<p dir="ltr">The United States government and Environmental Protection Agency have mandated that vehicles must meet 54.5 miles per gallon(<i>07/29/2011: President Obama Announces Historic 54.5 Mpg Fuel Efficiency Standard/Consumers Will Save $1.7 Trillion at the Pump, $8K per Vehicle by 2025</i>, n.d.). Faced with increased governmental regulations, manufacturers must find new ways to improve their internal combustion engines. Examining the various components of internal combustion engines, there is potential to optimize individual components for mass reduction and thus improving vehicle performance. Engine Components, specifically connecting rods, are essential to the operation of an engine. While connecting rod designs are highly refined, breakthroughs in additive manufacturing technology have given way to novel approaches in the optimization process. Autodesk Inc. has provided an innovative, generative design space to reduce design time and explore complex optimization. The generative design process provides engineers with unique designs while considering many parameters including material, load cases, and manufacturing processes. The study applied generative design structural load casing to a connecting rod of a single cylinder Ryobi engine to optimize for metal additive manufacturing. The generated outcomes were subjected to finite element analysis to determine their feasibility against a traditional drop forged or die cast design. The results compared three generated geometries against three common additive manufacturing materials in ANSYS Mechanical. The generated geometries were tested for equivalent (Von Mises) stress, equivalent strain, and total deformation. The study, using preliminary forces in a static situation, found that mass reductions of up to 19% were achievable while maintaining performance capabilities of the original design.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/24749493 |
| Date | 06 December 2023 |
| Creators | Cole Lewis Parsons (14824315) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/GENERATIVE_DESIGN_OPTIMIZATION_OF_CONNECTING_RODS/24749493 |
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