ShapeOp—A Robust and Extensible Geometric Modelling Paradigm

Deuss, Mario; Deleuran, Anders Holden; Bouaziz, Samir; Deng, Bailin; Piker, Daniel; Pauly, Mark

doi:10.1007/978-3-319-24208-8_42

Cited by 32 publications

(18 citation statements)

References 10 publications

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“…a twisted initial condition. For projective dynamics, we used the implementation in the ShapeOp library [55]. While our proof of equivalence does not apply to this problem because of the presence of rotations, we can see that with the choice w i = √ k i ADMM and projective dynamics take nearly the same steps towards convergence (the difference in run time is likely an artifact of implementation details).…”

Section: Comparison With Projective Dynamicsmentioning

confidence: 99%

ADMM Projective Dynamics: Fast Simulation of Hyperelastic Models with Dynamic Constraints

Overby

Brown

et al. 2017

IEEE Trans. Visual. Comput. Graphics

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We apply the alternating direction method of multipliers (ADMM) optimization algorithm to implicit time integration of elastic bodies, and show that the resulting method closely relates to the recently proposed projective dynamics algorithm. However, as ADMM is a general purpose optimization algorithm applicable to a broad range of objective functions, it permits the use of nonlinear constitutive models and hard constraints while retaining the speed, parallelizability, and robustness of projective dynamics. We further extend the algorithm to improve the handling of dynamically changing constraints such as sliding and contact, while maintaining the benefits of a constant, prefactored system matrix. We demonstrate the benefits of our algorithm on several examples that include cloth, collisions, and volumetric deformable bodies with nonlinear elasticity and skin sliding effects.

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Section: Comparison With Projective Dynamicsmentioning

confidence: 99%

ADMM Projective Dynamics: Fast Simulation of Hyperelastic Models with Dynamic Constraints

Overby

Brown

et al. 2017

IEEE Trans. Visual. Comput. Graphics

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“…A DR-inspired solver, which has gained reasonable popularity in recent years due to its ease of use and speed. Currently in its second major rewritten version, it now follows the projection dynamics approach as developed by Bouaziz et al [12][13][14] Inherently an explicit solver, equilibrium in each node is sought simultaneously by assigning mass, acceleration and damping of the nodes. This means that DR-based methods are insensitive to the static determinacy of the structural system such that mechanisms and large deformations are not an issue, provided the solver is able to remain stable (as is the case with Kangaroo).…”

Section: Form-finding Tools For Textile Hybridsmentioning

confidence: 99%

Shaping hybrids – Form finding of new material systems

Gengnagel

Magna

Thomsen

et al. 2018

International Journal of Architectural Computing

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Form-finding processes are an integral part of structural design. Because of their limitations, the classic approaches to finding a form-such as hanging models and the soap-film analogy-play only a minor role. The various possibilities of digital experimentation in the context of structural optimisation create new options for the designer generating forms, while enabling control over a wide variety of parameters. A complete mapping of the mechanical properties of a structure in a continuum mechanics model is possible but so are simplified modelling strategies which take into account only the most important properties of the structure, such as iteratively approximating to a solution via representations of kinematic states. Form finding is thus an extremely complex process, determined both by the freely selected parameters and by design decisions.

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“…After this grid was mapped to the actual curved wall, it was found that the resulting panel faces were approximately planar, thus no further planarization was applied. If non-planar faces were encountered, planarity constraint as discussed in Deuss et al [4] could have been applied. The roof and the ground floor were added by closing the holes at the top and the bottom of the wall, respectively, thus creating a cell.…”

Section: Vdfp/nmt Building Model (A)mentioning

confidence: 99%

Addressing Pathways to Energy Modelling Through Non-Manifold Topology

Chatzivasileiadi¹,

Lannon²,

Jabi³

et al. 2018

Proceedings of the 2018 Symposium on Simulation for Architecture and Urban Design (SimAUD 2018)

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This paper presents a comparison of different pathways for the energy modelling of complex building geometry. We have identified three key modelling questions: first, how can the spatial organisation of the building be appropriately represented for energy analysis? Second, how can curved building geometry be post-rationalized as planar elements given the planar constraints associated with energy simulation tools? And third, how can an exploratory design process be supported using a 'top-down' rather than a 'bottom-up' modelling approach? Using a standard office building test case and EnergyPlus, the following three pathways were explored: (a) OpenStudio using a non-manifold topology (NMT) system based on an open-source geometry library, (b) OpenStudio using the SketchUp 3D modelling tool and (c) through the DesignBuilder graphical interface. The efficacy of the software used in these pathways in addressing the three modelling questions was evaluated. The comparison of the pathways' capabilities has led to the evaluation of the efficacy of NMT compared to other existing approaches. It is concluded that NMT positively addresses the three key modelling issues.

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ShapeOp—A Robust and Extensible Geometric Modelling Paradigm

Cited by 32 publications

References 10 publications

ADMM Projective Dynamics: Fast Simulation of Hyperelastic Models with Dynamic Constraints

ADMM Projective Dynamics: Fast Simulation of Hyperelastic Models with Dynamic Constraints

Shaping hybrids – Form finding of new material systems

Addressing Pathways to Energy Modelling Through Non-Manifold Topology

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