Designing Mechanical Properties of 3D Printed Cookies through Computer Aided Engineering

Additive manufacturing or 3D printing can be applied in the food sector to create food products with personalized properties such as shape, texture, and composition. In this article, we introduce a computer aided engineering (CAE) methodology to design 3D printed food products with tunable mechanical properties. The focus was on the Young modulus as a proxy of texture. Finite element modelling was used to establish the relationship between the Young modulus of 3D printed cookies with a honeycomb structure and their structure parameters. Wall thickness, cell size, and overall porosity were found to influence the Young modulus of the cookies and were, therefore, identified as tunable design parameters. Next, in experimental tests, it was observed that geometry deformations arose during and after 3D printing, affecting cookie structure and texture. The 3D printed cookie porosity was found to be lower than the designed one, strongly influencing the Young modulus. After identifying the changes in porosity through X-ray micro-computed tomography, a good match was observed between computational and experimental Young’s modulus values. These results showed that changes in the geometry have to be quantified and considered to obtain a reliable prediction of the Young modulus of the 3D printed cookies

Designing Mechanical Properties of 3D Printed Cookies through Computer Aided Engineering.

Additive manufacturing or 3D printing can be applied in the food sector to create food products with personalized properties such as shape, texture, and composition. In this article, we introduce a computer aided engineering (CAE) methodology to design 3D printed food products with tunable mechanical properties. The focus was on the Young modulus as a proxy of texture. Finite element modelling was used to establish the relationship between the Young modulus of 3D printed cookies with a honeycomb structure and their structure parameters. Wall thickness, cell size, and overall porosity were found to influence the Young modulus of the cookies and were, therefore, identified as tunable design parameters. Next, in experimental tests, it was observed that geometry deformations arose during and after 3D printing, affecting cookie structure and texture. The 3D printed cookie porosity was found to be lower than the designed one, strongly influencing the Young modulus. After identifying the changes in porosity through X-ray micro-computed tomography, a good match was observed between computational and experimental Young's modulus values. These results showed that changes in the geometry have to be quantified and considered to obtain a reliable prediction of the Young modulus of the 3D printed cookies.status: Published onlin

Characterization and model-based design validation of 3D printed cookies

Additive manufacturing is revolutionizing processing in many applications including 3D food printing. A Fused Deposition Modelling printing method was developed to produce cookies. In order to design food of particular texture, a fine element model was established to predict the mechanical properties of structured products. Cookie structures were engineered to achieve desirable texture properties in silico and dedicated print files were created for 3D printing. In order to validate the model, the properties of the printed cookies were measured and analysed. Compression tests were performed to determine Young’s modulus. X-ray micro-CT imaging was applied to characterize the 3D microstructure of the printed cookies samples. Micro-CT imaging provided a better understanding about the effects of the 3D printing process on cookie structure. Finally, a better fit of the prediction model was obtained by adjusting the model geometry to the scanned printed structure, which indicates the importance of structure integrity for mechanical properties of printed cookies.status: publishe

The 2021 SSP scenarios of the IMAGE 3.2 model

The SSP (Shared Socio-economic Pathways) scenarios are intensively used in climate and environmental research to explore uncertain future developments and possible response strategies. This paper briefly describes an update of the SSP scenarios generated by the IMAGE 3.2 model. The paper presents the changes in method and key scenario updates. As such, it serves as a key reference for the updated SSP scenarios with IMAGE 3.2

The 2021 SSP scenarios of the IMAGE 3.2 model

The SSP (Shared Socio-economic Pathways) scenarios are intensively used in climate and environmental research to explore uncertain future developments and possible response strategies. This paper briefly describes an update of the SSP scenarios generated by the IMAGE 3.2 model. The paper presents the changes in method and key scenario updates. As such, it serves as a key reference for the updated SSP scenarios with IMAGE 3.2

Sensitivity of polar and temperate marine organisms to oil components

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