Role: Simulation and Analysis
Project description:
Design and build a robot to maneuver through an obstacle course of rocks and pits into a construction zone. The robot must construct a berm within a designated area within this zone.
Project solution:
For this competition, we first set a goal for how our robot would compete. We decided to build a robot capable of carrying a large amount of regolith in a single excavation cycle. We set the regolith amount at 50 kg to beat previous records and create a greater challenge for our design. This 50 kg goal created a weight problem because it required a sturdy drivetrain and chassis, which would further increase the robot's weight. We assumed a maximum robot weight, which required us to design for a total weight of 125 kg. We conducted a trade study to meet these goals, which led us to design a robot with a grouser-wheel drivetrain and a bucket-ladder excavation system.
This weight required extensive static and dynamic analysis in ANSYS. The main threats to the robot were the grousers, wheel mounts, and motor mounts. We applied a 2.25 FOS to the components, assuming a wheel would take double the load. This assumption is necessary because the BP1 simulant is finer than sand, which could cause contact loss when driving on non-compacted terrain.
Analysis was primarily conducted using Ansys. Structural analysis under cyclic loading was performed on the excavation and drivetrain to ensure the design's reliability. Load paths were determined to prevent any bending or shearing in the chassis. This load path also enabled a more accurate analysis of the forces applied to the grousers and wheel mount. Analysis of the wheels was also conducted through the use of LS Prepost. An SPH model was designed using a Tabulated compaction equation of state with a Mohr-Coulomb criterion. Unfortunately, we could not use this model during our design phase. However, the estimated sinkage was accurate to our competition runs and will be useful to our future teams.
Robot SolidWorks Model
Fully Assembled Robot
LS Prepost SPH Model (mm)
Project description:
This club consists of an engineering team that designs, manufactures, and races an electric vehicle in an FSAE EV competition. My position in this club was with the Vehicle Dynamics team.
As part of the Vehicle Dynamics team, we aim to save as much time on our laps as possible while extending our endurance in races. This was possible by gathering data on the current vehicles’ performance to compare with our simulation software, Optimum Lap. This program enabled us to observe the impact that modifications to the vehicle could have on the car. While improving the vehicle's efficiency was important, we also needed to consider the effort required to alter the sections, along with the safety factors already in place.
My time in the Dynamics team focused on assisting the chassis and drive train team in determining modifications that could be made to the vehicle. A redesign of our mount was created to reduce the vehicle's overall weight, thereby improving its handling in turns and acceleration, which contributed to a slight decrease in our time. Multiple changes were made to the design with analysis produced through Ansys to ensure it will be reliable.
Project solution:
As part of the Vehicle Dynamics team, we aim to save as much time on our laps as possible while extending our endurance in races. This was possible by gathering data on the current vehicles’ performance to compare with our simulation software, Optimum Lap. This program enabled us to observe the impact that modifications to the vehicle could have on the car.
The final form of assistance was helping the chassis team through structural analysis, which made my role in the dynamics team more efficient. I also focused on component redesigns that would reduce vehicle weight.
Mount Stress Analysis
Optimum Lap Speed per Distance Graph
Optimum Lap Vehicle Speed Performance Test
Project description:
This project compares two TPMS forms: I-WP and Schwartz Primitive. These configurations are similar in stiffness and thermal conductivity, making them suitable for comparison. The goal is to identify which of the two forms would survive a 0.5-meter drop.
Project solution:
The simulations were conducted in Ansys, using polyurea material properties. Hyperelastic simulations employed the 3rd-order Ogden model, based on the Helmholtz free energy. Quasistatic and Viscoelastic drop test simulations were generated. Little compression is expected in the simulations due to the material's Poisson’s ratio of 0.486.
Simulated data was compared to a theoretical set generated using the Boltzmann superposition principle and Prony series to determine the relaxation modulus. The overall project provided a valuable experience in various methods of drop test analysis. Utilizing initial contact methods allowed the simulations to skip hours of processing.
Project description:
The goal of this project was to design an EUV droplet generator with characteristics similar to those of ASML plants. The design was made to produce 50,000 droplets/second with a velocity of 70 m/s, utilizing molten tin and argon gas. A two-phase flow analysis is conducted using hand calculations and Ansys to confirm the design.
Project solution:
A droplet generator using the model designed is expected to produce the set goals when a pressure of 38 MPa of Argon gas is applied to the tin reservoir. This is confirmed by a hand calculation using the Navier-Stokes equation, along with the necessary pressure increases (Darcy-Weisbach equation), which yields a 3% difference.
This project provided experience with FEA through both manual calculations and software. Both Ansys Fluent and Comsol were used in this project, with Comsol used to perform an initial laminar single-phase test. While Ansys was able to produce a turbulent dual-phase flow test.
(A) Design
(B) Droplet Requirements
Single Phase FEA (Comsol, Velocity)
Dual Phase FEA (ANSYS, Volume)
Dual Phase FEA (Ansys, Velocity)