In the previous report, I mentioned that my current goal is to collect and analyze information about the 1st to 3rd contests, which I did not participate in. In this report, I review a lecture paper written by Professor Yoshida Keisuke (Professor Emeritus, Kyushu University), who served as the organizer of the 3rd contest, and add my own thoughts on "collaboration between departments and branches," "scale and management of the contest," and "use of potential energy," to serve as a basis for sustainable contest management in the future.

The Alternative ☆ Energy Contest is a new contest on "energy utilization" mainly for university and technical college students, which started in 2008 as an event in which the technology and society departments of the JSME cooperate. The mark "☆" in the title of the contest indicates something that goes beyond the preconceived notions of alternative energy, and the essence of this contest that appeals for novel ideas appears there. From 2012, the year after the Fukushima nuclear accident caused by the Great East Japan Earthquake, a stationary event was held at the College of Engineering, Nihon University located in Koriyama City, Fukushima Prefecture, as an event to watch over the reconstruction of Fukushima. The 17th meeting (October 19th, 2024) is scheduled to be held on the onsite and website with the College of Engineering, Nihon University as the operating base. We are grateful for the opportunity to give an overview of this contest at this civic forum in this paper.

The Low temperature differential Stirling engine(LTDSE) for a craft workshop was improved. The difference of the LTDSE used for workshop between lateest version and the LTDSE used in 2022 and 2023 is only displacer. Fine adjustment during assembly is not necessary. The explanation for attendees of craft workshop is shown by some pictures.

First, we will introduce the background of this Forum and the definition of Extended Digital Twins. Then the capability of Generative AI to recognize and generate Human Uncertainty such as Emotions and Creativity will be explained. Finally, we will examine the possibility of integrating Generative AI and Knowledge Graphs to convert and structure tacit Knowledge into explicit Knowledge.

Emotion mechanics aims to mathematically explain and predict the dynamics of human emotions. It formulates dominant emotion dimensions, termed the core affect, which consists of arousal and valence, using the brain's free energy. Free energy is an information quantity that represents prediction errors or uncertainty processed in the brain. The free energy principle suggests that free energy is minimized through the recognition process leading to Shannon surprise. We formulate arousal and valence as the surprise and decrease in free energy, which represents information gain. This formulation explains arousal potential, forming a convex function of valence over arousal, and epistemic emotions such as curiosity and interest, which drive the active inquiry process.

Recent advancements in AI and IoT are leading to the development of smart homes, enabling the automation and remote control of household appliances. However, real-time assessment of individual user comfort remains challenging. Multimodal emotion analysis using physiological indicators like pupil diameter and heart rate is gaining attention. By combining facial expressions, heart rate variability, and skin conductance, the relationship between emotions and the autonomic nervous system can be evaluated. In this presentation, we review previous experiments on emotion classification using EEG, heart rate, and pupil diameter, and introduces our research.

This study presents a basic investigation of the possible behaviors of autonomous vehicles under mixed autonomy conditions. Specifically, the author focuses on two behaviors: acquisition of acceleration strategies as a local behavior and altruistic route selection as a global behavior. For the acquisition of acceleration/deceleration strategies, a reinforcement learning algorithm was employed to reduce both CO2 emissions and traffic jams. Simulations on a road segment with a traffic light showed that an appropriate strategy can be learned. For altruistic route selection, autonomous vehicles, considered to have a relatively low time value, were assumed to tolerate suboptimal routes. Simulations on a medium-sized city road network showed that the performance of the whole transportation system, including human-driven vehicles, was improved. It is expected that the control algorithm proposed in this study, operating under the assumption that traffic safety is ensured for autonomous vehicles, will provide additional benefits as well as prevent traffic accidents.

Lipid bilayer membranes are critical cellular components that compartmentalize cells and organelles and provide the platform for various physiological functions such as molecular recognition, signal transduction and energy conversion. Dysfunction of the plasma membrane is directly linked to cell death, and, in this context, the measurement of membrane function is extremely important for physiological and pathological insights. On the other hand, lipid bilayers can be artificially reconstituted on solid substrates. Such artificial lipid bilayers are not only useful as biomembrane models but are also expected to be used as interfaces for nano-bioelectronic sensors. In this talk, I would like to present our recent research on the study of lipid membrane functions from two aspects: 1) the development of an electrochemiluminescence (ECL) imaging system to elucidate the effects of peptides on lipid membranes, and 2) the use of artificial lipid membranes for the detection of lipid vesicles with the solid-state nanopore sensor.

Nowadays, the sustainable development technologies have been attracted attention in manufacturing fields. We therefore focus on the bamboo as a suitable material because it has the growth ability in it and one of the sufficient forest resources in Japan. In the present report, we look at the fine bamboo fibers extracted by endmilling processes and discuss the development of bamboo fiber gears with a their molded technology based on self-adhesive processes for sustainable manufacturing system.

Novel 3 D.O.F. spherical gear, “ABENICS”, was invented and developed by Dr. Kazuki Abe who used to be a Ph.D. candidate in Riichiro Tadakuma laboratory at the graduate school of the faculty of engineering of Yamagata University. ABENICS spherical gear has 3 active degrees of freedom that are perpendicular to each other and cross at one point. It also has infinite motion range around pitch, roll, and yaw axis. It has huge possibility to be adapted to various industries. In this paper, the fundamental principle and mechanism of ABENICS spherical gear are explained. The metallic ABENICS spherical gear is also presented, and its application as a joint mechanism for a humanoid robotic arm is introduced. The monopole gear was fabricated according to the calculation of the virtual milling with the geometric shape of the base spherical gear. This base spherical gear works as a virtual milling tool to realize the profile of the monopole gear with the same concentric pole structure as the spherical gear. With this design, the monopole gear can mesh with the spherical gear without any limitation in their motion range.

This presentation introduces ChiCaRo, a telepresence robot developed for remote childcare support. Designed by our research group, ChiCaRo aims to assist parents and improve childcare quality by facilitating remote interactions between children and caregivers. Modern childcare faces challenges due to societal changes like increased female workforce participation, nuclear families, and reduced community interactions, leading to parental isolation and stress. ChiCaRo addresses these issues by providing support in homes and nurseries, aiding child development, and promoting broader societal use. The presentation will cover practical examples, system benefits, and research on ChiCaRo's acceptance and future applications.

Xooms Inc. develops content that provides "fun" and "exciting" experiences using technologies such as XR (VR/AR/MR), image recognition, and machine learning. Leveraging our expertise and know-how in content creation, recently, in collaboration with our partners, we developed an XR application for operating telepresence robots to facilitate remote communication. This application features an intuitive and user-friendly interface implemented through VR headsets and controllers. In the future, we aim to further enhance the operability of this interface and expand the application of XR interfaces across various industrial sectors, including research and product development.

iPresence Ltd. From Kobe, Japan specializes in developing cutting-edge telepresence solutions that enable seamless remote communication and interaction. Utilizing technologies such as telepresence robots and digital twin services, we provide innovative communication tools for a variety of industries. Our expertise in telepresence and remote operation allows us to offer services that bridge the gap between physical and virtual spaces, facilitating real-time collaboration and engagement. Recently, in collaboration with our partners, we have developed advanced telepresence avatar robots and related systems designed to enhance remote work, telemedicine, and educational applications. Our aim is to further refine these technologies and expand their application across different sectors, including industrial operations, healthcare, and education.

This paper examines the pivotal role of system integration in value creation and the resolution of complex societal issues. This paper examines the evolution of systems engineering and architecture design, with a particular focus on their significance in the management of complexity and the promotion of innovation. The authors introduce several structural modeling techniques, including ISM, DSM, DMM, and MDM, which can be employed in the design and management of complex systems. The concept of "panoramic value" is put forth as a foundational consequence of system integration. This superior-order value is derived from system-wide interactions and is defined as "panoramic value." The paper highlights the potential of data-driven methodologies in facilitating enhanced system integration and value co-creation. The paper introduces a novel "three-storey model," which integrates learning, intelligence, and problem recognition. The authors posit that this approach has the potential to make a significant contribution to the resolution of complex social issues and the realization of sustainable development. Moreover, the authors emphasize the importance of interdisciplinary collaboration, human-centered design, and ethical considerations.

The Model Based Development (MBD) is the adoption of digital technology to transform real machinery to virtual machinery. MBD has been adapted 20 years ago, but MBD is not completely used because of plant model is not complete.

As a development methodology that enables highly efficient and advanced manufacturing without rework through holistic optimization, Model-Based Development (MBD) is being actively promoted. However, with the recent significant transformations in the automotive development environment, there is a pressing need for the evolution of MBD methodologies. This paper examines the environmental changes surrounding the automotive industry and the corresponding challenges faced by MBD, and explores the requirements for modeling as a means to address these challenges. Furthermore, it introduces the concept of the physical function model as a modeling method that satisfies these requirements, supplemented with case studies. Within this context, the paper elucidates the characteristics of modeling using the physical function model and, based on these insights, discusses the potential of model description languages to represent functions across various engineering disciplines.

The concept of time constant is essential in considering a sustainable social system in which the market economy is in harmony with social common capital such as local communities and nature. Therefore, we have developed a time-constant model of market adjustment process based on physical functions. In this paper, we propose an analogy with physical functions and economic domain, where flow is goods flow and effort is price. This allows us to model the economic system in which demand and supply are regarded as masses and market as a spring. Furthermore, this model can be transformed into a time-constant model by normalizing inertia and elasticity by losses in demand and supply. Numerical results on the effects of demand, supply, and market time constants on the market adjustment process are presented for the initial conditions of excess demand and excess supply.

Autonomous driving technologies is essential to realizing sustainable logistics and regional transportation services, and require to reduce further communication latency in mobile networks that supports the technologies. In order to contribute to the realization of sustainable logistics and regional transportation services, we working on technology research and developments of ultra-reliable and low latency vehicular communications towards application to automated follower platooning for truck or bus rapid transit (BRT) vehicles. Unfortunately, the current cellular mobile networks suffer from a major problem, mainly in rural areas, where the transmission latency at the wired backhaul side between the base stations (BSs) and the mobile core nodes (CNs) is larger than the transmission latency at the wireless access side. On the other hand, to solve such problem in the cellular mobile networks, SRv6 Mobile User Plane (MUP) has emerged, which integrates 3GPP based mobile network with Segment Routing over Internet Protocol version 6 (SRv6). SRv6 MUP has the functionality to advertise the Internet Protocol (IP) routing information to the wired transport network among BSs and CNs in consideration to user terminal (UE) mobility, that enables not only low-latency edge computing and but also low-latency UE-to-UE communications via BSs with the shortest packet route, efficiently. This report fast overviews the SRv6 MUP technology. Then, this report also introduces a new concept of V2N/V2N2V communication latency reduction technology using SRv6 MUP, regarding evolved mobile network technology towards autonomous driving era. Finally, it presents field evaluation tests of low latency in-vehicle UE-to-UE communication using SRv6 MUP under a commercial 5G Standalone network assuming application to low-latency V2N2V, and the results demonstrate the effectiveness of SRv6 MUP in practical network environments.

New designing processes for sporting gear are introduced. In our new process, three technologies, 3D printing, Finite element method (FEM), and Algorithmic design process, have played an important role. Due to the development of computer, these three technologies have been developing rapidly in recent years and applied in various industrial fields. In this study, we introduce some engineering trials to design sporting footwear using these technologies. Our trial showed that these technologies brought various benefit to new product designing such as streamline of the development period and boundless structure design.

With a storage containing wet radioactive waste such as fuel debris, it is important to reduce the risk of explosion and combustion due to hydrogen generated by radiolysis of water. This study, as a part of the development of simulation technologies for verification of reduction countermeasures and proposal of new countermeasures, conducted a trial simulation of the hydrogen concentration behavior in a room installed the hydrogen recombination catalyst. The simulation using a CFD code focuses on reduction effect of hydrogen concentration by reducing to flow resistance of catalyst. It was found that the hydrogen concentration distribution was affected by formation of a circulating flow in a room by catalyst.

One initiative to decarbonize railways is the development of fuel-cell vehicles. However, the practical application of fuel-cell railway vehicles requires safety confirmation, and one critical issue is hydrogen concentration assessment in the event of a hydrogen leakage in a tunnel. In this study, numerical analysis was performed to investigate the hydrogen leakage flow from a stationary railway vehicle in a tunnel. The test vehicle comprised a two-car train set with a hydrogen leakage in its roof equipment. The tunnel was a single-track mountain tunnel, 400 m in length, located on a conventional Japanese railway. The Fire Dynamics Simulator (FDS) was used for the numerical analysis. The results demonstrated that the leaked hydrogen rose toward the crown of the tunnel and flowed toward both tunnel portals. The hydrogen concentration was the highest immediately above the leakage point and rapidly decreased toward both tunnel portals.

Hallway Model is experimented to validate CFD for hydrogen dispersion in a partially open space.

This paper describes when position of Door Vent (outer air inlet) is lowered on Hallway Model. CFD shows lower position decries hydrogen concentration in Hallway. For easier understanding, results of CFD are showed using animation.

This report shows the results of an investigation focusing on the hydrogen concentration near the ceiling, which was not fully analyzed in the previous report. Japan has declared its goal to become carbon neutral by 2050, utilization of hydrogen is one of the leading candidates for decarbonization. For safely use of hydrogen, quick detection of leaked hydrogen is important, and also high accurate prediction system of leaked hydrogen dispersion and a system to prevent hydrogen concentration from increasing. Inoue et al. carried out hydrogen leakage and dispersion experiments using the Hallway Model, and author et al. showed that numerical simulations can accurately reproduce them. In previous report, investigated the effects of obstacles placed in the Hallway Model on the hydrogen concentration distribution. In this report shows the hydrogen concentration retained between hanging partition walls installed near the ceiling of a hallway model is investigated, and high hydrogen concentrations are observed locally near the hanging walls. It is shown that when there are obstacles such as hanging walls, a localized increase in hydrogen concentration could lead to a fire or explosion.

When extracting hydrogen from ammonia, which is attracting attention as a new hydrogen carrier, it is necessary to extract only hydrogen from the hydrogen-nitrogen gas mixture. Hydrogen separation membranes are used as a means of gas separation, and high quality is required. In this study, focusing on the catalytic effect of transition metals, we fabricated metal/polymer multilayer membranes by layering transition metals on the surface of polyimide (PI) membranes with high heat resistance, and evaluated the hydrogen/nitrogen separation characteristics using the approach of measuring the permeability of the polymer membrane. The permeability coefficients of the Ni/PI multilayer films were measured using a gas permeability apparatus. The results showed that the Ni/PI laminate membrane exhibited a higher separation factor and a lower hydrogen permeation coefficient at low temperatures than the PI monolayer membrane, and these values became the same as those of the PI monolayer membrane as the temperature increased. This is because the Ni layer was the rate-limiting step in gas permeation at low temperatures, while the PI layer was the rate-limiting step at high temperatures.

This paper is described that textual information such as sentences is composed of three elements,these element combined of the concept for generative AI, it is possible to decipher the undeciphered scripts of ancient Greek civilization. The sentences related to the event from the three elements of shape, pronunciation, and culture, the concept of digital twins of custom is employed. As a result, it was found that the word order of the ancient Greek civilization script is SOV, SVO, and VSO, and the sentence pattern resembles that of kanji-kana mixed sentences.

Stochastic differentials in stochastic differential equations are defined by Ito integrals, however if stochastic differentials and stochastic variations are defined in a mechanical engineering field more better.In this paper, stochastic differentiation as a difference due to distributed time is defined, and clarify its relationship with tensor products and renormalization groups in engineering.The examine the meaning of the Rough path as tensor product , and are obtained the Uncertainty principle in quantum mechanics due to the Rough path based on the renormalization group due to this rough path. Furthermore, the quantum gravity equation is obtained from the rough pass theory.

The progress of material failure is modeled as an AI for symbol grounding problem, and the historical situation of material failure is analyzed for the acoustic radiation analysis. The effect of radiating fracture energy as a log-normal distribution is applied to digital twins In mechanical engineering.

In the current era of designing system of systems, the interconnection of various energy-related facilities and information control systems gives rise to new customer value, leading to the development of more attractive systems. This paper introduces an attempt to apply model-based systems engineering (MBSE) to the requirements analysis of energy systems, such as a hydrogen energy management power station. By emphasizing user experience (UX) design principles throughout the process, from deriving system requirements to evaluation, we ensure a human-centered design approach. System requirements are derived using context diagrams and use case diagrams to secure a user perspective. These requirements are then evaluated through operational optimization simulations focused on enhancing the overall user experience. Our company has developed an operational optimization tool that intuitively models user demands and challenges, such as those at power plants and factory power facilities, including carbon dioxide (CO₂) emission reduction, to find optimal solutions. By combining MBSE with UX design, we aim to refine the process of defining and evaluating system requirements, tailoring the engineering process to optimize the efficiency of design and operation for energy system development, thereby delivering customer value.

In recent years, the automotive development has been required to respond to changing market needs and stricter regulations. It is believed that further efficiency can be achieved by utilizing the accumulated CAE data from developments based on the design concept of "Toyota New Global Architecture" that considers overall optimization.

In this paper, we report on the construction of a surrogate model that can predict stress with high accuracy by incorporating shape features such as surface concavity and convexity into the training data, drawing on the methods for constructing thermal boundary surrogate models using "statistical methods" and "deep learning".

This paper discusses inductively coupled plasma discharge which is widely used in semiconductor fabrication processes, from view point of numerical evaluation. Three-dimensional asymmetric simulation is performed using COMSOL Multiphysics^Ⓡ. Mixture gas of Ar/CH₄ is introduced as a reaction gas. Two different modelling methods for coil are investigated. It is shown that modelling the coil as a boundary type is an optimized method, comparing to model the coil as a domain type.

In the development of aerodynamic-related products in the automotive manufacturing industry, evaluations must be fast and highly accurate with minimal deviation from the physical equations. On the other hand, Computational Fluid Dynamics and existing AI technologies had general problem with long processing time or low reliability of solution.

Therefore, in this study, we developed high-fidelity fluid prediction system based on Physics-Informed Graph Neural Network (PI-GNN), and design optimization system by using Multi-Objective Bayesian Optimization. We incorporated fluid equations into the loss function for consideration of physical equations when developing surrogate models. As a result, it was confirmed that the system enables highly accurate inference of fluid phenomena and fast optimization of the aerodynamic-related products.

The purpose of this paper is to build an estimation method of interior noise reduction effects due to structural changes during the early design stages at any position within the railway vehicle. We examined a model of a sound energy density propagation and proposed the model that considers both direct and diffuse sound. Additionally, we applied the proposed model to the floor section of a railway vehicle. As a result, we confirmed that the estimated values of the contribution rate about sound energy density decrease as the distance from the measurement point increases, indicating that the estimation results are qualitatively reasonable. Furthermore, it was confirmed that the cumulative contribution rate is approximately 75% outside the range of ±1m from the measurement point. This suggests that when the acoustic power of each element is comparable, the influence of sound propagating from the front and rear directions of the vehicle on the interior noise level cannot be ignored.

On the relationship between the waveguide shape and the vibration modes present in the waveguide, we solve a modal continuity equation. In the process, a virtual waveguide is assumed and solved. A virtual waveguide is defined based on numerical data calculated from the modal continuous equation. In addition, the existence of geometric mode distribution of vibration modes is defined, and it is confirmed that the virtual waveguides defined for each are the same. From the vibration analysis results by the finite element method, a mode continuous equation was created assuming the vibration mode, and it is consistent with the assumed vibration mode. In the actual mode, the assumed virtual waveguide was not realized, and it was confirmed that it was used as a tool for analyzing the waveguide

In this paper, in order to assist in quantitative evaluation when constructing an experimental SEA model, we first conduct the FEM calculations in numerical experiments to determine the large and small damping characteristics of a single flat steel plate structure. Then, using FEM and real experiments, we show the degree of variation in the FRF results and the SEA parameter results at five levels of input force from 1 N to 5 N. As a result, in the case of structure with large damping, it cannot be seen the influence of amplitude dependence of the FRF results. However, the results of the subsystem vibration energy normalized by the input power, which is a SEA parameter, showed the influence of amplitude dependence at relatively small input force. In the case of structures with small damping, the influence of amplitude dependence can be seen in the FRF results. The results of the subsystem vibration energy normalized by the input power showed that the results were more likely to vary due to the spatial averaging process of the number of input and response.

In the conceptual design of a sodium-cooled fast reactor system, structural integrity evaluation for various operating conditions is carried out for many components. The application of the optimization design is examined to find the shape with high design feasibility efficiently and at low cost. In this study, using a fin-tube heat transfer of an air heat exchanger (AHX) as an example, the Pareto solution which satisfies maximization of heat transfer area, minimization of pressure drops, and minimization of thermal stress was obtained by the multi-objective genetic algorithm NSGA-II. By comparison with the Monte Carlo calculation (MCS), it was confirmed that the Pareto solution by the multi-objective genetic algorithm NSGA-II corresponded to the boundary within the range of possible solutions. And it was possible to obtain the Pareto solution in a short time by using multi-objective genetic algorithm NSGA-II.

Drug-eluting stents (DES) have dramatically improved the early restenosis of conventional bare metal stents. However, several challenges remain in the long-term prognosis of DES, such as thrombosis, late restenosis, and hemorrhagic complications. In order to fundamentally improve the outcomes, it is essential to prevent restenosis and promote endothelialization by optimizing contact force in the early phase after implantation. In this study, a data map consisting of multidimensional data on stent shape variables, radial force, and physical properties of the vessel was constructed, and a design method for stents with the desired performance was developed by introducing boundary conditions corresponding to stent implantation.

The leg mechanisms affect the performance of the legged robots largely. Among various leg mechanisms, leg mechanisms employing one-degree-of-freedom link mechanisms are superior in terms of light weight and the ease of control. However, it is difficult to design link mechanisms analytically because of nonlinearity of the link mechanisms equation. Despite many methods have been proposed to overcome this problem, it is difficult to design link leg mechanisms using the existing methods. In our previous study, we developed a novel link mechanisms design method using single objective genetic algorithm, which could design proper link leg mechanisms. This paper shows that our method was improved in order to design more practical link leg mechanisms by using NSGA-II, a type of multi objective genetic algorithm, and by incorporating the two additional objectives: lifting the foot higher in swing phase and suppressing body rocking. The design results demonstrate that proposed method can design appropriate link leg mechanisms for various purposes.

Although various methodologies for numerical simulation of crack propagation have been developed to accurately predict fracture behavior in mechanical structures, the phase-field fracture (PFF) model is a powerful simulation methodology. The PFF model has the advantage in simulating complex crack path by introducing an auxiliary variable called the phase-field variable, which represents the fracture level at each coordinate. A crack propagation is simulated by minimizing the potential energy defined as a function of the phase-field variable. On the other hand, data assimilation methodologies based on Bayesian inference have been attracting attention to integrate measurement data into numerical simulations. This study proposes to implement the data assimilation methodology to the PFF model and validate the capability of proposed method to estimate model parameters included in the PFF model through numerical experiments.

In order to validate the accuracy of finite element nonlinear analysis, it is desired to analytically simulate standardized material tests and then compare the results with actual tests. As part of this effort, we aim to simulate the deformation and stress of a torsion test, which evaluates the shearing strength of a shaft. To do this, we model the test specimen as a round bar shaft using 3D solid elements, which lack rotational displacement degrees of freedom. In this study, we used Salome-Meca, including Code Aster, an open-source CAE software, to simulate a torsion test and discussed the issues involved.

This study proposes an efficient analysis method of shape optimization aimed at vibration suppression for structures with Maxwell-type viscoelastic dampers. A shape gradient function equivalent to the sensitivity function was derived using the adjoint variable method, and shape optimization was performed using the H1 gradient method. In calculating the shape gradient function, calculation costs were reduced by using the results of modal analysis of the frequency response and adjoint variables. An optimization system was constructed by combining a FEM software and a self-developed optimization program. Numerical analysis was conducted on a simple model, and the effectiveness of this method was confirmed by the analysis results.

In recent years, deep learning designed to adhere to physical laws, such as neural network models based on Hamiltonian and Lagrangian systems, has received significant attention. However, there have been few developments addressing cases with constraints. In this study, we consider a neural network learning model based on a physical system with existing holonomic constraints. We propose a novel deep learning method based on a Lagrange-Dirac system (an implicit Lagrangian system), whose geometric structure is defined by a Dirac structure on the cotangent bundle over a configuration manifold. It is noteworthy that such a Lagrange-Dirac system is applicable to physical systems with constraints. Our approach allows to consider mechanical systems with holonomic constraints, in which given training data comprising coordinates and velocities, the Lagrangian can be obtained the output by using the constraint force, momentum and its time derivative as teaching data. We demonstrate its validity through numerical experiments using the example of a double pendulum. The proposed deep learning approach shows that training data improves the accuracy of learning physical laws for holonomic mechanical systems.

This study investigates three spontaneous respiration modes and the possibility of abdominal distention. Therefore, the experiment will first examine the effect of MAP (Mean Airway Pressure) in a breathing mode that simulates healthy lungs in a neonatal spontaneous breathing simulator when two different air sources (compressor and SLE1000) are used, and then compare the characteristics of three different spontaneous breathing modes (Healthy lungs mode, Lung with increased airway resistance mode, Low compliance lungs mode) in PT-2 when MAP is constant to compare the characteristics of HNCPAP and NDPAP, respectively. The following results were obtained. In the breathing mode of healthy lungs, the likelihood of abdominal distention was very low regardless of the air source or device. Inhalation flow of both devices was similarly reduced by about 3/4 and 2/3 in the lungs with increased airway resistance and low compliance, respectively, based on the healthy lung case, and was dependent on the breathing mode regardless of the device used. In the case of low NDPAP compliance, about 1/3 of the inhalation flow of a healthy lung was added to the counterflow and overlapped with the vortex train generated by the (K-H) instability, resulting in a free jet with increased instability that persisted until the end of inhalation. The direct interference between the free jet and the reverse flow near the inspiratory airway pressure measurement hole caused intermittent leakage into the airway, resulting in abdominal distention.

In this study, the flows of aqueous glycerin solution in a venous chamber are numerically investigated. Inflow types for commercially available venous chambers are mostly limited to horizontal and vertical types, and there seems to be no venous chambers which the fluid flows into at an angle. In this study, we performed a set of LES simulations to evaluate the effect of inflow angle on the flow field in the venous chamber, where the following three inflow angles are chosen: horizontal (0°), 45°-downward, and 45°-upward. Results are shown in terms of streamlines, mean velocity, and turbulence statistics. It was found from the results that the magnitude of velocity for the 45°-downward case was the largest in the lower half of the chamber compared to those for the horizontal (0°) and 45°-upward cases. Also, the axial turbulence intensity for the 45°-downward case are relatively larger than the other cases in mostly entire region in the chamber.

This study aimed to develop a simple artificial atrioventricular valve with bi-cusps using a collagen tissue sheet (Biosheet) obtained by in-body tissue architecture. Because of the longer time required to fabricate Biosheets, we have been investigating the influence of valvular shape on performance by fabricating modelled valves using polyurethane sheets with mechanical properties that match those of the Biosheet and performing an in-vitro flow simulator. Our previous study showed that the regurgitation performance of our designed bicuspid atrioventricular valve prostheses could not be satisfied with clinical criteria. We evaluated the valve performance for our valve model and visualized the flow field around the closing valvular cups using an in-vitro flow simulator simultaneously. The experimental result showed that the geometrical size of our developed atrioventricular valve model did not affect the closing volume of the regurgitant flow and affected the length of the cuspid free edge.