Simulation Program Research Articles

Modeling and Numerical Investigations of Flowing N-Decane Partial Catalytic Steam Reforming at Supercritical Pressure

Steam reforming is an effective method for improving heat sinks of hypersonic aircraft at high flight Mach numbers. However, unlike the industrial process of producing hydrogen with a high water content, the catalytic steam reforming mechanism for the regeneration cooling process of hydrocarbon fuels with a water content below 30% is still unclear. Catalytic steam reforming (CSR) and catalytic thermal cracking (CTC) reactions occur at low temperatures, with the main products being hydrogen and carbon oxides. Thermal cracking (TC) reactions occur at high temperatures, with the main products being alkanes and alkenes. The above reaction exists simultaneously in the regeneration cooling channel, which is referred to as partial catalytic steam reforming (PCSR). Based on the experimental measurement results, an improved neural network correction method was used to establish a four-step global reaction model for the PCSR of n-decane under low water conditions. The reliability of the four-step model was verified by combining the model with a numerical simulation program and comparing it with the experimental results obtained by electric heating hydrocarbon fuels with a pressure of 3 MPa and a water content of 5/10/15%. The experimental and predicted results using the developed kinetic model are consistent with an error of less than 5% in the decane conversion rate. The average absolute error between the fuel outlet temperature and total heat sink is less than 10%. Using the PCSR model to predict the heat transfer characteristics of mixed fuels with different water contents, the convective heat transfer coefficient is basically the same, and the Nu number is affected by the thermal conductivity coefficient, showing different patterns with changes in the water content.

Clinical Simulation Program for the Training of Health Profession Residents in Confidentiality and the Use of Social Networks.

In the transition to a professional learning environment, healthcare professionals in their first year of specialized postgraduate clinical training (known as residents in Spain) are suddenly required to handle confidential information with little or no prior training in the safe and appropriate use of digital media with respect to confidentiality issues. The aims of this study were: (1) to explore the usefulness of an advanced clinical simulation program for educating residents from different healthcare disciplines about confidentiality and the dissemination of clinical data or patient images; (2) to explore the use of social networks in healthcare settings; and (3) to explore participants' knowledge and attitudes on current regulations regarding confidentiality, image dissemination, and the use of social networks; Methods: This was a cross-sectional study. Data were collected from all 49 first-year residents of different health professions at a Spanish hospital between June and August 2022. High-fidelity clinical simulation sessions designed to address confidentiality and health information dissemination issues in hospital settings, including the use of social networks, were developed and implemented. Data were assessed using a 12-item ad hoc questionnaire on confidentiality and the use of social media in the healthcare setting. Descriptive of general data and chi-square test or Fisher's exact test were performed using the SPSS 25.0 software; Results: All the participants reported using the messaging application WhatsApp regularly during their working day. A total of 20.4% of the participants stated that they had taken photos of clinical data (radiographs, analyses, etc.) without permission, with 40.8% claiming that they were unaware of the legal consequences of improper access to clinical records. After the course, the participants reported intending to modify their behavior when sharing patient data without their consent and with respect to how patients are informed; Conclusions: The use of advanced simulation in the training of interprofessional teams of residents is as an effective tool for initiating attitudinal change and increasing knowledge related to patient privacy and confidentiality. Further follow-up studies are needed to see how these attitudes are incorporated into clinical practice.

Effectiveness of a virtual reality triage simulation program for nursing students: A mixed-methods study

AimsTo examine the effectiveness of a virtual reality simulation (VRS) triage in improving students’ learning motivation, attitudes, satisfaction and learning experiences in an emergency nursing course. BackgroundVR facilitates the realization of clinical scenarios that are significant for teaching emergency nursing. Triage presents a unique challenge in emergency nursing courses, where practical learning opportunities are seldom available. DesignThe study employed a convergent parallel mixed-methods design. MethodsA total of 164 third-year nursing students were recruited from an emergency nursing course. The experimental group of 73 students participated in a VRS triage program and the control group of 91 students received a traditional program based on written case studies. The learning outcomes were evaluated using the Attention, Relevance, Confidence and Satisfaction motivational learning inventory together with questionnaires on learning attitudes and satisfaction. Qualitative data were collected through phenomenographic interviews. ResultsThe learning outcomes from the experimental group showed significant improvement in motivational learning inventory scores, with the greatest increase in satisfaction, followed by confidence, attention and relevance. Qualitative interviews with 30 students revealed four main themes in their learning experiences: “reflecting a real-world clinical environment,” “enabling the internalization of knowledge,” “enhancing clinical skills proficiency,” and “cultivating a positive attitude toward patient care.” The core theme was the establishment of professional core competency. ConclusionsVRS learning shows positive outcomes in enriching students’ learning experiences. This study contributes to the literature on the use of VR technology in nursing education by offering insights into the effectiveness of VRS learning.

A Finite Element Analysis for Investigating the Effects of Moving Loads on Flexible Pavements

To assist researchers in solving challenging structural mechanics engineering problems, finite element modeling (FEM) has grown to be a very popular technique. The several layers of various materials that make up a pavement's complicated structure and affect how it responds to stress have an impact on how it behaves. In this study, finite element analysis is done on a real existing road which is named Nowhata-Chowmasia road, situated in Rajshahi, Bangladesh. FEM is used to study this flexible pavement, which consists of 7 layers (surface, binder, base type-1, base type-2, sub-base, enhanced subgrade, and subgrade). The effect of the depth of the base layer on vertical stresses and displacements is examined using the ABAQUS/CAE 2017 modeling and simulation program. The base layer of the real existing road is 150 mm provided by the Roads and Highways Department (RHD) Rajshahi, Bangladesh. The analysis is done by measuring stress and displacement under wheel load by decreasing the base layer thickness to 100 mm and further increasing it to 200 mm. The modeling approach assumes that all materials function in a linear elastic manner. The Poisson's ratio, layer thickness, and material elastic modulus are the major inputs used in the modeling procedure. In this work, flexible pavement is simulated using a conventional axle load of 100 kN, which corresponds to a single four-wheeled axle. Finally, FEM analysis showed that the maximum stresses are 0.35 MPa, 0.27 MPa, and 0.21 MPa and maximum displacements are 0.52 mm, 0.34 mm, and 0.21 mm for 100 mm, 150 mm, and 200 mm base layer thickness respectively. So, for the increase of base layer thickness the stress and displacement are decreased.

Impact of a poverty simulation program on the unconscious biases – A multi-site study

Impact of a poverty simulation program on the unconscious biases – A multi-site study

Operational electricity cost reduction using real-time simulators

Ensuring the safe and cost-effective electricity transmission to consumers, along with the efficient and sustainable operation of power systems, has long been a primary objective for power system managers and operators. However, achieving optimal performance in a modern power system requires timely planning and operational optimal routines to be run within the realm of real-time simulation programs, and sometimes, the divergence becomes a problem with these developed routines. Despite extensive research aimed at advancing these objectives, the growing complexity of networks and their constraints has often led to the oversight of simultaneously considering both technical and economic aspects during operation. In this paper, an innovative real-time framework is introduced to reduce the operational costs of a power system swiftly. This framework addresses various nonlinear constraints, such as transmission losses, generation-consumption balance, power device limitations, and transient stability constraints, across various operational scenarios within a real-time simulator. This novel approach leverages scattered search and intentional contingencies within the network to pinpoint the optimal operating point, taking into account various network dynamics, including Automatic Voltage Regulators (AVR), governors, and tap of the transformers. The proposed method offers a fast and robust approach to identifying the most effective operating conditions for a power system. It incorporates considerations for sudden contingencies and extends capabilities through parallel simulations. It not only facilitates pre-determined preventive actions but also enables the adjustment of control parameters during post-contingency periods, such as fine-tuning of the active and reactive power generation of generators and adjusting the tap settings of transformers within power networks. Since the network simulation can be executed on distributed computers, referred to as ’Global,’ it is possible to achieve global network optimization. This approach allows for the consideration of grid networks, including renewable energy sources with models distributed through PCs. Also, it accounts for the induction motor losses within all factories involved in the global simulation. The results obtained from simulating the proposed method on a commercial real-time simulator demonstrate the superior effectiveness of the proposed framework compared to the existing methodologies, highlighting its potential to enhance the operational efficiency and economic viability of power systems.

Neural Network Algorithm for Training a Mobile Robot in the Task of Following a Target

The article is devoted to the research, development and implementation of an artificial neural network with reinforcement for controlling a mobile robot with a differential drive to solve the task of following a target. The authors of the study present a detailed description of the architecture of the neural network, its training using a deep deterministic gradient policy algorithm, and integration with the robot control system. A distributed neural network structure was selected for specialized generation of controls, for which the authors chose the angular and linear speed of the robot. A system of rules has been synthesized that takes into account changes in the distance between the robot and the target object and tracking of the heading angle in real time. A mathematical model of a robot with a differential drive is considered, on the basis of which a simulation program is implemented for intermediate training of a neural network, as a result of which the initial weighting coefficients are formed. Using this program, you can get by with less energy and time costs at the initial stage of the study. Experiments to test the effectiveness of the developed neural network were carried out in the Gazebo simulation environment using the ROS2 communication interface. The article describes the process of integrating a neural network with a robot control system in a simulation environment, as well as test results and analysis of the obtained data. The results of experiments are presented for three scenarios in which the initial position of the robot is the same, the remaining parameters are generated according to the rules described by the authors. The effectiveness of using such a solution for trajectory planning has been confirmed. The research contributes to the field of autonomous systems and demonstrates the potential of artificial reinforcement neural networks in robotics.

Modeling magnetic field amplification in supernova remnants driven by laser

Abstract The origin of magnetic fields and their amplification have always been hot topics in fields such as astrophysics and high-energy-density physics. Among them, the turbulent dynamo effect is an important candidate mechanism, and the interaction between supernova remnants (SNRs) is an important carrier for studying the amplification effect of turbulent magnetic fields. In this paper, we use the radiation magnetohydrodynamic simulation program to carry out a scaling simulation study on the amplification effect of turbulent magnetic fields in the interaction of SNRs driven by powerful lasers. We investigate and compare the evolution of turbulence under different laser driving methods, different directions, and different intensities of initial external environmental magnetic fields. Here, we carefully identify the contributions of Biermann self-generated magnetic fields and environmental magnetic fields in the process of magnetic field amplification, present magnetic energy spectra, and magnetic field amplification factors, and analyze the influence of radiative cooling effect on turbulence and magnetic field evolution. The results show that the collision direction component of the environmental magnetic field dominates the process of magnetic field amplification, and the frequency spectrum of turbulence is consistent with Kolmogorov’s law. The research results are necessary for sorting out and elucidating the physical mechanism of magnetic field amplification in SNRs, and have reference significance for regulating turbulence in strong magnetic fields in the future.

Study of Nursing Students’ Experiences pre and post Clinical Practice at clinical skills training center in Duhok city

A novel approach to education called simulation-based training offers students excellent chances to acquire and safely apply what they learn about nursing care. The purpose of this study was to evaluate how simulation-based training affected nursing students' abilities as clinical practitioners and their sense of self- Efficaciousness. Subjects and Methods: This study (pre-posttest intervention) employed a quiz-experimental design and was conducted utilizing moderate- and high-fidelity simulators on 63 first-year nursing students for the academic year 2023–2024.At Duhok Polytechnic University and Duhok Technical Institute, this study was conducted. Data collection: demographic information, self-efficacy, and clinical proficiency tests. The software SPSS version 20 is used for analysis. Results: Following their involvement in the simulation program, participants who received the simulation-based training shown statistically significant improvements in their self-Efficaciousness and clinical proficiency levels. Conclusion: Self-Efficaciousness and clinical competency can be improved in nursing courses through simulation-based training. It is strongly advised that the nursing curriculum use multiple-patient simulations as a teaching-learning technique.

The Effect of Fluorine and Hydrogen Concentrations on the Chain Reaction of HF Chemical Laser

A numerical investigation has been performed to examine the effect of fluorine concentration on the chain reaction mechanisms and parameters of hydrogen fluoride (HF) chemical laser. The practical difficulties associated with this type of lasers impose that an alternative route might be quite useful. Thus, particular attention was paid to develop a computer program to investigate various processes. The results of this computer simulation program proved their credibility when compared with the little published data. This computer program is called Reaction Rate Simulation Model (RRSM). An entirely new approach to emulate the reaction mechanisms has been followed. The effectiveness of reaction rates in the processes of HF laser production has been investigated. This simulation program dealt with the percentages of the forward and reverse reactions, when a large number of reactions have been considered. In addition a large number of species have been taken into account in these reactions. From the computer program (RRSM), some valuable results could be predicted with regard to the hydrogen fluoride chemical laser.

Procedure Design and Reliability Analysis for Prediction of Surface Subsidence of a Metal Mine Induced by Block Caving Method—A Case Study of Pulang Copper Mine in China

Surface subsidence resulting from block caving mining causes considerable environmental and economic harm in mining areas, highlighting the critical need for accurate predictions of surface subsidence. Given the unique features of the block caving technique and the resemblance between the released ore pillars and the mining processes, this paper developed a lightweight model to forecast surface settlement utilizing the probability integration approach to address the issue of predicting surface settlement in metallic mines. This study focuses on the Pulang Copper Mine, situated in the northeast of Shangri-La County within the Yunnan Province, as a case example. This mine employs the block caving method, which results in substantial surface subsidence. A visual mining simulation program is designed to combine the ore mining plan with the prediction model, manage the ore output of each mining point in batches, treat the ore pillars released in the planning cycle as strip work, and simulate and calculate the surface area above the ore pillars settlement value. The calculated values of surface subsidence induced by ore drawing are then interpreted as the downward displacement of the surface subsidence beneath the strip workings. Furthermore, to verify the reliability of the model, three-dimensional laser point cloud data of the Pulang Copper Mine in recent years were collected, and the differences between the predicted surface and the measured surface were calculated and analyzed.

A study on in-situ characterization technology development for clearance verification of radioactive waste from nuclear decommissioning

Although the clearance level of every radioactive nuclide was published by the IAEA to promote the recycling and reuse of decontaminated radioactive waste worldwide, technical and regulatory issues have always been raised around the application of the criteria. Therefore, several countries are developing in-situ characterization equipment or apparatus for on-site verification to check if the clearance criteria is met.In this study authors developed a pilot radiation detection and measurement system using in-situ characterization technology to solve the issues, which consists of a 3D scanning camera system and a built-in Monte Carlo simulation program. Measurement results show that MDA (Minimum Detectable Activity) of the current design was indisputably below the clearance level and built-in Monte Carlo simulation package closely predicts the measurements results with the error of less than 5%. This implicates that it can determine with enough margin whether the radioactivity level of decontaminated metallic components meets the clearance criteria at decommissioning site or not.Practically when we measure the radioactivity from gamma ray source mass attenuation always takes place during the photon transports through the medium. In fact, the reduction depends on the material, shapes, and radioactive sources. In this study the reduction factors were experimentally examined according to the influencing parameters and the results were saved as DCF (Density Correction Factor) in the data base. As expected, it turned out that the factor is somewhat affected by medium material and radioactive sources, but it is basically proportional to the distance of gamma ray passage.It is expected that upgraded design with more accurate and reliable instruments can make it easier for regulators to accept the application of the in-situ characterization technology on-site.

Effect of sound absorption on noise reduction in the automotive industry

Industrial noise is one of the most common physical factors that cause annoyance and damage workers' health in the long term. Precautions should be taken to reduce noise and improve acoustic performance in industrial working environments. This paper aims to analyze the acoustic performance of the automotive industry and contribute to the global outcomes of sustainability and the development of strategies to improve the quality of the working environment through improvement scenarios. For this purpose, the automotive industry in Türkiye was examined as a case study. In-situ acoustic measurements were made in the seat manufacturing unit of an automotive factory and the current situation was transferred to the simulation program. The effects of acoustic improvements on A-weighted sound pressure level and reverberation time at mid-frequencies (500, 1000, 2000 Hz) were investigated through three different scenarios. In the investigations, noise distributions were carried out through noise mapping. The A-weighted sound pressure levels in the automotive industry were reduced by approximately 15 dB. As a result of the study, suggestions for noise control precautions and their effects on the automotive industry seat manufacturing unit are presented.

Numerical simulation of a hybrid energy system proposed for low carbon data center

Low-carbon energy application for both large grid and distributed energy consumers is an urgent problem to be solved. Data centers (DC) are the typical distributed large-size energy consumers, and the application of renewable energy and energy storage is a promising solution for data center decarbonization. This paper developed a complete hybrid energy system (HES) simulation process for data center applications. The photovoltaic (PV) cell, hydrogen electrolysis, hydrogen storage, proton exchange membrane fuel cell (PEMFC), lithium battery (BAT), grid, and data center load are considered in the HES. A one-dimensional two-phase flow PEMFC model is developed. The detailed mass transfer process inside the PEMFC cell is modeled. The PEMFC model-solving algorithm is developed and integrated into the HES simulation program. The energy management system (EMS) based on a logical flow chart energy management strategy is integrated by editable subfunction. The HES simulation program is coded and implemented based on the MATLAB-SIMULINK environment. The yearly HES performance simulations are conducted and analyzed for a 200 kW data center in Xi’an with different HES parameters and an appropriate HES parameter arrangement is provided. The main contribution of this work is the development of an editable HES simulation program that is extensible for data center applications.

Otolaryngology Simulation Curriculum Development and Evaluation for Medical Education in Rwanda.

This study aimed to assess the feasibility and acceptability of a new low-cost otolaryngology simulation training curriculum for medical students in Rwanda. Given the limited access to hands-on training and equipment in low-middle-income countries, building confidence in performing basic otolaryngology skills is vital for all medical students, especially where all graduates initially serve in primary care before specializing. Preintervention and postintervention assessments of simulation training. Conducted at the University of Global Health Equity in Rwanda. The simulation program comprised 3 primary components: (1) a low-cost, moderate-fidelity model for cricothyrotomy and tracheostomy practice, (2) a low-cost, low-fidelity ear model for foreign body and cerumen removal, and a high-fidelity manikin for practicing, (3) epistaxis management, and (4) nasal foreign body removal. Students underwent pretest and posttest assessments measuring their knowledge, experience, perceived skill, and confidence in performing these procedures. A survey collected feedback on the program. A total of 29 medical students participated in the simulation program, integrated into a 1-week otolaryngology "boot camp" preceding a 3-week clerkship rotation. All models were created using basic, locally available materials, at a total cost of $1.02 for cricothyrotomy and $0.20 for foreign body models. Knowledge and perceived confidence increased for all 3 simulations. All students found the simulations useful, enjoyable, and anticipated using these skills in future training. The study's results demonstrated that the low-cost otolaryngology simulation was well-received and enhanced knowledge, interest, and confidence in performing basic otolaryngology skills across all simulations.

Improved real-time [formula omitted] control for aero-engines based on the equilibrium manifold expansion model

This paper investigates the transient performance and disturbance rejection control problem for aero-engines based on the equilibrium manifold expansion (EME) model. Considering the operating characteristics of the aero-engine vary greatly during different flight states, it is difficult to ensure the performance of the aero-engine in different states using a single controller designed offline. To solve this problem, this paper proposes an improved real-time H∞ controller. Through driving the controller to match the changes in dynamic characteristics of the system, the stability and disturbance rejection performance of the system are guaranteed over a wide range effectively. In addition, a dynamic adjustment mechanism is designed for the disturbance rejection parameter in the proposed real-time H∞ controller, which further improves the transient performance of the system. The sufficient conditions to ensure the stability of the system under the designed method are also given. Finally, the effectiveness and superiority of the proposed method are verified through an aero-engine numerical simulation program and a hardware-in-the-loop (HIL) experiment.

Intelligent Generating Controller a Desflurane Concentration Value Which Helps to Decrease Blood Pressure.

The aim of the article is to determine the appropriate concentration of desflurane to effectively counteract the increase in blood pressure resulting from surgical stress. In medical practice, this increase is often limited by using additional doses of opioid drugs. Additional medications or higher doses of those already used may adversely affect your health. During anesthesia, physician must note the use of drugs and remember them, especially those that he has recently administered, which affect his concentration. For this purpose, the authors decided to propose support for the selection of desflurane concentration so that frequent use of opioid drugs is not necessary. The authors used a system based on AI issues to accomplish this task. The learned system supports the anesthesiologist's work by imitating him. The proposed method for selecting the desflurane concentration is based on a fuzzy controller. This system includes a learning mechanism that allows for minimizing the operating error. The main advantage of this system is the ability to build a function allowing the selection of anesthesia parameters without knowledge of the mathematical description of the process. To accomplish this task, you need an expert who will provide information in the construction of logical if-then sentences (points in space). The fuzzy controller connects the points in the consideration space appropriately, generating a hypersurface. The algorithm test was performed only by computer without the participation of patients. The operation of the proposed algorithm was verified by computer simulation. The authors of the article analyzed the compliance of the obtained results with the table provided by the expert. The desflurane concentration values obtained by computer simulation are similar to those given in the table Minimal driver error does not affect the patient's clinical response. This error results from the functions used in the fuzzy system and its settings. The results of the performance test of the proposed algorithm are presented in a time course, and it has the shape of a step function. The work proposes a function that allows you to enter the time needed for the body's reaction to reach the desired Etdes level. In this study, a controller was created to support the selection of the concentration of desflurane allowing for a reduction in blood pressure (resulting from surgical stress). The results obtained by computer simulation provide valuable insights for optimizing anesthesia. This system can also be used as an important simulation program for teaching purposes.

Enhancing sustainable healthcare practices through energy-efficient wireless body area networks

This paper explores how the integration and performance of Wireless Body Area Networks (WBANs) contribute to sustainable healthcare practices. WBANs play a crucial role in reducing the environmental footprint of healthcare systems by providing continuous monitoring that can prevent unnecessary hospitalizations and reduce the consumption of disposable medical supplies. Additionally, the design of WBANs using environmentally friendly materials, low-power devices, and recyclable components is discussed to optimize the sustainability of healthcare practices. To enhance infrastructure, services, and quality of life, new technologies have been integrated to improve WBANs. Patients' essential health data may be continuously and instantly collected thanks to these networks, and healthcare providers can receive the data right away for quick analysis and action. WBANs have healthcare benefits, but there are also major drawbacks. Technologies that can combine low power consumption, minimal delay, and high enough data rates are needed for WBANs in order to support a variety of medical applications. The effectiveness of the LoRaWAN and IEEE 802.15.6 technologies in WBAN is assessed in this paper. With the use of seven crucial metrics which are throughput, arrival rate, delay, energy consumption, residual energy, network lifetime, and packet delivery ratio (PDR), this paper seeks to study which technology is appropriate with WBANs using NS3 as a simulation program. With network parameters, 1000 seconds, and 50 nodes, the paper evaluated the performance of each technology. The results show that IEEE 802.15.6 is superior in terms of throughput, PDR, and arrival rate whereas LoRaWAN is superior in terms of energy consumption, residual energy, network lifetime, and delay.

Effect of Sound Absorption on Noise Reduction in the Automotive Industry

Industrial noise is one of the most common physical factors that cause annoyance and damage to workers' health in the long term. Precautions should be taken to reduce noise and to improve acoustic performance in industrial working environments. This paper aims to analyze the acoustic performance of the automotive industry contributes to the global outcomes of sustainability and develop strategies for improving the quality of the working environment through improvement scenarios. For this purpose, the automotive industry in Türkiye was examined as a case study. In-situ acoustic measurements were made in the seat manufacturing unit of an automotive factory, and the current situation was transferred to the simulation program. The effects of acoustic improvements on A-weighted sound pressure level and reverberation time at mid-frequencies (500, 1000, 2000 Hz) were investigated through three scenarios. In the investigations, noise distributions were carried out through noise mapping. The A-weighted sound pressure levels in the automotive industry were reduced by approximately 15 dB. As a result of the study, suggestions for noise control precautions and their effects on the automotive industry seat manufacturing unit are presented.

AeroRunway: Diverse Weather and Time of Day Aerial Dataset for Autonomous Landing Training

Acquiring a sufficient amount of diverse and accurate real-world data poses a significant challenge in advancing autonomous systems, which are becoming increasingly popular. Despite the aerospace industry's keen practical and economic interest in autonomous landing systems, readily available open-source datasets containing aerial photographs are scarce. To address this issue, we present a dataset named AeroRunway, comprising high-quality aerial photos designed to aid in runway recognition during the approach and landing stages. The dataset is composed of images using X-Plane, a flight simulator software developed by Laminar Research. It is a highly realistic and detailed flight simulation program that allows users to experience the sensation of piloting various aircraft in a virtual environment. These synthetic images were collected mostly in variable weather conditions above 5000 feet to supplement existing satellite imagery that can be used for extreme situations. This dataset was created from 28 different airports in different weather conditions, such as foggy and rainy, at various times of the day, such as day and night, and consists of 3880 images and is approximately 13.3 GB in size.