With the development of machine learning, numerical analysis using neural networks has been devised. Remarkably, physics-informed neural networks (PINNs) enable physically consistent numerical analysis by introducing ...
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ISBN:
(数字)9798350373332
ISBN:
(纸本)9798350373349
With the development of machine learning, numerical analysis using neural networks has been devised. Remarkably, physics-informed neural networks (PINNs) enable physically consistent numerical analysis by introducing a loss function that conforms to relevant governing equations. Moreover, research is rapidly advancing for the application of PINNs to inverse analysis in areas such as physical property identification. For a PINN to learn governing equations, the weights of the loss functions should be properly determined because they have different roles in components such as boundary conditions, initial conditions, and governing equations. However, weight setting is generally challenging. We propose a loss balancing method considering the procedure for solving partial differential equations. The proposed method is validated through comparisons with conventional solvers.
Poly (methyl methacrylate) (PMMA), which is suitable for use in the human body owing to its biocompatibility, is commonly used in medical applications such as bone nails, bone cement, and dentures. However, owing to i...
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Crawler cranes are used in various applications, including plant construction and civil engineering. However, accidents caused by hazardous events, such as overturning the entire body or overshadowing of a suspended l...
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ISBN:
(数字)9798350373332
ISBN:
(纸本)9798350373349
Crawler cranes are used in various applications, including plant construction and civil engineering. However, accidents caused by hazardous events, such as overturning the entire body or overshadowing of a suspended load, can be problematic. Because crawler cranes are large and powerful machines, simulators are required to analyze the relationship between such hazardous events and human operations. This study proposed a framework for a mixed-reality simulator to analyze the interactions between humans and crawler cranes. This framework combined the high-performance graphics capabilities of Unreal Engine 5 with the high-precision multibody dynamics analysis of MATLAB Simscape to create a visually and physically realistic simulation. Moreover, the quantification of the decision-making process was possible based on the eye-tracking information of the operator. This study described the implementation of these features and discussed the prospects for human-crawler crane interaction analysis using this simulator.
This study was performed to verify the feasibility of using a black ice danger area estimation function based on the wetness data acquired by a piezoelectric based RCS (Road Condition Sensor) through real road tests u...
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In tissue engineering, the mechanical properties of the extracellular matrix (ECM) or scaffolds have increasingly been considered to impact therapeutic efficacy by regulating cell behaviors, including differentiation,...
In tissue engineering, the mechanical properties of the extracellular matrix (ECM) or scaffolds have increasingly been considered to impact therapeutic efficacy by regulating cell behaviors, including differentiation, proliferation, migration, and adhesion. However, the understanding of how cells sense, integrate, and convert the mechanical cues from the ECM cues into biochemical signals to control certain cell behaviors is still elusive, especially in 3D, which more closely mimics the natural microenvironment than 2D systems. This review highlights the key differences between 2 and 3D in the contexts of mechanoregulative cell behaviors such as cell adhesion, spreading, migration, and force transmission. Furthermore, critical designing factors that needs to be considered for the fabrication of 3D tissue engineering scaffolds is discussed: stiffness, viscoelasticity, degradability, and the immobilization of biomolecules. Although mechanotransduction in 3D is actively being studied, understanding cellular mechanotransduction in 3D and designing of mechanoregulative 3D scaffolds still presents several challenges, including varying mechanical properties depending on different tissues, dynamic mechanical environments, and integration of multimodal cues. Interdisciplinary methodologies encompassing material engineering, cell biology, and mechanicalengineering would serve to mitigate these challenges and augment our understanding of mechanoregulation governing cellular behaviors, thus fostering advancements in biomedical applications in the future.
A high-performance indium tin oxide (ITO) coating is key in fabricating an efficient photosensor. The manufacturing process of ITO is complex and time-consuming. Therefore, establishing a production technology that is...
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Fuel surrogates are mixtures of simple compounds that emulate the combustion characteristics of more complex fuels, with the primary objective to enable detailed combustion modeling of very complex real fuels. Current...
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Fuel surrogates are mixtures of simple compounds that emulate the combustion characteristics of more complex fuels, with the primary objective to enable detailed combustion modeling of very complex real fuels. Current efforts in surrogate development aim to optimize the compositions of pure hydrocarbons to emulate multiple combustion related properties. In doing so, weights are assigned when defining optimization problem to reflect the importance of each property. In this study, the impact of surrogate component selection and weight assignment on surrogate formulations was quantitatively investigated by analyzing their sensitivities during the surrogate optimization. Using experimental data of a reference jet fuel as target, a study was designed using a surrogate optimizer that imposes orthogonal perturbations on the surrogate components and weights, and their effect on the optimized surrogate mixtures was analyzed. Results from 3600 cases revealed that perturbations of surrogate components, rather than weights, induce far greater variability in the optimized composition and target property agreement. While the derived cetane number (DCN) agreement showed a greater variability from the weight perturbation, the main reason for such high sensitivity was due to the wide range of values for pure component DCN of the individual components, which was also a result of the surrogate component selection. The results also demonstrated that the selection of surrogate components nearly predefines the overall shape of the distillation curves regardless of the weight values. This study quantitatively supports the idea that appropriate selection of surrogate components that capture the physical and chemical characteristics of actual constituents of target fuel will increase the possibility of successful surrogate formulation and will mitigate the impact from arbitrary weight assignment.
Pitch-type wave energy converters (e.g., Salter’s duck-type wave energy converter [WEC] rotor) have been proven to work effectively in 2D. However, only a few studies have investigated the 3D nonlinear effects. Large...
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The oil refinery industry has a potential emission reduction by combining its fossil fuel with Renewable Energy usage. One alternative to reduce carbon emissions is the hybrid power system using solar panels for elect...
The oil refinery industry has a potential emission reduction by combining its fossil fuel with Renewable Energy usage. One alternative to reduce carbon emissions is the hybrid power system using solar panels for electricity generation. This research will observe the optimum scenario for utilizing a hybrid power system. The research subject is observed refinery facilities that will be built in Indonesia, where the electricity source used formerly comes from fossils. The monitored parameters are Cost of Energy (COE) and carbon emission. optimization involves three scenarios involving basic and hybrid configurations. The basic scenario is the initial configuration of the electricity supply with power source from the generator and PLN (national’s utility). The first scenario is a hybrid power plant utilizing the roofs of existing buildings in the refinery area. The second is a hybrid power plant with a battery to supply electricity at night, at the capacity of renewable energy (RE) of 20% and 40%. Compared to the basic scenario, scenario 1 increases COE by 0.17% and reduces carbon emission at 0.3% compared to the basic scenario. Scenario 2 with 20% and 40% of renewable energy are obtained at COE of 4.7% and 44.3%, while reducing emissions occurred at 38% and 52.7%, respectively. The scenario of a hybrid power system with a 20% renewable energy is the optimal result compared to the other scenarios.
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