More Like this

1. Web-based Interactive Polyhedral Graphics Statics Platform

   CHAI, Hua ; AKBARZADEH, Masoud ( October 2021 , International Association of Shell and Spatial Structures)

   This paper introduces a web-based interactive educational platform for 3D/polyhedral graphic statics (PGS) [1]. The Block Research Group (BRG) at ETH Zürich developed a dynamic learning and teaching platform for structural design. This tool is based on traditional graphic statics. It uses interactive 2D drawings to help designers and engineers with all skill levels to understand and utilize the methods [2]. However, polyhedral graphic statics is not easy to learn because of its characteristics in three-dimensional. All the existing computational design tools are heavily dependent on the modeling software such as Rhino or the Python-based computational framework like Compass [3]. In this research, we start with the procedural approach, developing libraries using JavaScript, Three.js, and WebGL to facilitate the construction by making it independent from any software. This framework is developed based on the mathematical and computational algorithms deriving the global equilibrium of the structure, optimizing the balanced relationship between the external magnitudes and the internal forces, visualizing the dynamic reciprocal polyhedral diagrams with corresponding topological data. This instant open-source application and the visualization interface provide a more operative platform for students, educators, practicers, and designers in an interactive manner, allowing them to learn not only the topological relationship but also to deepen their knowledge and understanding of structures in the steps for the construction of the form and force diagrams and analyze it. In the simplified single-node example, the multi-step geometric procedures intuitively illustrate 3D structural reciprocity concepts. With the intuitive control panel, the user can move the constraint point’s location through the inserted gumball function, the force direction of the form diagram will be dynamically changed from compression-only to tension and compression combined. Users can also explore and design innovative, efficient spatial structures with changeable boundary conditions and constraints through real-time manipulating both force distribution and geometric form, such as adding the number of supports or subdividing the global equilibrium in the force diagram. Eventually, there is an option to export the satisfying geometry as a suitable format to share with other fabrication tools. As the online educational environment with different types of geometric examples, it is valuable to use graphical approaches to teach the structural form in an exploratory manner. 

   more » « less
2. Stoichiometric Modeling of Artificial String Chemistries Reveals Constraints on Metabolic Network Structure

   https://doi.org/10.1007/s00239-021-10018-0  

   Moyer, Devlin ; Pacheco, Alan R. ; Bernstein, David B. ; Segrè, Daniel ( July 2021 , Journal of Molecular Evolution)

   Uncovering the general principles that govern the structure of metabolic networks is key to understanding the emergence and evolution of living systems. Artificial chemistries can help illuminate this problem by enabling the exploration of chemical reaction universes that are constrained by general mathematical rules. Here, we focus on artificial chemistries in which strings of characters represent simplified molecules, and string concatenation and splitting represent possible chemical reactions. We developed a novel Python package, ARtificial CHemistry NEtwork Toolbox (ARCHNET), to study string chemistries using tools from the field of stoichiometric constraint-based modeling. In addition to exploring the topological characteristics of different string chemistry networks, we developed a network-pruning algorithm that can generate minimal metabolic networks capable of producing a specified set of biomass precursors from a given assortment of environmental nutrients. We found that the composition of these minimal metabolic networks was influenced more strongly by the metabolites in the biomass reaction than the identities of the environmental nutrients. This finding has important implications for the reconstruction of organismal metabolic networks and could help us better understand the rise and evolution of biochemical organization. More generally, our work provides a bridge between artificial chemistries and stoichiometric modeling, which can help address a broad range of open questions, from the spontaneous emergence of an organized metabolism to the structure of microbial communities.

    

   more » « less
3. Unidirectional Maxwellian spin waves

   https://doi.org/10.1515/nanoph-2019-0092  

   Van Mechelen, Todd ; Jacob, Zubin ( June 2019 , Nanophotonics)

   Abstract In this article, we develop a unified perspective of unidirectional topological edge waves in nonreciprocal media. We focus on the inherent role of photonic spin in nonreciprocal gyroelectric media, i.e. magnetized metals or magnetized insulators. Due to the large body of contradicting literature, we point out at the outset that these Maxwellian spin waves are fundamentally different from well-known topologically trivial surface plasmon polaritons. We first review the concept of a Maxwell Hamiltonian in nonreciprocal media, which immediately reveals that the gyrotropic coefficient behaves as a photon mass in two dimensions. Similar to the Dirac mass, this photonic mass opens bandgaps in the energy dispersion of bulk propagating waves. Within these bulk photonic bandgaps, three distinct classes of Maxwellian edge waves exist – each arising from subtle differences in boundary conditions. On one hand, the edge wave solutions are rigorous photonic analogs of Jackiw-Rebbi electronic edge states. On the other hand, for the exact same system, they can be high frequency photonic counterparts of the integer quantum Hall effect, familiar at zero frequency. Our Hamiltonian approach also predicts the existence of a third distinct class of Maxwellian edge wave exhibiting topological protection. This occurs in an intriguing topological bosonic phase of matter, fundamentally different from any known electronic or photonic medium. The Maxwellian edge state in this unique quantum gyroelectric phase of matter necessarily requires a sign change in gyrotropy arising from nonlocality (spatial dispersion). In a Drude system, this behavior emerges from a spatially dispersive cyclotron frequency that switches sign with momentum. A signature property of these topological electromagnetic edge states is that they are oblivious to the contacting medium, i.e. they occur at the interface of the quantum gyroelectric phase and any medium (even vacuum). This is because the edge state satisfies open boundary conditions – all components of the electromagnetic field vanish at the interface. Furthermore, the Maxwellian spin waves exhibit photonic spin-1 quantization in exact analogy with their supersymmetric spin-1/2 counterparts. The goal of this paper is to discuss these three foundational classes of edge waves in a unified perspective while providing in-depth derivations, taking into account nonlocality and various boundary conditions. Our work sheds light on the important role of photonic spin in condensed matter systems, where this definition of spin is also translatable to topological photonic crystals and metamaterials. 

   more » « less
4. Parallelized Topological Relaxation Algorithm

   https://doi.org/10.1109/BigData47090.2019.9006309  

   Ruan, Guangchen ; Zhang, Hui ( December 2019 , 2019 IEEE International Conference on Big Data (Big Data))

   Geometric problems of interest to mathematical visualization applications involve changing structures, such as the moves that transform one knot into an equivalent knot. In this paper, we describe mathematical entities (curves and surfaces) as link-node graphs, and make use of energy-driven relaxation algorithms to optimize their geometric shapes by moving knots and surfaces to their simplified equivalence. Furthermore, we design and conFigure parallel functional units in the relaxation algorithms to accelerate the computation these mathematical deformations require. Results show that we can achieve significant performance optimization via the proposed threading model and level of parallelization. 

   more » « less
5. WebMILE: Democratizing Network Representation Learning at Scale

   https://doi.org/10.14778/3554821.3554883  

   He, Yuntian ; Zhang, Yue ; Gurukar, Saket ; Parthasarathy, Srinivasan ( January 2022 , Proceedings of the VLDB Endowment)

   n recent years, we have seen the success of network representation learning (NRL) methods in diverse domains ranging from com- putational chemistry to drug discovery and from social network analysis to bioinformatics algorithms. However, each such NRL method is typically prototyped in a programming environment familiar to the developer. Moreover, such methods rarely scale out to large-scale networks or graphs. Such restrictions are problematic to domain scientists or end-users who want to scale a particular NRL method-of-interest on large graphs from their specific domain. In this work, we present a novel system, WebMILE to democ- ratize this process. WebMILE can scale an unsupervised network embedding method written in the user’s preferred programming language on large graphs. It provides an easy-to-use Graphical User Interface (GUI) for the end-user. The user provides the necessary in- put (embedding method file, graph, required packages information) through a simple GUI, and WebMILE executes the input network embedding method on the given input graph. WebMILE leverages a pioneering multi-level method, MILE (alternatively DistMILE if the user has access to a cluster), that can scale a network embed- ding method on large graphs. The language agnosticity is achieved through a simple Docker interface. In this demonstration, we will showcase how a domain scientist or end-user can utilize WebMILE to rapidly prototype and learn node embeddings of a large graph in a flexible and efficient manner - ensuring the twin goals of high productivity and high performance. 

   more » « less