control modules.

Analysis of preload modal characteristics of hydraulic cylinders based on finite element method

In order to study the dynamic response of hydraulic cylinders under complex load conditions, the modal characteristics of hydraulic cylinders were simulated and calculated by comprehensively considering the combined effects of preload and oil fluid dynamics. The contact in the finite element model was specially processed to ensure that the local degrees of freedom of the piston in the structure were maintained during the modal simulation calculation process. After the static characteristics were calculated, the relevant data was imported into the modal simulation module to achieve coupling analysis under preload. By verifying the contact stiffness factor, the boundary conditions of the model were effectively optimized. The natural frequencies of the model were compared and analyzed under different piston strokes, and the mechanism of dynamic response was obtained. Through modal testing, the results indicated that the simulation results had high accuracy and reliability.

SolidWorks Flow Simulation: Selecting the optimal mesh for conducting CFD analysis on a centrifugal fan

The accuracy of mesh use determines the suitability of simulation results with experimental test results, therefore it is necessary to study the type and number of mesh used for flow simulation. This study aims to investigate the type of mesh and the number of cells that are appropriately used in the simulation of centrifugal fans using the Solidworks Flow Simulation module. The research was conducted by comparing the simulation results with the experimental results on centrifugal fans that have been carried out by previous studies. In this research, the type of mesh used is global mesh. The parameter of determining the number of cells is done by varying the mesh level because the mesh level affects the number of cells. In this simulation study, the boundary condition is set to one flow volume of 5 m3/h and a rotation speed of 92.362 rad/s. In this study, the total pressure and efficiency of the centrifugal fan are the things that are seen from the comparison of flow simulation with the experiment. Based on the simulation results that have been carried out, mesh levels 1 to 4 show results that differ significantly from the experimental results. At machine levels 5 to 7, the results are close to the experimental results, but the closest total pressure and efficiency values are at mesh level 5. The results of this study can be a reference for research that simulates centrifugal fans.

Selection of Real-Coded Genetic Algorithm parameters in solving simulation–optimization problems for the design of water distribution networks

Abstract The design of the water distribution network (WDN) is very difficult mainly due to the nonlinear relation between head and flow. The distribution network should also be cost-effective. In any simulation–optimization approach, the computational time requirement is very high for very complex problems. The optimization module plays a crucial role in reducing the computational time. This study aims to apply a simulation–optimization approach to designing a WDN. EPANET is selected as the simulation model and Real-Coded Genetic Algorithm (RCGA) is selected as the optimization module. To link the simulation module with the optimization module, a program is written in MATLAB. The developed simulation–optimization approach was applied to two benchmark network problems to check the suitability of the method. The parameters of the RCGA were optimized for the two networks. The computational efficiency of the developed simulation–optimization model is checked based on the number of function evaluations. For both networks, the number of function evaluations to get the optimum network design was less than the number of function evaluations required for other methods mentioned in the literature.

A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis

Alleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solution to overcome such limitations. In this paper, a novel semiautonomous control system (SCS) for wrist–hand prostheses using a computer vision system (CVS) is proposed and validated. The SCS integrates object detection, grasp selection, and wrist orientation estimation algorithms. By combining CVS with a simulated EMG-based intention detection module, the SCS guarantees reliable prosthesis control. Results show high accuracy in grasping and object classification (≥97%) at a fast frame analysis frequency (2.07 FPS). The SCS achieves an average angular estimation error ≤18° and stability ≤0.8° for the proposed application. Operative tests demonstrate the capabilities of the proposed approach to handle complex real-world scenarios and pave the way for future implementation on a real prosthetic device.

A56Using simulation to address staff wellbeing and retention in a global non-healthcare organization

Stress, anxiety and depression affect one-fifth of the working age population and are a leading cause of staff attrition and loss of productivity [1]. Conversations between colleagues can help reduce stress, increase job satisfaction and productivity, build stronger relationships, and create a more positive work environment [2]. In spite of numerous policy initiatives in large organizations and fewer in small [3], it is reported, by colleagues, that hands on ‘practice’ in having conversations would be beneficial. We were approached to create a remote live four-hour workshop with authentic simulated scenarios, appropriate for a cross cultural global reach, aiming to enable staff to feel ‘at ease’ with having proactive conversations with their colleagues on a daily basis. In 2021-2022, 120 hours were spent developing a live module for managers working in non-healthcare environments. This module was preceded by three online eLearning modules, ‘being aware, being proactive and being responsive’. After eight pilots, content and delivery was scrutinized, analysing feedback from participating managers, facilitators, and actors. In 2023, a further 24 workshops are underway, using the refined content and delivery structure; 144 actors, 24 facilitators and 24 simulation advisers are involved. Participants are global managers, clustered into geographical regions; module timings are amended to suit time zones and in total 192 participants are able to take part in small groups of eight. A 90 minute follow up a month later enables participants to discuss the personal areas of identified focus. Creating a safe space has been essential, with ongoing facilitator alertness. Participants have immersed themselves in the six scenarios covering loneliness, disillusion, over-work, depression, crisis and acute anxiety. Participants key areas of focus have included: being sensitive to situations, being a better observer, sharing values with staff, spending time with colleagues, scheduling time to look after oneself. Timekeeping to ensure equity of discussion and involvement, and arrival and integration of the six actors have both been challenging, although mitigated by the pilot experience. This programme, incorporates online eLearning modules, a remote ‘live’ simulated module, and follow-up group sessions. By practising through simulated scenarios, there is significant potential to improve the support, retention and wellbeing of employees within this non-healthcare organization. The programme’s global scope, with five regions, highlights its relevance and applicability to a diverse range of workplaces. There is potential for replication in other organizations facing similar challenges, ultimately impacting on our society as a whole. Authors confirm that all relevant ethical standards for research conduct and dissemination have been met. The submitting author confirms that relevant ethical approval was granted, if applicable.

세기관지염 환아를 위한 시뮬레이션 교육 모듈개발 및 수행능력평가

Research Purpose: This study aimed to provide baseline data for improving pediatric nursing simulation education. It developed and applied a tailored simulation practice learning module for the nursing department.
 Research Period & Participants: From September 16 to October 28, 2022, 97 third-year students at C Nursing College participated, focusing on pediatric nursing simulation classes.
 Research Results: After the simulation practice on bronchiolitis pediatric nursing, high scores were observed in both peer and self-evaluation. Clinical performance also showed marked improvement post-simulation education.
 Recommendations: Given the inherent challenges of experiencing direct procedures in pediatric nursing, more frequent simulation-based experiences are crucial. Furthermore, there's a pressing need for ongoing development of pediatric simulation modules resembling real clinical settings.

Assessing the training effect of knee arthroscopy cognitive-task surgical simulations on the theoretical and technical knowledge acquisition in novices

Background The COVID-19 pandemic had drastic consequences on medical education, especially in surgical exposure and procedural learning. Cognitive task analysis (CTA) simulators, including Touch Surgery, are gaining prominence as a learning tool for surgical training in a low-risk environment virtually. The study objective was to investigate the training effect of Touch Surgery’s knee arthroscopy module in both theoretical and technical knowledge acquisition for novices, and qualitative feedback on CTA simulators for surgical education. Methods Thirteen medical students were recruited in an Institutional Review Board-approved study to complete the knee arthroscopy simulation module on Touch Surgery, a clinically validated, cognitive task mobile-app based surgical simulator. Participants were given an expert-validated questionnaire evaluating surgical theory and technique on knee arthroscopy before and after at least three consecutive attempts on the module, along with qualitative questions assessing attitudes towards using the platform. A 2-tailed paired Student t-test was used to assess for statistically significant changes between pre- and post-study scores, with p-value < 0.05 considered significant. Results Mean scores for pre- and post-simulator use demonstrated statistically significant improvements for technical and overall knowledge acquisition (p < 0.05). Improvement in theoretical knowledge acquisition was also observed, but the difference was not statistically significant (p = 0.052). Participants generally found the app “easy to use”, “fun to use” and “more interactive compared to other study material”. Conclusion CTA simulators provide an effective means of technical knowledge acquisition for novices such as medical students, and serve as an engaging and useful training adjunct for surgical education.

Using Gamification to Develop Students As Strategic Thinkers – A Qualitative Perspective

The use of gamification as an instructional strategy has gained significant attention in recent years as a way of increasing student engagement and motivation. Gamification involves the application of game design principles to non-game contexts, such as higher education. One area in which gamification has shown particular promise is in developing students' strategic thinking abilities. This qualitative study explores university students' post-module reflections on their experience of working in teams over the course of a seven-week intensive postgraduate business analytics simulation module. Reflections were analysed using thematic analysis to identify common themes and patterns with respect to students’ strategic thinking in terms of decision-making. The study findings strongly suggests that gamification, particularly the use of business simulations, can be an effective tool for developing students' strategic mindsets, in terms of the process for decision-making, impact of critical incidents, the lessons they learned and corrective action taken, along with the role of the team itself.

Simulation tools for net-positive process design: Trees as unit operations for carbon sequestration and air quality regulation

Chemical processes have significant environmental and societal impacts, such as climate change and human health, due to air and water pollution. In addition, chemical processes consume unsustainable amounts of natural ecosystems’ goods and services. Engineers have tried to address these challenges by reducing waste, integrating processes, and minimizing the consumption of raw materials and energy. However, these efforts have not been enough to address the impact of the process on natural ecosystems and local communities. Hence, the need to integrate ecological systems into traditional engineering design to provide sustainable and cost-effective solutions. Although models for ecological systems are readily available in the literature, engineers are hesitant to utilize these models without familiar tools and the traditional undervaluation of ecosystem services’ role and the uncertainty of their performance. To overcome some of these barriers, ecosystems can be classified as unit operations since they can be designed to achieve specific tasks. This work focuses on integrating vegetation as unit operations in process design to remove air pollutants and sequester carbon. We developed a practitioner-friendly simulation module in CHEMCAD that utilizes sophisticated rural and urban forestry models developed by the online i-Tree assessment tool. We demonstrate the module through a power plant case study and highlight some alternative spatially explicit integrated designs that are environmentally and economically superior.

Radial Centrifugal Fan Redesign and New Technologies Using CFD Applications

The purpose of this article is to redesign centrifugal radial fans used in HVAC installations, using the analysis of aerodynamic flows and velocities distributions in the fan. Numerical simulations based on the reference model from the Pumps and Fans laboratory were performed using the SolidWorks program, Flow Simulation module. Following the simulations, information regarding the fluid flow in the machine rotor and casing, the most suitable shape of the blades resulted, and redesign solutions through 3D printing technologies were proposed. Numerical simulations with Flow Simulation on three-dimensional models were carried out, for a better analysis of the volume of air passing through the fan, but also for the prediction of some negative effects: the appearance of vortices that lead to high noises/acoustic disturbances, the appearance of additional vibrations, but also sudden and uncontrolled variations in the pressure force. Following the numerical analysis, it was found that for the new blade profiles the velocities are uniform, which greatly reduces the noise and vibrations in the operation of the fan. The redesign also aims to reduce the energy consumption of these fans.

Numerical Simulation and Design of Ensemble Learning Based Improved Software Development Effort Estimation System

This research paper proposes a novel approach to improving software development effort estimation by integrating ensemble learning algorithms with numerical simulation techniques. The objective of this study is to design an ensemble learning-based software development effort estimation system that leverages the strengths of multiple algorithms to enhance accuracy and reliability. The proposed system combines the power of ensemble learning, which involves aggregating predictions from multiple models, with numerical simulation techniques that enable the modelling and analysis of complex software development processes. A diverse set of software development projects is collected, encompassing various domains, sizes, and complexities. Ensemble learning algorithms such as Random Forest, Gradient Boosting, Bagging, and AdaBoost are selected for their ability to capture different aspects of the data and produce robust predictions. The proposed system architecture is presented, illustrating the flow of data and components. A model training and evaluation pipeline is developed, enabling the integration of ensemble learning and numerical simulation modules. The system combines the predictions generated by the ensemble models with the simulation results to produce more accurate and reliable effort estimates. The experimental setup involves a comprehensive evaluation of the proposed system. A real-world dataset comprising historical project data is utilized, and various performance metrics, including Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), are employed to assess the effectiveness of the system. The results and analysis demonstrate that the ensemble learning-based effort estimation system outperforms traditional techniques, showcasing its potential to enhance project planning and resource allocation.

Learning a simulation-based visual policy for real-world peg in unseen holes.

This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation and adapting to arbitrary unseen shapes in the real world with minimal sim-to-real cost. The core idea is to decouple the generalization of the sensory-motor policy from the design of a fast-adaptable perception module and a simulated generic policy module. The framework consists of a segmentation network (SN), a virtual sensor network (VSN), and a controller network (CN). Concretely, the VSN is trained to measure the pose of the unseen shape from a segmented image. After that, given the shape-agnostic pose measurement, the CN is trained to achieve a generic peg-in-hole. Finally, when applying to real unseen holes, we only have to fine-tune the SN required by the simulated VSN + CN. To further minimize the transfer cost, we propose to automatically collect and annotate the data for the SN after one-minute human teaching. Simulated and real-world results are presented under the configuration of eye-to/in-hand. An electric vehicle charging system with the proposed policy inside achieves a 10/10 success rate in 2-3s, using only hundreds of auto-labeled samples for the SN transfer.

비디오 모델링을 이용한 출생 직후 고위험 신생아간호 시뮬레이션 교육이 간호대학생의 의사소통 자기효능감, 비판적 사고능력, 임상수행능력에 미치는 효과

Purpose : The purpose of this study is to analyze the effect of high-risk neonatal nursing simulation education using video modeling on the communication self-efficacy, critical thinking ability and clinical performance in nursing students.
 Methods : A non-equivalent control group pretest-posttest design was used. The experimental group applied a video modeling simulation program, and the control group applied a scenario-based role play-oriented simulation program. The study participants included 78 nursing students (40 in experimental group and 38 in control group) from G city. A simulation module consisted of a orientation and lecture, pre-learning, problem-based learning, scenario operation, debriefing. Data were analyzed using χ² -test, independent t-test, Fisher’s exact test, paired t-test, ANCOVA.
 Results : The experimental group showed a significant increase in communication self-efficacy (t＝2.33, p＝.023, d＝.538) and clinical competence (F＝17.50, p＜.001, ηp² ＝.189) compared to the control group.
 Conclusion : The High-risk neonatal nursing simulation program using video modeling was effective in improving students’ communication self-efficacy and clinical competence. The neonatal nursing simulation education using video modeling applied in this study is expected to be one of the learning strategies that can significantly increase the effectiveness of HFS by adding learning methods tailored to the needs of students familiar with the media.

Mixed Reality as a Teaching Tool for Medical Students in Neurosurgery.

Background and Objectives: Simulation-based learning within neurosurgery provides valuable and realistic educational experiences in a safe environment, enhancing the current teaching model. Mixed reality (MR) simulation can deliver a highly immersive experience through head-mounted displays and has become one of the most promising teaching tools in medical education. We aimed to identify whether an MR neurosurgical simulation module within the setting of an undergraduate neurosurgical hands-on course could improve the satisfaction of medical students. Materials and Methods: The quasi-experimental study with 223 medical students [120 in the conventional group (CG) and 103 in the MR-group (MRG)] was conducted at the University Hospital Münster, Münster, Germany. An MR simulation module was presented to the intervention group during an undergraduate neurosurgical hands-on course. Images of a skull fracture were reconstructed into 3D formats compatible with the MR-Viewer (Brainlab, Munich, Germany). Participants could interact virtually with the model and plan a surgical strategy using Magic Leap goggles. The experience was assessed by rating the course on a visual analog scale ranging from 1 (very poor) to 100 (very good) and an additional Likert-scale questionnaire. Results: The satisfaction score for CG and MRG were 89.3 ± 13.3 and 94.2 ± 7.5, respectively. The Wilcoxon rank-sum test showed that MR users (Mdn = 97.0, IQR = 4, n = 103) were significantly more satisfied than CG users (Mdn = 93.0, IQR = 10, n = 120; ln(W) = 8.99, p < 0.001) with moderate effect size (r^biserial = 0.30, CI95 [0.15, 0.43]), thus indicating that the utilization of MR-simulation is associated with greater satisfaction. Conclusions: This study reports a positive response from medical students towards MR as an educational tool. Feedback from the medical students encourages the adoption of disruptive technologies into medical school curricula.

Real-Time Selection System of Dispatching Rules for the Job Shop Scheduling Problem

Personalized market demands make the job shop scheduling problem (JSSP) increasingly complex, and the need for scheduling methods that can solve scheduling strategies quickly and easily has become very urgent. In this study, we utilized the variety and simplicity of dispatching rules (DRs) and constructed a DR real-time selection system with self-feedback characteristics by combining simulation techniques with decision tree algorithms using makespan and machine utilization as scheduling objectives, which are well adapted to the JSSP of different scales. The DR real-time selection system includes a simulation module, a learning module, and an application module. The function of the simulation module is to collect scheduling data in which is embedded a novel mathematical model describing the JSSP; the function of the learning module is to construct a DR assignment model to assign DR combinations to the job shop system, and the function of the application module is to apply the assigned DR combinations. Finally, a series of job shop systems are simulated to compare the DR assignment model with the NSGA-II and PSO algorithms. The aim is to verify the superiority of the DR assignment model and the rationality of the DR real-time selection system.

Mar-RUL: A remaining useful life prediction approach for fault prognostics of marine machinery

Although the maritime industry has the potential to lead smart maintenance methodologies, current maintenance routines within the sector focus on either reactive or preventive maintenance approaches. These approaches are increasingly conservative and often prompted by an increase of large costs or unnecessary maintenance actions. Attempts are being made, however, to optimise these costs and actions through the application of novel practices, such as the employment of prognostic-based maintenance, which is an approach that aims to minimise risk while maximising the lifespan of a system. In this respect, Mar-RUL is introduced to support Operations & Maintenance (O&M) decision making and address some of the main challenges that the sector is currently experiencing, including the lack of fault data analysis and the formalisation of deep learning technologies for the implementation of the Remaining Useful Life (RUL) prediction. In response, a degradation data simulation module is developed in tandem with an ensemble model comprised of three distinct deep learning architectures: Markov-Convolutional Neural Network (CNN), 1D-CNN, and Long Short-Term Memory (LSTM) neural network. To evaluate the performance of Mar-RUL, a case study on the turbocharger of a diesel generator of a tanker ship is presented. The case study results demonstrated that the application of time series imaging and ensemble methods can provide promising outcomes for the enhancement of RUL prediction.

Child Death in a Resource-Limited Setting: A Simulation Case for Pediatric Residents to Prepare for Global Health Electives.

Pediatric residents are increasingly pursuing global health electives. Differences in cultural norms and management around pediatric deaths in resource-limited settings can be emotionally overwhelming for residents. Educational resources are needed to better equip them for handling these stressful situations. We developed a predeparture simulation child death case to prepare pediatric residents for their global health elective. The simulation module included a clinical case followed by a multidisciplinary structured debriefing. The case featured a 5-year-old, malnourished child in hypovolemic shock who clinically deteriorates and dies. After obtaining a history and performing a physical examination, residents were expected to diagnose severe malnutrition, treat hypovolemic shock, and decide how far to extend resuscitation with the limited resources. Upon returning from abroad, residents were invited to complete a survey on the utility of the simulation case module in preparing for their elective. Twenty-nine residents participated in the simulation case module, and 18 completed the survey. Seventeen agreed or strongly agreed that the simulation module was a useful tool for preparation (Mdn = 4.5 on a 5-point Likert scale). Residents reflected that the simulation module helped manage expectations and provided them with an understanding of the cross-cultural differences in managing pediatric deaths in a resource-limited setting. Pediatric residents trained in resource-rich countries do not encounter death often. Postgraduate training programs could consider simulations like this one to prepare such residents for cross-cultural differences in managing pediatric deaths and build resiliency to operate in resource-limited settings.

Investigation of Numerical Simulation for Adaptive Optics System

In this study, the performance of the adaptive optics (AO) system was analyzed through a numerical computer simulation implemented in MATLAB. Making a phase screen involved turning computer-generated random numbers into two-dimensional arrays of phase values on a sample point grid with matching statistics. Von Karman turbulence was created depending on the power spectral density. Several simulated point spread functions (PSFs) and modulation transfer functions (MTFs) for different values of the Fried coherent diameter (ro) were used to show how rough the atmosphere was. To evaluate the effectiveness of the optical system (telescope), the Strehl ratio (S) was computed. The compensation procedure for an AO system was implemented. Analytical analysis was used to define the wave front and aberrations of the circular aperture telescope. Zernike polynomials were used to describe the residual error and figure out how much the compensation changed the measured turbulence values. The results of the computer simulation involving atmospheric turbulence reveal that elevating the ro values (4, 8, 12, 16, 20, 24, 28, 32) cm resulted in a 3.4% rise in S. However, when the adaptive optics system operated with a constant ro (20 cm), augmenting the Zernike aberration modes led to a remarkable 44% increase in S, signifying a substantial enhancement in the compensation procedure.