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Record W4285360284 · doi:10.46720/f2020-mcf-004

One Way Coupled FSI Analysis to Design the Restricted Intake Manifold for a Single Cylinder SI Engine

2021· article· en· W4285360284 on OpenAlexaboutno aff
Nafees Ahmad, Mehul Varshney, Mohammad Haani Farooqi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInlet manifoldPlenum spaceComputational fluid dynamicsMechanicsPressure dropThrottleTurbulenceTorqueExhaust manifoldCylinderMechanical engineeringComputer scienceEngineeringPhysicsInternal combustion engine

Abstract

fetched live from OpenAlex

"Interactions between fluids and structures occur in a wide range of engineering problems. The solutions to these problems are based on the relationship with continuum mechanics, and mostly these problems are solved with the help of numerical methods. Due to complex geometries, fluid physics, and fluid-structure interactions, addressing such issues is a computational challenge. The geometrical design of an air intake manifold is essential for the excellent performance of the IC engine. As per the SAE rule, the air intake manifold of the gasoline-fueled car should have a circular restriction of 20 mm, limiting the power of the engine. This research work aims to design an intake system that compensates for the power loss to the maximum extent and reduces the engine noise of the intake for the single-cylinder Honda CBR 250R engine. A 3D model of the actual manifold is designed to modify the intake manifold. With that geometry, Computational Fluid Dynamics (CFD) simulations were performed to optimize each section, including De Laval Nozzle, plenum, and runner, in such a way that there will be minimal pressure drop during the airflow. The flow was modeled as steady, Newtonian, and Incompressible. Continuity and Momentum conservation equations and the k-epsilon turbulence model were solved to obtain mean flow characteristics. Then, Lotus Engine Simulation software was used to optimize the size of the plenum to get the maximum power at higher RPM and maximum torque at lower RPM to enhance the performance of the car on the racing track. The runner length is tuned with the help of the Acoustics and Induction system theory to provide the ram effect in the naturally aspirated engine to achieve maximum volumetric efficiency. The exact injector position and fuel injection angle were decided by Prototype testing for proper air-fuel mixing. Finite Element Analysis (FEA) has been performed to determine the thickness and type of material for the manifold manufacturing to bear the backfire condition (pressure generated up to 3 bar) due to mistimed spark event during the frequent racing. The Formula SAE is an abstraction of the Automotive industry with more than 600 Formula Student combustion teams worldwide. The students face difficulty designing as there is a dearth of literature that systematically walks them through the designing steps. This research work walks the students chronologically by developing an optimized intake manifold."

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.765
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.255
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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