Structural analysis and topology optimisation of an aftercooler cover for weight reduction in off-highway engine application

Space travel has always been a crucial task. Exploration and experimenting on Planets in our solar system will help us understand the universe better and also, we could find the origin of life. Rovers play an important role in finding these answers. The problem we have at present is not only with technology to explore the universe but also the ability of our rockets to carry rovers to other rocks. Since a large amount of fuel is required for Space travel, we end with very little cargo that can be sent to explore. As additive manufacturing started to play a vital part in Mechanical Science, we are going to try to use that tool to build a Generative design that helps in parts consolidation, weight reduction, increase flexibility, design optimisation and cost consolidation. Since weight is an important aspect, we could reduce the present rover weight and add additional scientific tools to the rover to increase its scope of search and applications. This project focuses on features enrichment in Rovers by optimizing rover weight and design using Design for Additive Manufacturing concept.

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Physarum computing and topology optimisation

International Journal of Parallel Emergent and Distributed Systems ◽

10.1080/17445760.2016.1221073 ◽

2016 ◽

Vol 32 (5) ◽

pp. 448-465 ◽

Cited By ~ 4

Author(s):

Alexander Safonov ◽

Jeff Jones

Keyword(s):

Topology Optimisation ◽

And Topology

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Strength Assessment of Fan Blade with Different Materials

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst196138 ◽

2019 ◽

pp. 266-283

Author(s):

Polyminna Dileep ◽

C. Mohan Naidu

Keyword(s):

Structural Analysis ◽

Weight Reduction ◽

Fuel Efficiency ◽

Aircraft Engine ◽

Sandwich Composite ◽

Strength Assessment ◽

Static And Dynamic Analysis ◽

Composite Blade ◽

Aero Engine ◽

Fan Blade

Weight reduction of turbofan engines is one of the main concerns of aero engine manufacturers in order to cut fuel burn. To achieve higher fuel efficiency, aero engine manufacturers develop turbofans with higher bypass ratio, which can only be achieved with larger (and heavier) fan sections. This makes weight reduction in fan components a major consideration and becomes a key driver for the use of composite materials in future engines. The objective of this project is to design, perform structural analysis and optimization of a Composite fan blade. Development of a fan blade is comparable to a future large aircraft engine fan blade. This thesis is about the structural analysis of a composite fan blade with a honeycomb sandwich construction with a polymer matrix composite and honeycomb Aluminium core compared with baseline solid basic fan blade made of titanium. The focus of this work is to design the sandwich composite blade with honeycomb core and conduct static and dynamic analysis.

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Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4044097 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 6

Author(s):

Zhenguo Nie ◽

Haoliang Jiang ◽

Levent Burak Kara

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Topology Optimization ◽

Structural Analysis ◽

Stress Field ◽

Convolutional Neural Networks ◽

Von Mises Stress ◽

Channel Network ◽

Promising Alternative ◽

And Topology

Abstract The demand for fast and accurate structural analysis is becoming increasingly more prevalent with the advance of generative design and topology optimization technologies. As one step toward accelerating structural analysis, this work explores a deep learning-based approach for predicting the stress fields in 2D linear elastic cantilevered structures subjected to external static loads at its free end using convolutional neural networks (CNNs). Two different architectures are implemented that take as input the structure geometry, external loads, and displacement boundary conditions, and output the predicted von Mises stress field. The first is a single input channel network called SCSNet as the baseline architecture, and the second is the multichannel input network called StressNet. Accuracy analysis shows that StressNet results in significantly lower prediction errors than SCSNet on three loss functions, with a mean relative error of 2.04% for testing. These results suggest that deep learning models may offer a promising alternative to classical methods in structural design and topology optimization. Code and dataset are available.2

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WEIGHT REDUCTION OF A DIFFERENTIAL CASE AND ITS STATIC STRUCTURAL ANALYSIS

10.37099/mtu.dc.etdr/808 ◽

2019 ◽

Author(s):

Konark Dhananjay Kumbhalkar

Keyword(s):

Structural Analysis ◽

Weight Reduction

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Development of a patient-specific immobilisation facemask for radiation therapy using additive manufacturing, pressure sensors and topology optimisation

Rapid Prototyping Journal ◽

10.1108/rpj-09-2021-0241 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Amirhossein Asfia ◽

James I. Novak ◽

Bernard Rolfe ◽

Tomas Kron

Keyword(s):

Additive Manufacturing ◽

Head Movement ◽

Pressure Sensors ◽

Sensor Data ◽

Patient Specific ◽

Topology Optimisation ◽

Content Type ◽

Fused Deposition ◽

And Topology ◽

Mask Design

Purpose Radiotherapy relies on the delivery of radiation to cancer cells with millimetre accuracy, and immobilisation of patients is essential to minimise unwanted damage to surrounding healthy cells due to patient movement. Traditional thermoformed face masks can be uncomfortable and stressful for patients and may not be accurately fitted. The purpose of this study was to use 3D scanning and additive manufacturing to digitise this workflow and improve patient comfort and treatment outcomes. Design/methodology/approach The head of a volunteer was scanned using an Artec Leo optical scanner (Artec, Luxembourg) and ANSYS (Ansys, Canonsburg, USA) software was used to make two 3D models of the mask: one with a nose bridge and one open as would be used with optical surface guidance. Data based on measurements from ten pressure sensors around the face was used to perform topology optimisation, with the best designs 3D printed using fused deposition modelling (FDM) and tested on the volunteer with embedded pressure sensors. Findings The two facemasks proved to be significantly different in terms of restricting head movement inside the masks. The optimised mask with a nose bridge effectively restricted head movement in roll and yaw orientations and exhibited minimal deformation as compared to the open mask design and the thermoformed mask. Originality/value The proposed workflow allows customisation of masks for radiotherapy immobilisation using additive manufacturing and topology optimisation based on collected pressure sensor data. In the future, sensors could be embedded in masks to provide real-time feedback to clinicians during treatment.

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Towards the Way for Correlating Dimensionality and Topology in Luminescent MOFs Based on Terephthalate and Bispyridyl-like Ligands

Dalton Transactions ◽

10.1039/d1dt01204e ◽

2021 ◽

Author(s):

Javier Cepeda ◽

Sonia Perez-Yañez ◽

Jose Angel Garcia ◽

Sara Rojas ◽

Antonio Rodríguez Diéguez

Keyword(s):

Structural Analysis ◽

Metal Ions ◽

Chemical Characterization ◽

Ternary Compounds ◽

And Topology ◽

Physico Chemical ◽

Group 12 ◽

The Way

Herein, we report on the synthesis, structural analysis, physico-chemical characterization and photoluminescence performance of two ternary compounds based on dicarboxylate and bispyridyl-like ligands and metal ions of group 12, namely...

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