Multi-Scale Modeling of Melt Pool Formation and Solidification in Powder Bed Fusion: A Fully Coupled Computational Fluid Dynamics-Extended Discrete Element Method Approach

Aminnia, Navid; Peters, Bernhard; Estupinan, A.

doi:10.2139/ssrn.4502227

Cited by 4 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Before the oil crisis of the 1970s, significant people were only mindful of the easy use of cars and convenience, and no one thought about pollution and fuel consumption [2,3,[6][7][8][9]. In recent years, air pollution has become one of the significant problems in the world, causing the pollution of cars to be limited and making its control a significant issue in the policy of car manufacturers [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the mean effective pressure of a spark ignition internal combustion engine using a neural network, considering the wall-wetting dynamics

Mahnaz Zameni,

Mahdi Ahmadi,

Arash Talebi

2024

Global J. Eng. Technol. Adv.

View full text Add to dashboard Cite

The management and development of internal combustion engines stand as critical pursuits within the automotive and related industries. Utilizing cylinder pressure as feedback, engine controllers rely on intricate systems to regulate performance. However, due to the inherent complexity and nonlinearity of engines, direct measurement of cylinder pressure through pressure sensors is costly and computationally demanding. Consequently, the need for accurate and detailed engine models becomes paramount. Neural networks offer a promising avenue for simulating internal combustion engines, combining speed and precision. By treating the engine as an enigmatic entity, neural networks can construct detailed models. This study aims to employ two types of neural networks—multilayer perceptron and radial basis functions—to train and build a model of an internal combustion engine. These networks will simulate and estimate the engine's mean suitable pressure, allowing for a comparison of their effectiveness. Prior to implementing the neural network architecture, an engine model was constructed in MATLAB to gather necessary training data. This preliminary step ensured a robust foundation for subsequent network design and implementation. In summary, this research focuses on leveraging neural networks to model internal combustion engines, utilizing both multilayer perceptron and radial basis functions to simulate engine behavior and estimate mean suitable pressure.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimation of the mean effective pressure of a spark ignition internal combustion engine using a neural network, considering the wall-wetting dynamics

Mahnaz Zameni,

Mahdi Ahmadi,

Arash Talebi

2024

Global J. Eng. Technol. Adv.

View full text Add to dashboard Cite

show abstract

“…Reducing the quantity of fuel that is used and the amount of pollutants that are created may be accomplished via the management of the engine in a number of different methods, including modification [6][7][8][9][10][11]. In the event that you are in possession of a certain model of the engine, this procedure will be much less complicated, which will lead to a decrease in the amount of money that is necessary.…”

Section: Introductionmentioning

confidence: 99%

Creating a neural network-based model to predict the exhaust gas temperature of the internal combustion engine

Mahnaz Zameni,

Mahdi Ahmadi,

Arash Talebi

2024

GSC Adv. Res. Rev.

View full text Add to dashboard Cite

The regulation and improvement of the performance of internal combustion engines is a continual primary focus of research and development activities conducted within the automobile industry and other relevant sectors. To succeed in reaching this objective, it is necessary to have an accurate and complete model of these engines. However, due to internal combustion engines' complex and nonlinear nature, accurately replicating their behavior may be challenging and time-consuming. Neural networks are a potentially useful strategy for simulating these engines successfully since they offer a solution that strikes a healthy balance between speed and precision. This research investigates the process of building a model of an internal combustion engine by using not one but two separate kinds of neural networks: multilayer perceptrons and radial basis functions. These neural networks aim to simulate and make predictions about the temperature of the engine's exhaust gas. They are especially useful for modeling nonlinear systems because of their incredible convergence speed and excellent accuracy levels.

show abstract

“…In situations where the hot press is not available, one must resort to the conventional method of compression and sintering, which, as mentioned earlier, requires extensive preliminary work [49,50]. This can be particularly demanding, especially in scenarios involving low-volume production [36,[51][52][53][54].…”

Section: Introductionmentioning

confidence: 99%

Laboratory preparation of LSM and LSF sputtering targets using PTFE rings for deposition of SOFC thin film electrodes

Ramin Babazadeh Dizaj,

Nastaran Sabahi

2023

World J. Adv. Eng. Technol. Sci.

View full text Add to dashboard Cite

The manufacturing of sputtering targets diverges from the conventional methods in ceramic processing, primarily because the quantities produced are frequently limited. The application of hot-press in this scenario significantly simplifies the sputter target fabrication process, allowing precise control over both target density and dimensions during pressing. However, without a hot press, the fabrication necessitates substantial preliminary efforts, which may be challenging to justify due to the restricted production volume. This study utilizes polytetrafluoroethylene (PTFE) rings as compaction dies filled with powders. Subsequently, the die is deformed between parallel platens, effectively compacting the powders. The method relies on the characteristic that the pressing results in minimal change in the internal diameter of the ring. This approach was exemplified through the creation of 2-inch (La0.5Sr0.5) MnO3-δ (LSM) and (La0.8Sr0.2) FeO3-δ (LSF) targets, where the deformable die was sized based on preliminary experiments involving smaller-diameter PTFE rings. The outcome of this fabrication process successfully produced sputter targets with high density, well within the tolerances of the sputter gun. Further tests involved using the prepared targets for the successful deposition of thin film LSM-LSF composite cathodes for SOFC applications.

show abstract

Multi-Scale Modeling of Melt Pool Formation and Solidification in Powder Bed Fusion: A Fully Coupled Computational Fluid Dynamics-Extended Discrete Element Method Approach

Cited by 4 publications

References 0 publications

Estimation of the mean effective pressure of a spark ignition internal combustion engine using a neural network, considering the wall-wetting dynamics

Estimation of the mean effective pressure of a spark ignition internal combustion engine using a neural network, considering the wall-wetting dynamics

Creating a neural network-based model to predict the exhaust gas temperature of the internal combustion engine

Laboratory preparation of LSM and LSF sputtering targets using PTFE rings for deposition of SOFC thin film electrodes

Contact Info

Product

Resources

About