Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SimuLearn: Fast and Accurate Simulator to Support Morphing Materials
  Design and Workflows   Morphing materials allow us to create new modalities of interaction and
fabrication by leveraging dynamic behaviors of materials. Yet, despite the
ongoing rapid growth of computational tools within this realm, current
developments are bottlenecked by the lack of an effective simulation method. As
a result, existing design tools must trade-off between speed and accuracy to
support a real-time interactive design scenario. In response, we introduce
SimuLearn, a data-driven method that combines finite element analysis and
machine learning to create real-time (0.61 seconds) and truthful (97% accuracy)
morphing material simulators. We use mesh-like 4D printed structures to
contextualize this method and prototype design tools to exemplify the design
workflows and spaces enabled by a fast and accurate simulation method.
Situating this work among existing literature, we believe SimuLearn is a timely
addition to the HCI CAD toolbox that can enable the proliferation of morphing
materials.

31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an