High-fidelity Simulation Model Research Articles

Analysis of in-cylinder pressure oscillation and its effect on wall heat transfer

In-cylinder pressure oscillations in internal combustion engines have been associated with increased heat losses and damages to the engine components. The links between the acoustic waves and the increased heat transfer (and potentially ensuing engine damages) have not yet been well understood. In this study, a high-fidelity large eddy simulation model incorporating an auto-ignition model is used to simulate the combustion process and the associated pressure oscillation at various engine operating conditions. The study serves to develop a better understanding of the acoustic waves in a combustion chamber and their effect on wall heat transfer. First, a simplified model of the pressure oscillations is proposed and shown to accurately characterize the pressure in the combustion chamber. Second, the simplified pressure model and acoustic theory are leveraged to develop a model of the in-cylinder gas velocities. Finally, a heat transfer model is presented that takes into consideration the pressure/velocity oscillations and the inherent acoustic properties of the trapped gas. The increase in heat transfer is shown to primarily stem from an increased heat transfer coefficient due to the velocity oscillations of the trapped gas. The results are consistent with previously observed experimental measurements of the heat flux in the presence of pressure oscillations.

Data-Driven Models to Predict Hydrocarbon Production From Unconventional Reservoirs by Thermal Recovery

AbstractIn the numerical simulations of thermal recovery for unconventional resources, reservoir models involve complex multicomponent-multiphase flow in non-isothermal conditions, where spatial heterogeneity necessitates the huge number of discretized elements. Proxy modeling approaches have been applied to efficiently approximate solutions of reservoir simulations in such complex problems. In this study, we apply machine learning technologies to the thermal recovery of unconventional resources, for the efficient computation and prediction of hydrocarbon production. We develop data-driven models applying artificial neural network (ANN) to predict hydrocarbon productions under heterogeneous and unknown properties of unconventional reservoirs. We study two different thermal recovery methods—expanding solvent steam-assisted gravity drainage for bitumen and in-situ upgrading of oil shale. We obtain training datasets by running high-fidelity simulation models for these two problems. As training datasets of ANN models, diverse input and output data of phase and component productions are generated, by considering heterogeneity and uncertainty. In the bitumen reservoirs, diverse permeability anisotropies are considered as unknown properties. Similarly, in the oil shale reservoirs, diverse kerogen decomposition kinetics are considered. The performance of data-driven models is evaluated with respect to the position of the test dataset. When the test data is inside of the boundary of training datasets, the developed data-driven models based on ANN reliably predict the cumulative productions at the end of the recovery processes. However, when the test data is at the boundary of training datasets, physical insight plays a significant role to provide a reliable performance of data-driven models.

Effect of Implementing Simulation Education on Health Care Worker Comfort With Nasopharyngeal Swabbing for COVID-19.

To determine if rapid implementation of simulation training for the nasopharyngeal swab procedure can increase provider confidence regarding procedure competency. A simulation training exercise was designed as a departmental initiative to improve competency performing nasopharyngeal swabs during the COVID-19 pandemic. Sixty-one health care workers attended teaching sessions led by the Department of Otorhinolaryngology on proper nasopharyngeal swab technique. After a brief lecture, participants practiced their swab technique using a high-fidelity airway simulation model. Pre- and postintervention self-evaluations were measured via standardized clinical competency questionnaires on a 5-point Likert scale ranging from "No knowledge, unable to perform" up to "Highly knowledgeable and confident, independent." Forty-six participants in this study submitted pre- and postintervention self-assessments. Postintervention scores improved on average 1.41 points (95% CI, 1.10-1.73) out of 5 from a mean score of 3.13 to 4.54 (P < .0001). This reflects a large effect size with a Glass's delta value of 1.3. Lecture coupled with simulation-based teaching can significantly improve health care workers' confidence in performing nasopharyngeal swabs. Proper training for frontline workers performing swabs for COVID-19 is essential to improving testing accuracy and can be achieved in a simple and timely manner. To meet the testing needs of the growing pandemic, many health care workers who are unfamiliar with nasopharyngeal swabs have been asked to perform this test. Simulation-based teaching sessions may improve health care workers' confidence and help prevent false-negative results. This intervention is easily reproducible in any setting where frequent nasopharyngeal swab testing occurs. Prospective cohort study.

A Randomized Cross-Over Trial Focused on Clinical Breast Exam Skill Acquisition Using High Fidelity versus Low Fidelity Simulation Models in Rwanda

Breast cancer incidence is rising for women in low and middle income country (LMIC)s. Growing the health care workforce trained in clinical breast exam (CBE) is critical to mitigating breast cancer globally. We developed a CBE simulation training course and determined whether training on a low-fidelity (LF) simulation model results in similar skill acquisition as training on high-fidelity (HF) models in Rwanda. A single-center randomized educational crossover trial was implemented. A preintervention baseline exam (exam 1), followed by a lecture series (exam 2), and training sessions with assigned simulation models was implemented (exam 3)-participants then crossed over to their unassigned model (exam 4). The primary outcome of this study determined mean difference in CBE exam scores between HF and LF groups. Secondary outcomes identified any provider level traits and changes in overall scores. The study was implemented at the University Teaching Hospital, Kigali (CHUK) in Rwanda, Africa from July 2014 to March 2015 PARTICIPANTS: Medical students, residents in surgery, obstetrics and gynecology, and internal medicine residents participated in a 1-day CBE simulation training course. A total of 107 individuals were analyzed in each arm of the study. Mean difference in exam scores between HF and LF models in exam 1 to 4 was not significantly different (exam 1 0.08 standard error (SE) = 0.47, p = 0.42; exam 2 0.86, SE = 0.69, p = 0.16; exam 3 0.03, SE = 0.38, p = 0.66; exam 4 0.10 SE = 0.37, p = 0.29). Overall exam scores improved from pre- to post-intervention. Mean difference in exams scores were not significantly different between participants trained with HF versus LF models. LF models can be utilized as cost effective teaching tools for CBE skill acquisition, in resource poor areas.

Does Use of High-fidelity Simulation Improve Resident Physician Competency and Comfort Identifying and Managing Bradyarrhythmias?

Introduction: A workshop was designed to evaluate whether high-fidelity simulation with interactive case discussion could improve resident physician knowledge and comfort interpreting and managing bradyarrhythmias. Methods: All the residents completed a pre-test and then participated in a one-hour interactive presentation, which included practice interpreting rhythm strips and 12-lead electrocardiograms. Forty-four residents were assigned to the intervention group and completed 10 simulated cases using a mannequin, a real defibrillator/external pacemaker, a medication cart, and a simulated telemetry monitor displaying real-time electrocardiograms under the guidance of two instructors. Seventeen residents were assigned to the control group and completed the same 10 cases using interactive discussion with the same instructors but without the use of the high-fidelity simulation models. All residents underwent post-testing. Results: For the intervention group, the mean pre- and post-test knowledge scores were 13.93 and 17.28 (p=0.0001), and the mean pre- and post-test comfort scores were 2.92 and 4.24 (p=0.0001). For the control group, the mean pre- and post-test knowledge scores were 14.52 and 18.00 (p=0.005), and the mean pre- and post-test comfort scores were 2.97 and 4.35 (p=0.001). There were no statistically significant differences between pre-test and post-test knowledge and comfort scores for the two groups (p=0.633, p=0.421, p=0.177).Conclusion: Interactive workshops help improve resident knowledge and comfort with identifying and managing bradycardias. The use of high-fidelity simulation models may not be superior to a similar interactive learning experience without the use of high-fidelity simulation tools.

Simulations of airborne collisions between drones and an aircraft windshield

Drones are a considerable thread to the safe operation of transport aircraft with the wide application and development trend of drones. The airborne collision safety between the windshield of transport aircraft and the five light unmanned aircraft vehicles (UAVs) under various possible flight conditions is mainly studied in this paper. The collision simulation model of drone and aircraft windshield is established under PAM-CRASH software environment, which is used to simulate the dynamic response and damage of the windshield after the impact of drone and aircraft windshield under various conditions. The simulation results with that of collision test between whole-level drones and a full-scale aircraft with windshield is compared and analyzed to verify the validity of the simulation. The drone with similar bird mass is also selected to verify the appropriateness of the airworthiness rules of the windshield structure against bird impact to light UAV. The influencing parameters are important to the research results and are taken into a little consideration in the study. The research shows that the configuration, material, weight, speed and attitude of drones all have significant effects on the impact damage to the aircraft windshield, and a “parallel” attitude of a 1360 g drone which was proven to be a very severe gesture resulted in an unairworthy consequence at an impact velocity of 154.8 m/s. The windshield damage from a 1360 g drone strike is much heavier than that from a bird of a little big mass. It is expected that the high fidelity simulation model can be used to simulate all kinds of working conditions, reduce the test times, and save a lot of economic costs and provide credible technical support and basis for the airworthiness authorities to formulate precise and convincing regulatory regulations in future.

A Randomized Cross-Over Trial Focused on Breast Core Needle Biopsy Skill Acquisition and Safety Using High Fidelity Versus Low Fidelity Simulation Models in Rwanda

Breast cancer is the most common cancer diagnosed in low and middle-income countries. Growing the number of health care personnel trained in diagnostic procedures like breast core needle biopsy (BCNB) is critical. We developed a BCNB simulation-training course that evaluated skill acquisition, confidence, and safety, comparing low-cost low fidelity (LF) models to expensive high fidelity (HF) models. A single-center randomized education crossover trial was implemented. Participants were randomized to HF or LF groups. A preintervention baseline exam followed by lectures and training sessions with a HF or LF model was implemented. A postintervention simulation exam was conducted, and participants crossed over to the other simulation model. The study was implemented at the University Teaching Hospital, Kigali (CHUK) in Rwanda, Africa from October 2014 to March 2015. Residents training in surgery or obstetrics and gynecology participated in a 1-day BCNB training course. A total of 36 residents were analyzed, 19 in the HF arm and 17 in the LF arm. Mean difference in exam scores for HF and LF groups in the baseline exam (exam 1) (0.067, p = 0.94, standard error [SE] of 1.57) postintervention exam (exam 2) (1.85, SE 1.46, p = 0.33), and the crossover exam (exam 3) (4.39, SE = 1.90, p = 0.11) were not significantly different between HF and LF. Overall exam scores improved from pre- to postintervention. Our results indicate that mean difference in exams scores were not significantly different between residents trained with HF versus LF models. In resources poor areas-LF models can be utilized as effective teaching tools for skill acquisition for diagnostic surgical procedures.

Surgical cricothyroidostomy. Analysis and comparison between teaching and validation models of simulator models.

to compare the acquisition and retention of knowledge about surgical cricothyroidostomy by the rapid four-step technique (RFST), when taught by expository lecture, low fidelity and high-fidelity simulation models. ninety medical students at UFPR in the first years of training were randomized assigned into 3 groups, submitted to different teaching methods: 1) expository lectures, 2) low-fidelity simulator model, developed by the research team or 3) high-fidelity simulator model (commercial). The procedure chosen was surgical cricothyroidostomy using the RFST. Soon after lectures, the groups were submitted to a multiple-choice test with 20 questions (P1). Four months later, they underwent another test (P2) with similar content. Analysis of Variance was used to compare the grades of each group in P1 with their grades in P2, and the grades of the 3 groups 2 by 2 in P1 and P2. A multiple comparisons test (post-hoc) was used to check differences within each factor (test and group). Statistical significance was considered when p<0.05. Statistical analysis was performed in the statistical software R version 3.6.1. each group was composed of 30 medical students, without demographic differences between them. The mean scores of the groups of the expositive lecture, of the simulator of low fidelity model and of high-fidelity simulator model in P1 were, respectively, 75.00, 76.09, and 68.79, (p<0.05). In P2 the grades were 69.84, 75.32, 69.46, respectively, (p>0.05). the simulation of low fidelity model was more effective in learning and knowledge retention, being feasible for RFST cricothyroidostomy training in inexperienced students.

Controlling melt pool shape, microstructure and residual stress in additively manufactured metals using modified laser beam profiles

Laser powder bed fusion has proven to be an effective additive manufacturing technology for the manufacture of complex metal components. However, the local thermal history associated with Gaussian beam, raster scan processes produces heterogeneous and spatially non-uniform microstructures that differ from those produced from conventional manufacturing and often lack optimized mechanical properties. Steep thermal gradients and high cooling rates produce large thermal strains driving residual stress fields that can negatively affect the dimensional accuracy of the as-built component. Here, we present experimental and simulation methods for controlling microstructure and residual stress through tailored laser beam profiles. Elliptical and Bessel beam profiles are shown to produce more equiaxed microstructures as compared to those of Gaussian beams, while distributed diode-based illumination profiles allow for reduced residual stresses. These experimental results are supported by high-fidelity powder-scale simulation models coupled to the cellular automata and thermomechanical models that account for macroscale residual stress.

Screening and optimization of polymer flooding projects using artificial-neural-network (ANN) based proxies

Polymer flooding is one of the most broadly implemented chemical EOR processes due to its low injection cost and successes in oil production increments. This work develops artificial-neural-network based proxies by utilizing synthetic production histories generated from a high-fidelity numerical simulation model. Injection-pattern-based reservoir models are structured to establish the knowledgebase to train the proxies. A forward and an inverse-looking ANN models are structured in this study. The forward-looking expert system are employed as a forecasting and screening tool that is capable to predict time-based project responses. And the inverse-looking ANN predicts the project design schemes that fulfill the expected oil recoveries. The proxies are generalized considering reservoir rock and fluid properties and project design parameters. In this paper, we present results of extensive blind testing applications to confirm the validates of the proxy models. Afterwards, various applications of the expert systems are discussed. A project screening protocol that couples the expert system and particle swarm optimization (PSO) methodology is presented to maximize the polymer injection projects' net present value (NPV). Moreover, we propose a robust computational workflow that coupled utilize the inverse and forward-looking proxies to find various polymer injection schemes to fulfill the expected oil production profile, which effectively addresses the issue associated with the existence of non-unique solutions in the inverse design problems. The expert ANN systems and the associated project design workflows provide versatile approaches for the field engineers to obtain quick techno-economical assessments of polymer injection projects.

2292 How to Build a High Fidelity Model for Teaching Perineal Laceration Repair

Video Objective Train the trainer: Hands on creation in less than 10 minutes an anatomically accurate simulation model for repair of third and fourth degree obstetric lacerations Setting 1. Create in less than 10 minutes an anatomically accurate high fidelity simulation model using beef tongue and beef intestine and craft supplies in order to teach the repair of third and fourth degree obstetric lacerations to obstetrics and gynecology residents. 2. Understand the anatomy of the perineum and anal sphincter as illustrated by this simulation model. 3. In the setting of insufficient training in ob/gyn residencies regarding 3rd and 4th degree obstetric laceration repairs and assuring competence in this area by the time residents graduate, simulation models have become increasingly relevant. This video aims to provide residency program directors and educators with a detailed step-by-step hands-on creation in less than 10 minutes of an anatomically correct high fidelity simulation model using beef tongue and beef intestine along with easily obtained craft supplies which can be used for teaching OB/GYN residents third and fourth degree obstetric laceration repairs Interventions n/a Conclusion The video provides an easily made (within 10 minutes) anatomically accurate high fidelity model utilizing beef tongue and beef intestine along with easily obtained craft supplies that can be used to teach the correct techniques for third and fourth degree repairs for obstetric lacerations.

High-Fidelity Microsurgical Simulation: The Thiel Cadaveric Nerve Model and Evaluation Instrument.

With surgical education moving from a time-based to a competency-based model, developing high-fidelity simulation models has become a priority. The Thiel cadaveric model has previously been used for a number of medical and surgical simulations, including microvascular simulation. We aim to investigate the use of the Thiel model in peripheral nerve simulation and validate a novel evaluation instrument. Sixteen residents ranging from postgraduate years 1 to 6 participated in the study. Their nerve coaptations using Thiel cadaveric nerves were video recorded and evaluated by 5 fellowship-trained microsurgeons using the Micro-Neurorrhaphy Evaluation Scale (MNES). The intraclass correlation among the 5 evaluators was 0.75, revealing excellent interrater reliability. The Cronbach α was .77, underlining the internal consistency of the test items. Bivariate analysis revealed a significant association between the MNES scores and the participants' self-declared level of experience. This correlation was confirmed by mixed modeling. Our results validate the MNES and underscore the utility of the Thiel nerve tissue for peripheral nerve surgical simulation.

Mathematical Modelling Of Structures Using Model Order Reduction Technique

Today’s world is a world of simulation. Now a days, every product is first designed in virtual domain and then tested for actual implementation. To be able to perform such accurate virtual domain analysis, an accurate mathematical model is needed to be designed in first place. Specifically, in the field of dynamic analysis, so as to continuously monitor the system, the requirement a high-fidelity simulation models in all industries is rising rapidly and this has now become an important part of modern simulation strategies. FEA simulation software’s nowadays could provide very accurate results but they cannot be used directly for dynamic simulations where the environment is continuously changing (input forces, random vibrations etc.). Therefore, this paper deals with design of a mathematical model of a beam to overcome the above stated issue. The technique so used is Model Order Reduction. This method develops an efficient reduced model by reducing the degrees of freedom and also preserving a characteristic behavior of the system. The methodology deals with extracting the mass, and stiffness matrices from FEA simulation software, reducing their size (order), building a second order system using reduced sizes of mass and stiffness, analyzing mode shapes vectors and nodes for input force applications, and generating a state space model of the system.

Validation and educational impact study of the NANEP high-fidelity simulation model for open preperitoneal mesh repair of umbilical hernia.

The aim of the study was to develop, validate and analyze the educational impact of a high-fidelity simulation model for open preperitoneal mesh repair of an umbilical hernia. The number of surgical simulators available for training residents is limited. Primary for ethical reasons and secondary for the emerging pay-per-quality policies, practicing-on simulators rather than patients is considered gold standard. Validated full-procedural surgical models will become more and more important in training residents. Such models may assure that evidence-based standards regarding technical aspects of the procedures become integral part of the curriculum. Furthermore, they can be employed as a quality control of residents' skills (Fonseca et al. in J Surg Educ 70:129-137, 2013). In a repeated measures design, medical students, residents in their last year of training and attending surgeons performed an open preperitoneal mesh repair on the NANEP model [NANEP stands for the German acronym Nabelhernien-Netzimplatation-Präperitonal (English: Umbilical hernia mesh implantation preperitoneal)]. Subjects were categorized as "Beginners" (internship students) or "Experts" (residents and surgeons). Content validity was analyzed by criteria of subject-matter-experts. Blinded raters assessed surgical skills by means of the Competency Assessment Tool (CAT) using the online platform "CATLIVE". Differential validity was measured by group differences. Proficiency gain was analyzed by monitoring the learning curve (Gallagher et al. in Ann Surg 241:364-372, 2005). Post-operative examination of the simulators shed light on criterion validity. The NANEP model-proofed content and construct-valid significant Bonferroni-corrected differences were found between beginners and experts (p < 0.05). Beginners showed a significant learning increase from the first to the second surgery (p < 0.05). Post-operative examination data confirmed criterion validity. The NANEP model is an inexpensive, simple and efficient simulation model. It has highly realistic features, it has been shown to be of high-fidelity, full-procedural and benchtop-model. The NANEP model meets the main needs of surgical educational courses at the beginning of residency.

A Data-Driven Approach for Process Optimization of Metallic Additive Manufacturing Under Uncertainty

The presence of various uncertainty sources in metal-based additive manufacturing (AM) process prevents producing AM products with consistently high quality. Using electron beam melting (EBM) of Ti-6Al-4V as an example, this paper presents a data-driven framework for process parameters optimization using physics-informed computer simulation models. The goal is to identify a robust manufacturing condition that allows us to constantly obtain equiaxed materials microstructures under uncertainty. To overcome the computational challenge in the robust design optimization under uncertainty, a two-level data-driven surrogate model is constructed based on the simulation data of a validated high-fidelity multiphysics AM simulation model. The robust design result, indicating a combination of low preheating temperature, low beam power, and intermediate scanning speed, was acquired enabling the repetitive production of equiaxed structure products as demonstrated by physics-based simulations. Global sensitivity analysis at the optimal design point indicates that among the studied six noise factors, specific heat capacity and grain growth activation energy have the largest impact on the microstructure variation. Through this exemplar process optimization, the current study also demonstrates the promising potential of the presented approach in facilitating other complicate AM process optimizations, such as robust designs in terms of porosity control or direct mechanical property control.

A High-Fidelity Surgical Model and Perfusion Simulator Used to Demonstrate ECMO Cannulation, Initiation, and Stabilization

Our high-fidelity simulation model provides a realistic example for health-care professionals to experience cannulation, initiation, and hemodynamic stabilization during extracorporeal membrane oxygenation (ECMO) therapy. This educational experience brings a variety of critical care specialties together, in a controlled simulation setting, to develop, master, and maintain clinical skills. This may include perfusionists, ECMO specialists, surgical technicians, registered nurses, physicians, and students. The simulation component includes a unique vascular access pad that is attached to either a static fluid model or to the Califia perfusion simulator system (Biomed Simulation, Inc., San Diego, CA). This collective high-fidelity simulation model can be surgically cannulated via a cutdown technique using an appropriately sized cannula and connected to an in situ ECMO circuit. This article explains the educational strategy, how the surgical pad is made, and the simulator connections so that any hospital can re-create this experience.

An Explicit Nonlinear Model Predictive ABS Controller for Electro-Hydraulic Braking Systems

This paper addresses the development and Hardware-in-the-Loop (HiL) testing of an explicit nonlinear model predictive controller (eNMPC) for an antilock braking system (ABS) for passenger cars, actuated using an electro-hydraulic braking unit. The control structure includes a compensation strategy to guard against the performance degradation due to actuation dead times, identified by experimental tests. The eNMPC is run on an automotive rapid control prototyping unit, which shows its real-time capability with comfortable margin. A validated high-fidelity vehicle simulation model is used for the assessment of the ABS on a HiL rig equipped with the braking system hardware. The eNMPC is tested in seven emergency braking scenarios, and its performance is benchmarked against a proportional-integral-derivative (PID) controller. The eNMPC results show: 1) the control system robustness with respect to the variations in tire-road friction condition and initial vehicle speed; and 2) consistent and significant improvement of the stopping distance and wheel slip reference tracking, with respect to the vehicle with the PID ABS.

Computationally efficient MPC for path following of underactuated marine vessels using projection neural network

A practical model predictive control (MPC) for path following of underactuated marine vessels, which is a representative marine application, is presented in this paper. Taking advantage of the capability of dealing with multivariable system and input saturation, the MPC method is used to transform the underactuated control problem into the optimization problem with incorporation of input (rudder) constraints. Considering the implementation obstacle of solving optimization problem formulated by the MPC method efficiently, the projection neural network, which is known as parallel computational capability, is employed here to improve the computational efficiency. The full information of ship motion is normally difficult to obtain directly due to the lack of enough measurements; therefore, the state observer is also included. A simple linear model represented the main dynamics of path following of underactuated marine vessels is conceived as predictive (control design) model; meanwhile, in order to demonstrate the effectiveness of proposed control design, all the comparative studies are conducted on a nonlinear high-fidelity simulation model. The simulation results validate that the proposed control design is effective and efficient.

Experimental Verification of a Coordinated Path-Following Strategy for Underactuated Marine Vehicles.

This work presents the results of an experimental verification of a coordinated path following strategy for underactuated marine vehicles. The coordinated path following strategy is presented, and is then experimentally verified using three autonomous underwater vehicles. The vehicles are required to coordinate their motion along spatially separated straight-line paths to obtain a desired formation. The vehicles are steered to the paths using an integral line-of-sight guidance approach that allows the vehicles to reject constant ocean currents. Simultaneously, the coordination is achieved by adjusting the velocity based on the along-path distance. First, simulation results are presented, which serve as benchmarks for the experimental results. Furthermore, the simulations are used to show the effect of changing different parameters. The simulation results are performed using high-fidelity hardware simulation models. The results obtained from experiments in the harbor of Porto are then presented and compared with the results of the simulation.

Fault blocking converters for HVDC transmission: a transient behaviour comparison

A thorough comparison of the transient behaviours of two state-of-the-art converters suitable for HVDC transmission is presented. The alternate arm and mixed-cell modular multilevel converter topologies both have DC fault blocking capability and are selected for the comparison. Converter performance is evaluated and compared under various transient conditions including charging sequence, unbalanced operation, and DC fault recovery. The study is conducted using high-fidelity converter simulation models, integrating detailed controllers that reflect real-scale projects. The main findings of the study assist in the selection of the most suitable converter, given specific performance specifications such as capacitor voltage ripple, cell capacitor requirements, and response during transient operation.