Project

# Title Team Members TA Documents Sponsor
43 Digital Twin Bridge Monitoring System
 Hanchi Ge
Kowshik Dey
Rongjian Chen
 design_document1.pdf
design_document2.pdf
final_paper1.pdf
final_paper2.pdf
proposal2.pdf
video1.mp4
 Simon Hu
**Project Advisor:**
Dr. Cristoforo Demartino

**Team Members:**
- Kowshik Arko Dey [arkod2]
- Hanchi Ge [hanchig2]
- Rongjian Chen [rc21]

**Problem:**
Bridges are one of the most vital infrastructures that serve as connectors both inside and outside of a country. They facilitate the movement of people, goods, and vehicles. Despite being marvels of engineering and architecture, accidents in bridges have become more frequent as time passes. The significant causes can be attributed to as being vehicle overloading and structural concerns of the bridge. These type of accidents are more prominent in third world countries, like Bangladesh, where most of the bridges have no monitoring system due to the cost involving these traditional monitoring systems. As a result, the drivers are left to their own assessments and judgements which may lead to accidents and structural damage to the bridges. The development of digital monitoring system can effectively save the money wasted on repetitive maintenance and repair of bridges due to overloading and structural damage.

**Solution Overview:**
The Digital Twin Bridge Monitoring System is designed to address the critical issue of bridge safety and maintenance. This innovative system involves the creation of a digital counterpart for a physical bridge, which is outfitted with advanced pressure sensors. These sensors are crucial for accurately gauging the weight of vehicles as they traverse the bridge, ensuring that the bridge's load capacity is not exceeded. Additionally, the system is equipped with a traffic light mechanism. This feature plays a vital role in warning drivers about potential overloading or existing structural issues, thereby enhancing safety measures.

To demonstrate the practicality and functionality of this system, we plan to construct a scaled-down prototype model. This model will serve as a platform for installing our hardware components, which include various modules such as sensors and a micro-controller. The key to our system's effectiveness lies in the ability to transmit the sensor's processed data to the digital twin platform. This enables the real-time monitoring and detection of the bridge's condition, allowing for immediate responses to any detected problems. Through this advanced monitoring system, we aim to revolutionize how bridge safety is managed, ensuring the longevity and reliability of these critical infrastructures.

**Solution Components:**

*Pressure Sensor Subsystem Overview*
The Sensor Subsystem is strategically designed for early detection of potential risks posed by overweight vehicles. Situated in every lane at the initial incline of the bridge, pressure sensors are meticulously installed. Their primary role is to identify vehicles exceeding the weight limit. Upon detection, the traffic light will show red.

*Displacement Subsystem Overview*
Displacement sensors are used to measure the displacement of a bridge structure, which is critical for us to assess the structural safety of a bridge. Displacement sensors will be strategically placed at key points in the bridge structure, such as supports, beams and joints, to ensure we can fully monitor the health of the bridge.

*Processing Subsystem Details*
The operation of the Processing Subsystem is pivotal for maintaining traffic flow and ensuring safety. Under standard operational circumstances, the traffic signal lights are set to green, allowing vehicles to pass. However, the system is on constant alert for overweight vehicles. The moment an overweight vehicle is identified, the traffic lights switch to flashing red, serving as a clear warning to drivers to halt and not to enter the bridge. Further, should there be any detected structural deformation within the bridge, the signal lights will steadfastly remain red. Moreover, to prevent any approach towards the potentially unsafe bridge, all traffic lights leading to it from the preceding intersection will be deactivated.

The heart of this subsystem is an internal micro-controller responsible for Analog-to-Digital (A/D) conversion and the initial stages of signal processing.

- **Signal Conditioning:** The raw signals from the sensors are often weak and noisy. Signal conditioning modules are used to amplify, filter, and convert these signals into a format suitable for digital processing.
- **Analog-to-Digital Conversion (ADC):** The conditioned analog signals are converted into digital data through ADC. This conversion is essential for the subsequent data analysis and digital twin simulation.
- **Data Processing Unit:** A micro-controller processes the digital data, performing preliminary calculations and data compression to reduce the amount of data to be transmitted.
- **Data Transmission:** The processed data is transmitted to the Digital twin software.

*Power Subsystem Functionality*
It efficiently converts AC power, commonly available from standard outlet sources, into the DC voltages required by the various components of the system. This includes the sensors, micro-controller, and communications modules, thereby guaranteeing their uninterrupted operation and performance.

**Criterion for Success:**
Successful development and integration of the scaled physical model, software, and hardware components. The scale model can use pressure sensors to measure the weight of the passing model car, and when the weight of the car exceeds our preset standard, the signal light of the scale bridge will be red to warn the driver. At the same time, the

signals obtained from the scale model, such as pressure signals and structural deformation signals of the bridge, need to be transmitted in real time to the digital twin monitoring system. Comprehensive documentation of the project's design, implementation, and testing process.

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Augmented Reality and Virtual Reality for Electromagnetics Education

Zhanyu Feng, Zhewen Fu, Han Hua, Daosen Sun

Featured Project

# PROBLEM

Many students found electromagnetics a difficult subject to master partly because electromagnetic waves are difficult to visualize directly using our own eyes. Thus, it becomes a mathematical abstract that heavily relies upon mathematical formulations.

# SOLUTION OVERVIEW

We focus on using AR/VR technology for large-scale, complex, and interactive visualization for the electromagnetic waves. To speed up the calculation, we are going to compute the field responses and render the fields out in real-time probably accelerated by GPU computing, cluster computation, and other more advanced numerical algorithms. Besides, we propose to perform public, immersive, and interactive education to users. We plan to use the existing VR equipment, VR square at laboratory building D220 to present users with a wide range of field of view, high-resolution, and high-quality 3D stereoscopic images, making the virtual environment perfectly comparable to the real world. Users can work together and interact with each other while maneuvering the virtual objects. This project also set up the basis for us to develop digital-twins technology for electromagnetics that effectively links the real world with digital space.

# COMPONENTS

1.Numerical computation component: The part that responsible for computing the field lines via Maxwell equations. We will try to load the work on the GPU to get better performance.

2.Graphic rendering component: The part will receive data from the numerical computation component and use renderers to visualize the data.

3.User interface component: This part can process users’ actions and allow the users to interact with objects in the virtual world.

4.Audio component: This part will generate audio based on the electromagnetic fields on charged objects.

5.Haptic component: This part will interact with the controller to send vibration feedback to users based on the field strength.

# CRITERIA OF SUCCESS

Set up four distinct experiments to illustrate the concept of four Maxwell equations. Students can work together and use controllers to set up different types of charged objects and operate the orientation/position of them. Students can see both static and real-time electromagnetic fields around charged objects via VR devices. Achieve high frame rates in the virtual world and fasten the process of computation and using advanced algorithms to get smooth electromagnetic fields.

# WHAT MAKES OUR PROJECT UNIQUE

We will build four distinct scenarios based on four Maxwell Equations rather than the one Gaussian’s Law made by UIUC team. In these scenarios, we will render both electric and magnetic field lines around charged objects, as well as the forces between them.

The experiments allow users to interact with objects simultaneously. In other words, users can cooperate with each other while conducting experiments. While the lab scene made by UIUC team only allows one user to do the experiment alone, we offer the chance to make the experiment public and allow multiple users to engage in the experiments.

We will use different hardware to do the computation. Rather than based on CPU, we will parallelize the calculation and using GPU to improve the performance and simulate large-scale visualization for the fields to meet the multi-users needs.

Compared to the project in the UIUC, we will not only try to visualize the fields, but also expand the dimension that we can perceive the phenomena i.e., adding haptic feedback in the game and also using audio feedback to give users 4D experience.