Physicalizing cardiac blood flow data via 3D printing

Ang, Kathleen; Samavati, Faramarz; Sabokrohiyeh, Samin; García, Julio; Elbaz, Mohammed

doi:10.1016/j.cag.2019.09.004

Cited by 16 publications

(24 citation statements)

References 56 publications

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“…Physical prototypes offer quicker, lower‐cost interim representations for design iteration (e.g., [ASS∗19, Bar11, Mar14]). One approach for prototyping is to build a small portion of the final physicalization, with the final scale, fabrication technique, and material as done by [ADMAS18] or to build a scale‐model of a larger‐scale physicalization as a way of verifying the overall design rationale (e.g., [HDA∗19]).…”

Section: Discussionmentioning

confidence: 99%

“…Thrun and Lerch used 3D printing to represent high‐dimensional datasets such as pain phenotypes as a landscape in four different colors (i.e., white, red, green, blue, yellow), highlighting distance [TL16]. Ang et al [ASS∗19] physicalized blood‐flow datasets by 3D printing slices of curves or glyph to resemble flow directions in a volume (see Figure 5c). Lozano‐Hemmer physicalized viewers' heart rates with a set of light bulbs hanging in a room, synchronizing the bulbs with each heart rate as viewers began interacting with the work [LH06].…”

Section: Target Data For Physicalizationmentioning

confidence: 99%

“…However, since material in this approach needs to be deposited on top of an exiting layer, FDM printing relies heavily on support structures that need to be removed after fabrication. Therefore, to fabricate delicate structures, creative solutions such as layer supports are designed [ASS∗19]. FDM printing also suffers from a limited building volume, which is by average 25 3 cm 3 .…”

Section: Design and Physical Rendering Approachesmentioning

confidence: 99%

“…InfoVis physicalizations in our corpus include correlations between data series [Dwy04], personal activity data [STS∗14], or time‐series data of one's baby as a personal memento (e.g., [SSJ∗14]). Examples of SciVis physicalizations include physical maps to form connections between themes in a gallery space [PGDG12] or to explain the future of energy in Hawaii [KHT∗20]), to explore volumetric, anatomical data [NB00] or 4D MRI blood flow data [ASS∗19]), to understand the assembly of macro‐molecules or viruses using passive physical models [BSJ98] or combined with augmented reality overlays [GSSO05].…”

Section: Physicalization Classification Schemesmentioning

confidence: 99%

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Data to Physicalization: A Survey of the Physical Rendering Process

Djavaherpour

Samavati

Mahdavi-Amiri

et al. 2021

Computer Graphics Forum

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Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data‐driven geometry, rendering data as a physically fabricated object is still a daunting leap for many physicalization designers. Rendering in the scope of this research refers to the back‐and‐forth process from digital design to digital fabrication and its specific challenges. We developed a corpus of example data physicalizations from research literature and physicalization practice. This survey then unpacks the “rendering” phase of the extended InfoVis pipeline in greater detail through these examples, with the aim of identifying ways that researchers, artists, and industry practitioners “render” physicalizations using digital design and fabrication tools.

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Section: Discussionmentioning

confidence: 99%

Section: Target Data For Physicalizationmentioning

confidence: 99%

Section: Design and Physical Rendering Approachesmentioning

confidence: 99%

Section: Physicalization Classification Schemesmentioning

confidence: 99%

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Data to Physicalization: A Survey of the Physical Rendering Process

Djavaherpour

Samavati

Mahdavi-Amiri

et al. 2021

Computer Graphics Forum

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“…However, in the second group (“two-way shape memory materials”), the shape can be altered reversibly [ 15 , 16 ]. Although the investigation of this technique also points to health-related areas [ 12 , 17 , 18 ], this paper will focus only on studies related to the mechanical performance.…”

Section: Introductionmentioning

confidence: 99%

Fused Filament Fabrication-4D-Printed Shape Memory Polymers: A Review

et al. 2021

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Additive manufacturing (AM) is the process through which components/structures are produced layer-by-layer. In this context, 4D printing combines 3D printing with time so that this combination results in additively manufactured components that respond to external stimuli and, consequently, change their shape/volume or modify their mechanical properties. Therefore, 4D printing uses shape-memory materials that react to external stimuli such as pH, humidity, and temperature. Among the possible materials with shape memory effect (SME), the most suitable for additive manufacturing are shape memory polymers (SMPs). However, due to their weaknesses, shape memory polymer compounds (SMPCs) prove to be an effective alternative. On the other hand, out of all the additive manufacturing techniques, the most widely used is fused filament fabrication (FFF). In this context, the present paper aims to critically review all studies related to the mechanical properties of 4D-FFF materials. The paper provides an update state of the art showing the potential of 4D-FFF printing for different engineering applications, maintaining the focus on the structural integrity of the final structure/component.

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