Simulation Training Research Articles

Synergistic cotreatment of cooling tower blowdown and produced waters: Techno-economic, sustainability, and optimization systems analyses

A blowdown and produced water cotreatment train design was preliminarily simulated to explore water-energy nexus synergy. This process model was able to provide results concerning water compositions, chemical demand, and energy intensity. The computational expense associated with this simulation made it intractable to use within optimization algorithms for further informative, comprehensive systems analyses. This work details the efforts of developing a framework suitable for the optimization of computationally demanding wastewater treatment train simulations, specifically demonstrated for the cotreatment train’s process, economic, and sustainability models. The unique challenges of the cotreatment train model motivated a modified surrogate optimization methodology to be developed. Using this framework, worst and best case economic scenarios were optimized to minimize the levelized cost of water (LCOW) employed in a reduced-order model-based simulation. Applying the optimal designs obtained from the surrogate optimization into the original comprehensive simulation resulted in an expected range of LCOW from $2.01 to $4.43m-3. Other established techno-economic and sustainability indicators further inform on process implications. The process was compared to current management practices of blowdown water treatment and produced water injection to discuss the advantages and disadvantages of the proposed cotreatment train designed for water reuse. The cotreatment process was estimated to have lower levelized treatment costs but require more chemicals and energy to manage a higher salinity wastewater than pure blowdown water alone. If sustainable management goals motivate produced water remediation, the cotreatment process can be beneficial for the broader scope of water management.

Immersive Simulations in Surgical Training: Analyzing the Interplay Between Virtual and Real-World Environments

Background The adoption of immersive simulations in surgical education marks a nuanced shift towards bridging virtual and real-world experiences. Introduced by Johan Huizinga and further explored by Edward Castronova, the “Magic Circle” concept serves as a metaphorical boundary within which the standard constraints of reality are temporarily lifted, allowing for the emergence of unique learning and interaction dynamics. This framework, while new to the field of surgical training, presents a theoretical potential for improving educational outcomes by merging simulated environments with actual surgical operations. Aim This study aims to critically assess the introduction of immersive simulations in surgical education, with a particular focus on the interplay between virtual scenarios and their real-world counterparts. It seeks to evaluate the potential of the Magic Circle as a novel conceptual framework for enhancing the educational journey within surgical disciplines. Method Through qualitative analysis, this research explores the application of immersive simulation technologies in surgical fields. It examines the Magic Circle concept's influence on these educational paradigms, especially regarding its effect on the efficiency of learning, the transferability of skills, and levels of learner engagement. Results This paper proposes that embedding immersive simulations within the Magic Circle framework could lead to improved understanding of surgical procedures and heightened acquisition of skills. This conceptualization suggests a promising avenue for enriching the educational matrix in surgical training, bridging theoretical knowledge with practical application through a novel lens. Recommendation The study advises a judicious integration of immersive simulation technologies within surgical training programs, guided by the principles of the Magic Circle. It calls for further empirical research to validate and refine this conceptual approach, with an emphasis on maximizing the utility of immersive learning tools, enhancing the effectiveness of skill transfer, and ensuring an equitable and effective educational experience for all surgical trainees.

Empowering medical students: bridging gaps with high-fidelity simulations; a mixed-methods study on self-efficacy

BackgroundHigh-fidelity simulations play a crucial role in preparing for high-mortality events like cardiopulmonary arrest, emphasizing the need for rapid and accurate intervention. Proficiency in cardiopulmonary resuscitation(CPR) requires a strong self-efficacy(SE); training for both is crucial. This study assesses the impact of Advanced Life Support(ALS) simulation on SE changes in final-year medical students.MethodsThis mixed-methods prospective simulation study involved medical students in emergency medicine internships, examining self-efficacy perceptions regarding ALS technical skills(ALS-SEP). A comparison was made between students who underwent scenario-based ALS simulation training and those who did not. Competencies in chest compression skills were assessed, and the concordance between ALS-SEP scores and observed CPR performances were evaluated. Focus group interviews were conducted and analyzed using content analysis techniques.ResultsThe study involved 80 students, with 53 in the experimental group(EG) and 27 in the control group(CG). The EG, underwent simulation training, showed a significantly higher ALS-SEP change than the CG(p < 0.05). However, there was low concordance between pre-simulation SEP and actual performance. Compression skills success rates were inadequate. Qualitative analysis revealed main themes as"learning“(32.6%), “self-efficacy“(29%), “simulation method“(21.3%), and “development“(16.5%).DiscussionPost-simulation, students reported improved SEP and increased readiness for future interventions. The findings and qualitative statements support the effectiveness of simulation practices in bridging the gap between SEP and performance. Utilizing simulation-based ALS training enhances learners’ belief in their capabilities, raises awareness of their competencies, and encourages reflective thinking. Given the importance of high SEP for ALS, simulation trainings correlating self-efficacy perception and performance may significantly reduce potential medical errors stemming from a disparity between perceived capability and actual performance.

National Addiction Workshop: A Virtual Adaptation to Support Competency Development in Opioid Use Disorder Management.

Accessible, manualized, skill-based training ready for wide dissemination is needed to prepare healthcare staff to meet the needs of people impacted by the opioid epidemic. A 2-day workshop and simulation training was designed by an interprofessional substance use disorder (SUD) specialty care team, adapted to a virtual platform, manualized, and offered to healthcare staff and trainees from a large healthcare system. The workshop was offered 6 times over the course of 10 months with a total of 177 participants from across the United States enrolled in the training. Interactive experiential learning strategies including games designed to test knowledge, small-group case discussions, video demonstrations of skills, patient panels, and 3 simulations of a patient with chronic pain who developed opioid use disorder in the context of long-term opioid therapy were utilized in efforts to build skills and confidence managing SUDs in primary care and general mental health settings. Of those who completed the post-workshop survey, most found both content and training structure useful, particularly content related to medication management, stigma, and collaborative care. In addition, overall confidence scores in assessing, diagnosing, and treating SUD increased. Skill building exercises, such as interprofessional team simulations, were highlighted as most beneficial. The workshop received national attention leading to a partnership with the healthcare system's simulation center for wider dissemination. Expanding access to SUD treatment requires training healthcare staff to effectively change attitudes, increase knowledge, and improve key skills. This 2-day interprofessional workshop was well-received by participants who reported high acceptability and satisfaction scores and demonstrated improved confidence in the management of SUDs. This type of manualized, collaborative, skill-based learning experience can foster staff preparedness and willingness to conceptualize SUD as a chronic condition amenable to treatment in different healthcare settings.

Evaluation of a Three-Dimensional Printed Interventional Simulator for Cardiac Ablation Therapy Training

Cardiac ablation (CA) is an interventional electrophysiological procedure used to disrupt arrhythmic substrates in the myocardium by inducing localized scarring. Current CA training relies on the master–apprentice model. In different fields of medicine including CA, virtual and physical simulators have proven to enhance, and even outperform, conventional training modalities while providing a risk-free learning environment. Despite the benefits, high costs and operational difficulties limit the widespread use of interventional simulators. Our previous research introduced a low-cost CA simulator using a 3D-printed biatrial cardiac model, successfully recording ten ablation lesions on the phantom myocardium. In this work, we present and evaluate an enhanced version: compared to the previous version, the cardiac phantom’s electrical behavior and ablation settings were optimized to produce consistent lesions, while 3D-printed components improved the haptic and radiographic properties of the simulator. Seven cardiologists compared the experimental simulator’s performance to the leading commercial system from Heartroid in a 24-question survey on a 5-point Likert scale. The four following areas of fidelity were considered: catheter entry, anatomical correctness, radiographic appearance, and mapping and ablation. The experimental simulator significantly outperformed the commercial system (p &lt; 0.01), particularly in radiographic appearance (p &lt; 0.01). The results show the potential for the experimental simulator in routine CA training.

Examining flight time, cognitive reflection, workload, stress and metacognition on decision making performance for pilots during flight simulation

Despite technological advancements, human decision errors still contribute to civil aviation accidents. This study investigated whether flight time, cognitive reflection, task-load, metacognition, and perceived stress predicted decision-making (DM) performance during two in-flight training simulations with 104 commercial pilots at Bogota International Airport. Hierarchical regression analysis revealed that the predictors accounted for 56% of the variance. Cognitive reflection, flight time and performance task load emerged as significant positive predictors. Cognitive reflection significantly moderated the relationship between flight time and DM performance, with pilots scoring lower on cognitive reflection showing improved DM with increased flight time, while controlling for performance task load. The study did not find significant relationships between stress metacognition and DM performance. The study emphasises the significance of advanced training methods in improving pilots’ DM, especially for those with low cognitive reflection. Future research should expand to multiple airlines, address gender balance, and incorporate direct measures of metacognitive monitoring.

Assessing the impact of self-e-learning, classroom teaching, and simulation training on learning of COLREG: a survey-based analysis among maritime students at the Universiti Malaysia Terengganu

ABSTRACT Understanding the International Regulations for Preventing Collisions at Sea (COLREG) is crucial for maritime safety, yet maritime students often face challenges in mastering these regulations. This study investigates the effectiveness of different learning methods – self-e-learning, classroom instruction, and simulation training – on COLREG comprehension among maritime students at Universiti Malaysia Terengganu (UMT). The primary objective is to assess how these learning methods influence students’ mastery of COLREG. A mixed-method approach was employed, utilising a structured questionnaire for quantitative data collection and in-depth interviews for qualitative insights. Data were analyzed using Smart PLS 4.0 to explore the relationships between learning methods and COLREG knowledge. The findings of the study indicate that self-e-learning and classroom teaching significantly enhance students’ understanding of COLREG, while the impact of simulation training was less effective, necessitating a review of current simulation programs. The study recommends revising the curriculum to balance these learning methods, improve e-learning resources, and critically evaluate simulation training to better prepare students for maritime careers and enhance overall maritime safety.

Deep neural helmholtz operators for 3D elastic wave propagation and inversion

Summary Numerical simulations of seismic wave propagation in heterogeneous 3D media are central to investigating subsurface structures and understanding earthquake processes, yet are computationally expensive for large problems. This is particularly problematic for full waveform inversion, which typically involves numerous runs of the forward process. In machine learning there has been considerable recent work in the area of operator learning, with a new class of models called neural operators allowing for data-driven solutions to partial differential equations. Recent works in seismology have shown that when neural operators are adequately trained, they can significantly shorten the compute time for wave propagation. However, the memory required for the 3D time domain equations may be prohibitive. In this study, we show that these limitations can be overcome by solving the wave equations in the frequency domain, also known as the Helmholtz equations, since the solutions for a set of frequencies can be determined in parallel. The 3D Helmholtz neural operator is 40 times more memory-efficient than an equivalent time-domain version. We employ a Helmholtz neural operator for 2D and 3D elastic wave modeling, achieving two orders of magnitude acceleration compared to a baseline spectral element method. The neural operator accurately generalizes to variable velocity structures and can be evaluated on denser input meshes than used in the training simulations. We also show that when solving for wavefields strictly on the surface, the accuracy can be significantly improved via a graph neural operator layer. In leveraging automatic differentiation, the proposed method can serve as an alternative to the adjoint-state approach for 3D full-waveform inversion, reducing the computation time by a factor of 350.

Ecological and Cost Advantage from the Implementation of Flight Simulation Training Devices for Pilot Training

The paper discusses a case study of obtaining an airline pilot license in integrated training—the so-called “from zero to Airline Transport Pilot License”. The environmental implications of simulator-based training were examined across multiple dimensions. Key areas of research include the reduction of harmful exhaust gases pollution associated with traditional flight training activities. Based on our analysis, it can be stated that increasing the use of Flight Simulation Training Devices in pilot training should be significant consideration. This approach brings many benefits, especially ecological ones. Changing the training program and increasing the use of flight simulators can result in a reduction of CO2 emissions by up to 70%. Based on country specific electricity factors, CO2 emissions during flight training in each EU country were calculated. Using Levelized Cost of Electricity average value to calculate training costs in EU countries depends on the mix of energy sources (wind, photovoltaics, carbon and gas). The findings highlight the significant ecological advantages of simulator-based training methods in mitigating the environmental footprint of aviation operations. By seeking to minimize environmental disruption and increase training efficiency, the adoption of simulators is a sustainable approach to pilot training that is consistent with global efforts to mitigate climate change and protect natural ecosystems.

Improvement of the Resuscitation Environment with the Modified Toyota Kaizen Approach Via In Situ Anaesthesia Simulation Training.

Improvement of the Resuscitation Environment with the Modified Toyota Kaizen Approach Via In Situ Anaesthesia Simulation Training.

Retraction Note: 3D motion trajectory prediction based on optical image remote sensing data in sports training simulation

Retraction Note: 3D motion trajectory prediction based on optical image remote sensing data in sports training simulation

Training healthcare professionals in assessment of health needs in older adults living at home: a scoping review

BackgroundInterprofessional assessment and management of health needs for older adults living at home can help prioritize community service resources and enhance health, yet there is a shortage of professionals with the necessary competencies. Therefore, support and training for healthcare professionals in community settings to assess older adults’ health with the aim of for health promotion are needed.AimTo identify and provide an overview of published papers describing approaches for training healthcare professionals in assessing physical, mental, and social health needs in older adults living at home.MethodA systematic literature search of the Cinahl, Medline, Academic Search Ultimate, Scopus, Embase, and British Nursing Index databases was performed. We considered studies focusing on the training of healthcare professionals in assessing a single or multiple health needs of older adults aged 65 and above living at home. We considered studies published between 1990 – and March 2024. The review evaluated qualitative, quantitative, and mixed methods studies published in English-language peer-reviewed academic journals. A quality appraisal was conducted via the Mixed Methods Appraisal Tool (MMAT).ResultsTwenty-three studies focused on training healthcare professionals to assess health needs and plan care for older adults living at home were included. The majority of the included studies combined teacher-driven pedagogical approaches consisting of educational sessions, written materials or e-learning, and more participant-engaging pedagogical approaches such as knowledge exchange or various forms of interactive learning. Healthcare professionals were trained to detect and manage single and multiple health needs, and some studies additionally incorporated interprofessional collaboration. Healthcare professionals were satisfied with the training content and it increased their confidence and competencies in health needs assessment and care planning for older adults. Moreover, some studies have reported that training interventions foster the implementation of new and effective ways of working and lead to positive outcomes for older adults.ConclusionHealthcare professionals were satisfied with a combination of participant-engaging and teacher-driven pedagogical approaches used to train them in assessing health needs and planning care for older adults living at home. Such training can lead to enhanced assessment skills and facilitate improvements in practice and health promotion for older adults. Future research is recommended on interprofessional simulation training for conducting structured and comprehensive health needs assessments of older adults living at home, as well as on the implementation of such assessments and health-promoting interventions.

A Low-Cost, Low-Tech Virtual Mass Casualty Training Simulation for Undergraduate Medical Education.

Mass casualty incident (MCI) training effectively increases trainees' knowledge and confidence when implemented in a live, in-person setting. In-person MCI training is resource-intensive, but virtual MCI training models are an alternative with similar effectiveness at a lesser cost. However, most of these validated virtual options are based on high-tech virtual reality (VR) programs. We designed and implemented a low-tech, low-cost virtual MCI training model for third-year medical students, using Google JamboardTM (Google, Mountain View, CA) and ZoomTM(Zoom Video Communications, Inc., San Jose, CA) as the primary technological platforms. Learners were instructed on the adult simple triage and rapid treatment (START) and the pediatric JumpSTART triage algorithms over ZoomTM. In small groups, students used a gameboard on Google JamboardTM to simulate a scene at an MCI where they were tasked with triaging 25 patients in 30 minutes, followed by a debriefing session. Students were surveyed on their perceived understanding of the triage algorithms and confidence before and after the event using a 5-point Likert scale (poor, fair, good, very good, and excellent). Pre- and post-event scores were compared using paired, two-sample, and two-tailed t-tests. We considered a p value of <0.01 significant to correct for multiplicity using the Bonferroni method. Learners reported an increased understanding of the triage algorithms (adult and pediatric), scene setup, andunderstanding of emergency medical servicetraining/transportation, as well as increased confidence in participating in an MCI (all p < 0.001). Virtual MCI training can be used as an alternative or supplement to in-person MCI training. Low-tech virtual MCI training models can increase the accessibility of these valuable training activities without sacrificing the quality of learning. Areas for further investigation include low-tech virtual MCI training models' ability to effectively recreate situational and environmental distractions and other challenges better simulated by in-person and high-tech VR training events.

Application of graph neural networks to predict explosion-induced transient flow

We illustrate an application of graph neural networks (GNNs) to predict the pressure, temperature and velocity fields induced by a sudden explosion. The aim of the work is to enable accurate simulation of explosion events in large and geometrically complex domains. Such simulations are currently out of the reach of existing CFD solvers, which represents an opportunity to apply machine learning. The training dataset is obtained from the results of URANS analyses in OpenFOAM. We simulate the transient flow following impulsive events in air in atmospheric conditions. The time history of the fields of pressure, temperature and velocity obtained from a set of such simulations is then recorded to serve as a training database. In the training simulations we model a cubic volume of air enclosed within rigid walls, which also encompass rigid obstacles of random shape, position and orientation. A subset of the cubic volume is initialized to have a higher pressure than the rest of the domain. The ensuing shock initiates the propagation of pressure waves and their reflection and diffraction at the obstacles and walls. A recently proposed GNN framework is extended and adapted to this problem. During the training, the model learns the evolution of thermodynamic quantities in time and space, as well as the effect of the boundary conditions. After training, the model can quickly compute such evolution for unseen geometries and arbitrary initial and boundary conditions, exhibiting good generalization capabilities for domains up to 125 times larger than those used in the training simulations.

Exploring ambulance clinicians’ clinical reasoning when training mass casualty incidents using virtual reality: a qualitative study

BackgroundHow ambulance clinicians (ACs) handle a mass casualty incident (MCI) is essential for the suffered, but the training and learning for the ACs are sparse and they don’t have the possibility to learn without realistic simulation training. In addition, it is unclear what type of dilemmas ACs process in their clinical reasoning during an MCI. With virtual reality (VR) simulation, the ACs clinical reasoning can be explored in a systematic way. Therefore, the objective was to explore ambulance clinicians’ clinical reasoning when simulating a mass casualty incident using virtual reality.MethodsThis study was conducted as an explorative interview study design using chart- stimulated recall technique for data collection. A qualitative content analysis was done, using the clinical reasoning cycle as a deductive matrix. A high-fidelity VR simulation with MCI scenarios was used and participants eligible for inclusion were 11 senior ACs.Results/conclusionAll phases of the clinical reasoning cycle were found to be reflected upon by the participants during the interviews, however with a varying richness of analytic reflectivity. Non-analytic reasoning predominated when work tasks followed specific clinical guidelines, but analytical reasoning appeared when the guidelines were unclear or non-existent. Using VR simulation led to training and reflection on action in a safe and systematic way and increased self-awareness amongst the ACs regarding their preparedness for MCIs. This study increases knowledge both regarding ACs clinical reasoning in MCIs, and insights regarding the use of VR for simulation training.

New training simulator for lumbar puncture base on magnetorheological

In response to the difficulties in accurately reproducing the resistance drop generated by puncturing key tissue layers with a needle and the poor experience in existing simulators, based on the continuous controllability and rapid response of magnetorheological fluid under the influence of a magnetic field, this paper proposes a lumbar puncture training simulator(LPTS) that can accurately simulate the puncture feedback force within tissues such as the skin, subcutaneous fat, and supraspinous ligament throughout the entire process. By using a dual rod structure and reasonably arranging the damping channel gap, the influence of mechanical friction and zero-field damping force on the feedback force during tissue progression is minimized. This paper introduces the acquisition and modeling analysis of raw data, and based on this, the design, simulation, and mechanical testing of the simulator are carried out. Finally, a performance testing platform for the simulator is established to evaluate its tracking performance of the expected puncture strength and the reproducibility of the puncture sensation. The results show that the experimental puncture strength deviates from the expected puncture strength by 0.35 N to 0.61 N in the crucial steps of breaking through the supraspinous ligament, interspinous ligament, ligamentum flavum, and dura mater, with a relative error below 10 %.

Learner evaluation of an immersive virtual reality mass casualty incident simulator for triage training

BackgroundTo minimize loss of life, modern mass casualty response requires swift identification, efficient triage categorization, and rapid hemorrhage control. Current training methods remain suboptimal. Our objective was to train first responders to triage a mass casualty incident using Virtual Reality (VR) simulation and obtain their impressions of the training’s quality and effectiveness.We trained subjects in a triage protocol called Sort, Assess, Lifesaving interventions, and Treatment and/or Transport (SALT) Triage then had them respond to a terrorist bombing of a subway station using a fully immersive virtual reality simulation. We gathered learner reactions to their virtual reality experience and post-encounter debriefing with a custom electronic survey. The survey was designed to gather information about participants’ demographics and prior experience, including roles, triage training, and virtual reality experience. We then asked them to evaluate the training and encounter and the system’s potential for training others.ResultsWe received 375 completed evaluation surveys from subjects who experienced the virtual reality encounter. Subjects were primarily paramedics, but also included medical learners as well as other emergency medical service (EMS) professionals. Most participants (95%) recommended the experience for other first responders and rated the simulation (95%) and virtual patients (91%) as realistic. Ninety-four percent (94%) of participants rated the virtual reality simulator as “excellent” or “good.” We observed some differences between emergency medical service and medical professionals regarding their prior experience with disaster response training and their opinions on how much the experience contributed to their learning. We observed no differences between subjects with extensive virtual reality experience and those without.ConclusionsOur virtual reality simulator is an automated, customizable, fully immersive virtual reality system for training and assessing personnel in the proper response to a mass casualty incident. Participants perceived the simulator as an adequate alternative to traditional triage and treatment training and believed that the simulator was realistic and effective for training. Prior experience with virtual reality was not a prerequisite for the use of this system.

Versatile and Tunable Performance of PVA/PAM Tridimensional Hydrogel Models for Tissues and Organs: Augmenting Realism in Advanced Surgical Training.

The increasing complexity and difficulty of surgical procedures have led to a rise in medical errors within clinical settings in recent years. Gastrointestinal diseases, in particular, present significant medical challenges and impose substantial economic burdens, underscoring the urgent need for experiential, high-fidelity gastrointestinal surgical training tools. This study leverages patient-specific computed tomography (CT) and magnetic resonance imaging (MRI) data, combined with 3D printed manufacturing, to develop hydrogel organ models with tunable performance and tissue-mimicking softness. These properties are achieved by regulating the freeze-thaw cycles, cross-linking agents, and the concentration of incorporated antibacterial nanoparticles in DN hydrogels. Through the application of indirect 3D printing and the "sacrificial material method", we successfully fabricate organ tissues such as the stomach, intestines, and blood vessels with high precision. In ex vivo surgical training demonstrations, these tissue-like soft hydrogels provide an effective platform for preoperative simulation and surgical training in digestive surgery, accommodating various surgical procedures and accurately simulating intraoperative bleeding. The development of advanced bionic organ models with specific and tunable characteristics based on DN hydrogels is poised to significantly advance surgical training, medical device testing, and the reform of medical education.

Building Frontline Capability for Shared Decision-Making (SDM) in a Major Academic Oncology Center Caring for People With Non-Small Cell Lung Cancer: Performance Outcomes of a SDM Simulation Training Program.

There is a growing body of evidence on shared decision-making (SDM) training programs worldwide. However, there is wide variation in program design, duration, effectiveness, and evaluation in both academia (ie, medical school) and the practice setting. SDM training has been slow to integrate in practice settings. A pilot study of 6 multidisciplinary clinicians was conducted using quantitative and qualitative methods to evaluate changes in participant understanding and implementation of SDM in the practice setting. A 2-rater criterion-based evaluation method was used to assess a simulation-based case study role-play program using 7 domains of SDM pre and post training. The authors assessed whether clinicians addressed each of the 7 domains or what fraction of each domain was addressed as part of their simulation case study role-play performance. Focus groups were conducted pre- and postintervention to provide feedback to participants and to understand the clinician experience in greater detail. The increase in improvement in SDM ranged from 17% to 37%, and 7 of 8 domains for which participants were rated showed significant improvement. The areas of greatest improvement were seen in determining a patient's goals/preferences, including risk tolerance regarding treatments (+37%) and values and self-efficacy (+37%). The results of this study reveal a significant shift in clinician awareness of a patient's goals, preferences, and values. Postintervention, clinicians began to understand the value of building a partnership with their patients whereby the patient becomes an active participant in their clinical care.

Retraction Note: High dimensional image super-resolution model based on infrared spectral imaging for aerobics training simulation monitoring

Retraction Note: High dimensional image super-resolution model based on infrared spectral imaging for aerobics training simulation monitoring