Simulation Design Research Articles

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups

In settings requiring synthetic data generation based on a clinical cohort, e.g., due to data protection regulations, heterogeneity across individuals might be a nuisance that we need to control or faithfully preserve. The sources of such heterogeneity might be known, e.g., as indicated by sub-groups labels, or might be unknown and thus reflected only in properties of distributions, such as bimodality or skewness. We investigate how such heterogeneity can be preserved and controlled when obtaining synthetic data from variational autoencoders (VAEs), i.e., a generative deep learning technique that utilizes a low-dimensional latent representation. To faithfully reproduce unknown heterogeneity reflected in marginal distributions, we propose to combine VAEs with pre-transformations. For dealing with known heterogeneity due to sub-groups, we complement VAEs with models for group membership, specifically from propensity score regression. The evaluation is performed with a realistic simulation design that features sub-groups and challenging marginal distributions. The proposed approach faithfully recovers the latter, compared to synthetic data approaches that focus purely on marginal distributions. Propensity scores add complementary information, e.g., when visualized in the latent space, and enable sampling of synthetic data with or without sub-group specific characteristics. We also illustrate the proposed approach with real data from an international stroke trial that exhibits considerable distribution differences between study sites, in addition to bimodality. These results indicate that describing heterogeneity by statistical approaches, such as propensity score regression, might be more generally useful for complementing generative deep learning for obtaining synthetic data that faithfully reflects structure from clinical cohorts.

Simulation Design of a Triple Antenna Combination for PET‐MRI Imaging Compatible With 3, 7, and 11.74 T MRI Scanner

ABSTRACTThe use of electromagnetism and the design of antennas in the field of medical imaging have played important roles in clinical practice. Specifically, magnetic resonance imaging (MRI) utilizes transmission and reception antennas, or coils, that are tuned to specific frequencies depending on the strength of the main magnet. Clinical scanners operating at 3 Teslas (T) function at a frequency of 127 MHz, while research scanners at 7 T operate at 300 MHz. An 11.74 T scanner for human imaging, which is currently under development, will operate at a frequency of 500 MHz. MRI allows for the high‐definition scanning of biological tissues, making it a valuable tool for enhancing images acquired with positron emission tomography (PET). PET is an imaging modality used to evaluate the metabolism of organs or cancers. With recent advancements in the development of portable PET systems that can be integrated into any MRI scanner, we propose the design based on electromagnetic simulations of a triple‐tuned array of dipole antennas to operate at 127, 300, and 500 MHz. This array can be attached to the PET inset and used in 3, 7, or 11.74 T scanners.

Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study

Molecular biology is a complex, abstract, subject that can be challenging for higher education students to comprehend. The current manuscript describes the design, implementation, and evaluation of two immersive VR simulations of a DNA lab and a crime scene investigation (CSI) for a forensic molecular biology course in the context of the “TESLA” Erasmus+ project. It illustrates the instructional design and technical aspects of the VR simulations’ development. The experimental study employed a comparative quantitative research design. The guiding research questions examined how instructional modalities (online vs. face-to-face) affect learners’ perceptions of VR-based training in higher education and the key factors influencing learners’ intention for their adoption. Forty-six (n = 46) undergraduate students completed a 17-item questionnaire, which served as the main data collection instrument. Results demonstrate that both online and face-to-face VR-based instruction can effectively convey core concepts, thus challenging the traditional notion that face-to-face interaction is inherently superior. Its implications underscore the potential of VR simulations to supplement or even substitute traditional teaching methods, particularly for complex science subjects.

Inverse problem for thermal radiation distribution on turbine blade under quartz lamp irradiation

Due to the strong time-varying characteristics and complex geometry of aerospace components, rapid changes in the distribution of radiative heat flux on the test surface are often required during non-uniform aerodynamic heating tests. However, it takes time to adjust the geometric parameters of the lamp array, which cannot meet the requirement for rapidly changing radiative heat flux distribution. To address this issue, a new method for calculating radiant heat flux and a fast linear analysis method of quartz lamp power are proposed which can calculate radiant heat flux distribution of complex surface and meet the need of timeliness and rapidity in radiant heat flux distribution, making it more suitable for engineering applications. Through numerical verification under single lamp and quartz lamp array, the maximum difference between the theoretical analysis method and the Monte Carlo method is less than 2.25% under single lamp, and less than 5% under quartz lamp array. Finally, turbine blade model and plane model are taken as research objects to verify the feasibility and reliability of the fast linear analysis method of quartz lamp power. The results show that the relative average error of the calculated quartz lamp power is 5.86% and 14.83%, respectively, compared with the actual power. This provides a reference and basis for the rapid simulation design of thermal radiation environment during the experiment.

Modifications to ArduSub That Improve BlueROV SITL Accuracy and Design of Hybrid Autopilot

Improvements to ArduSub for the BlueROV2 (BROV2) Heavy, necessary for accurate simulation and autonomous controller design, were implemented and validated in this work. The simulation model was made more accurate with new data obtained from real-world testing and values from the literature. The manual control algorithm in the BROV2 firmware was replaced with one compatible with automatic control. In a Robot Operating System (ROS), a proportional–derivative (PD) controller to assist augmented reality (AR) pilots in controlling angular degrees of freedom (DOF) of the vehicle was implemented. Open-loop testing determined the yaw hydrodynamic model of the vehicle. A general mathematical method to determine PD gains as a function of the desired closed-loop performance was outlined. Testing was carried out in the updated simulation environment. Step response testing found that a modified derivative gain was necessary. Comparable real-world results were obtained using settings determined in the simulation environment. Frequency response testing of the modified yaw control law discovered that the bandwidth of the nonlinear system had a one-to-one correspondence with the desired closed-loop natural frequency of a simplified linear approximation. The control law was generalized for angular DOF and linear DOF were operated with open-loop control. A full six-DOF simulated dive demonstrated excellent tracking.

Street landscape environment design based on visual technology and entertainment robots: Computer simulation gamification landscape design

In recent years, with the development of social economy and the innovation of science and technology, the street landscape environment design based on visual technology and entertainment robot has been widely concerned. This paper aims to explore how to use computer simulation and gamification design methods to enhance the entertainment and attractiveness of street landscapes. In this paper, the basic principles of computer vision and V2X vehicle networking are deeply studied, and a series of simulation experiments and data analysis are carried out in combination with actual scenarios to verify the feasibility and effectiveness of V2X vehicle networking mode based on computer vision in urban street landscape design. V2X vehicle networking mode through real-time information exchange with road infrastructure, other vehicles, pedestrians, etc., can obtain a large number of urban streetscape design related data. Studies have shown that this design approach can increase people’s interest and engagement in street landscapes, and increase the entertainment experience and sense of interaction of urban residents.

Optimizing Cr(VI) reduction to Cr(III) using Pd-CNTs nanocatalyst: kinetic Monte Carlo simulation and experimental design insights

In this investigation, we explored the kinetics of Cr(VI) reduction to Cr(III) on carbon nanotube decorated with palladium (Pd-CNTs) nanocatalyst, using formic acid as the reducing agent. This study has been bone utilizing kinetic Monte Carlo simulation and experimental design methods. The mechanism and kinetic parameters of this reaction are provided. The effect various factors such as reaction time, pH level, dichromate (Cr2O72−) concentration, and formic acid concentration on Cr(VI) reduction was studied. Concentrations of HCOOH and Cr2O72− were identified as the crucial variables, while the HCOOH concentration has the most significant impact. Positive influences on Cr(VI) reduction were observed with increasing pH level and HCOOH concentration. Reaction time positively affects on Cr(VI) reduction efficiency. However, the concentration of Cr2O72− showed an increasing effect up to a threshold, negatively impacting the efficiency. The optimal conditions (Reaction time = 60 min, pH = 4.5, [Cr2O72−] = 5.05 × 10−3 M, and [HCOOH] = 0.95 M) for Cr(VI) reduction. At optimal conditions, the Cr(VI) reduction efficiency was obtained to be 100%.

Student informed development of virtual reality simulations for teaching and learning in the molecular sciences

ABSTRACT The development of accurate spatial conceptualisations of molecular biology structures, processes and interactions represents a critical learning outcome for a wide array of life sciences students. In this study, we investigated student learning through a bespoke virtual reality (VR) simulation focused on interactive assembly of an expression vector and visualisation of the recombinant protein expression process, encompassing constructivist pedagogical principles. A mixed methods approach was pursued involving surveys, assessments, and online simulation data capture to facilitate student partnered inputs into virtual simulation design and implementation in the teaching of molecular and cellular biology. The scope of student learning modalities, effective teaching practices and perspectives on challenging curriculum were also captured to position VR implementation within a wider learning framework. Students expressed a consensus view towards the application of this innovative teaching modality and appear well equipped to adapt to this new teaching and learning approach. The visual and kinaesthetic elements of the simulations were found to offer a unique entry point to challenging and abstract molecular concepts that has the potential to transform life science education for students, where a partnership approach can best deliver a roadmap for effective integration into the curriculum.

The design and implementation of virtual reality simulations in Spanish for the Health Professions: what are learners’ perceptions?

Although virtual reality (VR) games and headsets are widely available and have started to be used in language courses, there is little previous research on how VR can be used in courses on Languages for Specific Purposes, particularly in Spanish for the Health Professions. The purpose of this study was to develop and implement VR simulations that mirrored a medical interview in Spanish and to examine learners’ attitudes toward language practice in a VR environment. Scenarios were designed following Task-Based Language Teaching and results from a language needs analysis. Participants in this study were undergraduate students enrolled in a Spanish for the Health Professions course. Participants took on the role of a healthcare provider to interact with Spanish-speaking avatars within the virtual environment. They completed a series of tasks relevant to the medical interview, including greetings, triage, symptom elicitation, social information, medication information, basic diagnosis, and treatment plan. They participated in surveys and wrote journals about their VR class experience. Results showed that the VR simulations contributed to perceived skill development with an emphasis on conversation, listening, critical thinking, and pronunciation. The immersive experience and real-world application led learners to be more engaged and focused while amplifying course topics, particularly cultural awareness and sensitivity, applied vocabulary, and pragmatics. Pedagogical implications are discussed.

Development and Insulation Performance Evaluation of Experimental Sample for a Direct Current High-Voltage Transmission Line

For the negative-ion-based neutral beam injection system, the direct current (DC) high-voltage transmission line (HVTL) is the link between the radio frequency (RF) negative-ion source system and the power supply system, which not only realizes the function of the power transmission between the power supply system and the RF negative-ion source system, but also provides transmission channels for high-pressure cooling water, working gas, and the measurement and control signals needed for the operation of the RF negative-ion sources. In this study, the experimental sample for the DC HVTL is developed based on the insulation simulation design, and an insulation performance evaluation test bed of the experimental sample is designed and built. The insulation performances of the experimental sample at different SF6 gas pressures are investigated, and the leakage current laws of the experimental sample at different applied voltages and different SF6 gas pressures are obtained. The test results show that the maximum leakage current is 472 μA at a loading voltage of 500 kV, which proves that the experimental sample for the DC HVTL satisfies the requirements of the insulation design.

Metamaterial design for aortic aneurysm simulation using 3D printing

IntroductionThe use of three-dimensional (3D) printed anatomic models is steadily increasing in research and as a tool for clinical decision-making. The mechanical properties of polymers and metamaterials were investigated to evaluate their application in mimicking the biomechanics of the aortic vessel wall.MethodologyUniaxial tensile tests were performed to determine the elastic modulus, mechanical stress, and strain of 3D printed samples. We used a combination of materials, designed to mimic biological tissues’ properties, the rigid VeroTM family, and the flexible Agilus30™. Metamaterials were designed by tessellating unit cells that were used as lattice-reinforcement to tune their mechanical properties. The lattice-reinforcements were based on two groups of patterns, mainly responding to the movement between links/threads (chain and knitted) or to deformation (origami and diamond crystal). The mechanical properties of the printed materials were compared with the characteristics of healthy and aneurysmal aortas.ResultsUniaxial tensile tests showed that the use of a lattice-reinforcement increased rigidity and may increase the maximum stress generated. The pattern and material of the lattice-reinforcement may increase or reduce the strain at maximum stress, which is also affected by the base material used. Printed samples showed max stress ranging from 0.39 ± 0.01 MPa to 0.88 ± 0.02 MPa, and strain at max stress ranging from 70.44 ± 0.86% to 158.21 ± 8.99%. An example of an application was created by inserting a metamaterial designed as a lattice-reinforcement on a model of the aorta to simulate an abdominal aortic aneurysm.ConclusionThe maximum stresses obtained with the printed models were similar to those of aortic tissue reported in the literature, despite the fact that the models did not perfectly reproduce the biological tissue behavior.

Aerospike: Mission Simulation and Optimal Design Using Openfoam and Dakota

Aerospike: Mission Simulation and Optimal Design Using Openfoam and Dakota

Civil aircraft air conditioning and refrigeration control system hil simulation design based on NI VeriStand

Civil aircraft air conditioning and refrigeration control system hil simulation design based on NI VeriStand

Health simulation through the lens of self-determination theory — opportunities and pathways for discovery

Health simulation is broadly viewed as an appealing, impactful, and innovative enhancement for the education and assessment of health professions students and practitioners. We have seen exponential and global growth in programmes implementing simulation techniques and technologies. Alongside this enthusiasm and growth, the theoretical underpinnings that might guide the efficacy of the field have not always been considered. Many of the principles that guide simulation design, development and practice have been intuited through practical trial and error. In considering how to retrofit theory to practice, we have at our disposal existing theories that may assist with building our practice, expertise, identity as a community of practice, authority and legitimacy as a field. Self-determination theory (SDT) is an established and evolving theory that examines the quality of motivation and human behaviours. It has been applied to a variety of contexts and provides evidence that may support and enhance the practice of health simulation. In this paper, SDT is outlined, and avenues for examining the fit of theory to practice are suggested. Promising links exist between SDT and health simulation. Opportunities and new pathways of discovery await.

Mechanical performance simulation and optimal design of carbon fiber composite B-pillar

This study primarily concentrates on the layer optimization and structural refinement of carbon fiber composite B-pillars. In the initial phase, an initial layer configuration for the carbon fiber composite material B-pillar was devised, followed by comprehensive finite element numerical simulations. The weight of the B-pillar was effectively diminished by 44.9% compared to its metal counterpart, while maintaining consistent performance across diverse operational conditions. Subsequently, an advanced layer thickness optimization model was formulated, incorporating the innovative ‘super layer’ concept. Integration of simulation software, such as ISIGHT and ABAQUS, facilitated the determination of optimal layer thickness and ratio for the composite material. The layer order was systematically optimized through the application of a discrete particle swarm optimization algorithm based on exchange order, adeptly addressing issues related to discontinuous design variables and potential combinations. The incorporation of a ply drop-off structure laying scheme was derived, resulting in an impressive weight reduction of 57.5%. In the final phase, adherence to NCAP side collision testing standards enabled a comprehensive evaluation, where in various indicators including deformation mode, intrusion amount, and intrusion speed were employed. The results substantiate that the composite B-pillar exhibits equivalent side impact resistance to the original metal B-pillar, ensuring robust passenger protection.

Solving high-dimensional parametric engineering problems for inviscid flow around airfoils based on physics-informed neural networks

Engineering problems often involve solving partial differential equations (PDEs) over a range of similar problem setups, leading to high computational costs when using traditional numerical approaches to solve each setup individually. Recently developed physics-informed neural networks (PINNs) offer a novel approach to solving parametric problems, enabling the simultaneous solution of a series of similar problems. Our previous research combined PINNs with mesh transformation to learn PDE solutions in the computational space, effectively solving inviscid flow around airfoils. In this study, we expand the input dimensions of the model to include shape parameters and flow conditions, forming an input encompassing the complete state-space (i.e., all parameters determining the solution are included in the input). We spend about 18.8 h achieving the continuous solutions in a large state-space in one go, encompassing various subsonic inviscid airfoil flows encountered in engineering, thereby highlighting the model's significant advantages in addressing high-dimensional parametric problems. Once established, the model can efficiently complete airfoil flow simulation and shape inverse design tasks in about 1 s. Furthermore, we introduce a pretraining-finetuning method, enabling the fine-tuning of the model for the task of interest and quickly achieving accuracy comparable to the finite volume method.

An improved wireless power transmission system for micro unmanned aerial vehicles

AbstractDue to its limited load capacity, the piggybacking of wireless charging systems for micro unmanned aerial vehicles has become a challenging task in the design of micro unmanned aerial vehicles. Therefore, this paper proposes an improved lightweight design method for micro unmanned aerial vehicles to carry a wireless charging system. The improved system uses an inductor–capacitor–capacitor‐parallel (LCC‐P) topology compensation network instead of a bilateral inductor–capacitor–capacitor (LCC) topology compensation network to achieve constant current charging (CC) and constant voltage charging (CV). Then the adaptive frequency conversion control is used to realize the automatic conversion from CC charging to CV charging during the charging process. Compared with the traditional wireless charging system based on a direct current‐direct current converter (DC‐DC converter) to achieve CC charging and CV charging, this improved system reduces the total weight of the receiving end of the wireless charging system based on ensuring the charging efficiency, which meets the demand of wireless charging systems carried by micro drone aircraft. The test results of the constructed physical system coincide with the simulation design results, and the total weight of the receiving end is only 8 g, which verifies the correctness and effectiveness of the improved design scheme.

Undergraduate Student Nurses' Satisfaction, Self-confidence, and Perception of High-fidelity Simulation-based Learning on Critically-ill Patients.

Replicating critical care practice settings in high-fidelity simulation (HFS) provides more learning opportunities to develop competencies, improve self-confidence, and learner satisfaction in a safe environment. Simulation is increasingly adopted globally as an alternative teaching strategy. Yet, data on the HFS experience of Filipino undergraduate nursing students is limited. This study describes the satisfaction, self-confidence, and perception of undergraduate nursing students on the use of HFS-based learning on critically-ill adult and pediatric patients requiring advanced life support (ALS). A quantitative, descriptive, correlational study was conducted using purposive sampling on all fourth-year BS Nursing students enrolled in Critical Care Nursing course in a state university. Data were collected through an online survey on demographic data, and the students' perceptions towards high-fidelity simulation-based learning (SBL) using three tools, namely: Simulation Design Scale, Educational Practices Questionnaire, and Student Satisfaction and Self-confidence in Learning. T-test and ANOVA were used to compare the means of the variables. Bivariate analysis (Pearson's product-moment correlation) was performed to find the relationship between variables. A total of 86 students participated in the survey. Overall, the students were highly satisfied with the simulation experience (4.46 out of 5.0, SD=0.47), and had high ratings of self-confidence in SBL (4.44 out of 5.0, SD=0.42). Overall satisfaction level was positively related to student's perception on simulation design (r=0.61, p<0.01) and educational practices (r=0.59, p<0.01). Similarly, the students' overall self-confidence with SBL was also positively correlated with their perceptions of the simulation design (r=0.32, p<0.01), and educational practices (r=0.34, p<0.01). Effective use of technology through HFS-based learning is useful in increasing satisfaction and self-confidence of Filipino undergraduate nursing students in caring for critically-ill patients needing ALS. Educators must highly consider all parameters of simulation design and educational practices in planning and implementing HFS-based learning to achieve meaningful learner experience.

A Combined Discrete Event Simulation and Factorial Design Experiment for the Scheduling Problem in a Hybrid Flow Shop

Production plants have always been confronted with the problem of scheduling, as this has a direct impact on production time and therefore on production costs. This is especially true in today's world, where it is necessary to produce a quality product at a low price and in a short time, while at the same time responding flexibly to customer demands. Due to the complexity and for economic reasons, testing different variants in a real production environment is insufficient and ineffective. For this reason, this paper proposes a new method that combines discrete event simulation and factorial design experiment to find the optimal schedule in hybrid flow shop. It was tested with the goal of achieving the minimum makespan. The results show that this method makes it possible to find improved solution very quickly. Compared to the original production schedule, the makespan could be reduced by 3 hours and 31 minutes which is reduction of 16.3%. The proposed methodology can be used in many discrete and process production plants.

Simulation and conceptual design of an aniline production process from catalytic hydrogenation of nitrobenzene in ChemCAD

Aniline is a very important compound in organic chemistry, mainly used to synthesize polyurethane and its precursors. In the present work, the simulation and conceptual design of an aniline production process through the catalytic hydrogenation route of nitrobenzene was carried out using ChemCADÒ simulator. The simulated aniline production process consisted of a fired heater, a tubular reactor, several heat exchangers, a phase separator, a decanter, as well as two distillation columns. By means of the simulation, the temperatures, pressures, mass flowrates and enthalpies of the main intermediate and final streams were known, as well as the main operating and design parameters of some equipment. About 1,743 kg/h of aniline with a purity of 99.78% are produced at the top stream of the second distillation column, while about 49,881 kg/h of hydrogen are obtained as a by-product in the phase separator. In this work a first-of-its-kind ChemCAD simulation model was obtained in this work, which can be utilized for further optimization studies and tasks involving the increment of aniline purity, yields and productivity.