Dr jadidi fluent-basic-m03

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Mohammad Jadidi

Goal: In these power point presentations, the basics of applied CFD simulation in the industry using powerful ANSYS-FLUENT software is presented.

ANSYS Fluent (basic)
Module 03
Instructor:
Dr. Mohammad Jadidi
(Ph.D. in Mechanical Engineering)

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Instructor: Dr. Mohammad Jadidi

Thanks
Jadidi.cfd@gmail.com
Dr. Mohammad Jadidi
(Postdoctoral in Mechanical Engineering)
End of Module 03 Next part:
ANSYS Fluent (basic)

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Slides from talk presenting: Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking. Presentation at IcETRAN 2024 session: "Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation" IEEE Slovenia GRSS IEEE Serbia and Montenegro MTT-S IEEE Slovenia CIS 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING 3-6 June 2024, Niš, Serbia

CSM Cloud Service Management Presentarion

CSM Cloud Service Management Presentarion

CSM Cloud Service Management Presentarion

官方认证美国密歇根州立大学毕业证学位证书原版一模一样

官方认证美国密歇根州立大学毕业证学位证书原版一模一样

官方认证美国密歇根州立大学毕业证学位证书原版一模一样

原版一模一样【微信：741003700 】【美国密歇根州立大学毕业证学位证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma 1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700 留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

Electric vehicle and photovoltaic advanced roles in enhancing the financial p...

Electric vehicle and photovoltaic advanced roles in enhancing the financial p...

Electric vehicle and photovoltaic advanced roles in enhancing the financial p...

Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network

Iron and Steel Technology Roadmap - Towards more sustainable steelmaking.pdf

Iron and Steel Technology Roadmap - Towards more sustainable steelmaking.pdf

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Understanding Inductive Bias in Machine Learning

Understanding Inductive Bias in Machine Learning

Understanding Inductive Bias in Machine Learning

This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models. The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees. By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.

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DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL

As digital technology becomes more deeply embedded in power systems, protecting the communication networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3) represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities. Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network (CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to train and test our model. The results of our experiments show that our CNN-LSTM method is much better at finding smart grid intrusions than other deep learning algorithms used for classification. In addition, our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection accuracy rate of 99.50%.

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Dr jadidi fluent-basic-m03

1. ANSYS Fluent (basic) Module 03 Instructor: Dr. Mohammad Jadidi (Ph.D. in Mechanical Engineering)

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54. Thanks Jadidi.cfd@gmail.com Dr. Mohammad Jadidi (Postdoctoral in Mechanical Engineering) End of Module 03 Next part: ANSYS Fluent (basic)