scholarly journals Computational Modeling Methods for Deployable Structure Based on Alternatively Asymmetric Triangulation

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1278
Author(s):  
Zhang ◽  
Yu ◽  
Li ◽  
Fan
Keyword(s):  
Computational Modeling ◽  
Parametric Modeling ◽  
Mathematical Idea ◽  
Regular Polygons ◽  
Digital Environment ◽  
Geometric Properties ◽  
Folding Angle ◽  
3D Shape ◽  
Modeling Methods ◽  
Deployable Structure

Asymmetric triangulation is an interesting method combined with concentric pleating to obtain a 3D shape without stretching or tearing. There exists some geometric properties in the process of folding to help realize extension and contraction, which can be used in parametric modeling of different regular polygons. To facilitate design and modeling, adequate computational modeling methods are indispensable. This paper proposes a new mathematical idea and presents a feasible way to build the parameterized models in the digital environment of Rhinoceros, utilizing the Kangaroo plugin in Grasshopper. Designers can directly observe the models’ kinematic deployment and calculate the folding efficiency. It is concluded that the tendencies of folding efficiency in different regular polygons are not the same. To realize rigid folding, each polygon has a limited folding angle.

scholarly journals Anatomy of a Psychological Theory: Integrating Construct-Validation and Computational-Modeling Methods to Advance Theorizing

2021 ◽  
pp. 174569162096679
Author(s):  
Ivan Grahek ◽  
Mark Schaller ◽  
Jennifer L. Tackett
Keyword(s):  
Computational Modeling ◽  
Construct Validation ◽  
Theory Development ◽  
Psychological Theory ◽  
Modeling Methods ◽  
Psychological Theories ◽  
Development Processes ◽  
Convergence And Divergence

Discussions about the replicability of psychological studies have primarily focused on improving research methods and practices, with less attention paid to the role of well-specified theories in facilitating the production of reliable empirical results. The field is currently in need of clearly articulated steps to theory specification and development, particularly regarding frameworks that may generalize across different fields of psychology. Here we focus on two approaches to theory specification and development that are typically associated with distinct research traditions: computational modeling and construct validation. We outline the points of convergence and divergence between them to illuminate the anatomy of a scientific theory in psychology—what a well-specified theory should contain and how it should be interrogated and revised through iterative theory-development processes. We propose how these two approaches can be used in complementary ways to increase the quality of explanations and the precision of predictions offered by psychological theories.

A New Ergonomics Manikin Generation Method from Real 3D Scanning Body

2010 ◽  
Vol 26-28 ◽  
pp. 1075-1078 ◽  
Author(s):  
Zhan Xun Dong ◽  
Zhen Yu Gu ◽  
Zhan Wei Wu
Keyword(s):  
3D Scanning ◽  
Parametric Modeling ◽  
Human Model ◽  
Free Form ◽  
Model Optimization ◽  
Body Scanning ◽  
Modeling Methods ◽  
Fundamental Information ◽  
Model Phase

Computer-Aided Ergonomics (CAE) makes it possible that people may build a virtual environment for ergonomics evaluation in the product’s digital model phase. Manikin with anthropometry data supplies fundamental information in design lifecycle, so it also plays an important role in CAE software. Thanks to the 3D scanning technology, we developed a new ergonomics manikin generation method which could create free-form surface human model from real body. Generation method concluded body scanning, model optimization, and combining skeleton stages. Finally, case study proved that Paper’s method could generate more exact manikin than former parametric modeling methods, and it would benefit customized products design.

scholarly journals Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling

2021 ◽  
Vol 12 ◽  
Author(s):  
Renee Dale ◽  
Scott Oswald ◽  
Amogh Jalihal ◽  
Mary-Francis LaPorte ◽  
Daniel M. Fletcher ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Machine Learning ◽  
Computational Modeling ◽  
Quantitative Methods ◽  
Plant Biology ◽  
Experimental Plant ◽  
Modeling Methods ◽  
Modeling Techniques ◽  
Research Questions ◽  
Biology Research

The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.

Computational modeling methods for simulating obstructive human lung diseases

2016 ◽  
Author(s):  
Stavros Nousias ◽  
Aris Lalos ◽  
Konstantinos Moustakas ◽  
Antonios Lalas ◽  
Dimitrios Kikidis ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Lung Diseases ◽  
Human Lung ◽  
Modeling Methods

Computational Modeling Methods for 3D Structure Prediction of Ribozymes

Ribozymes ◽  
2021 ◽  
pp. 861-881
Author(s):  
Pritha Ghosh ◽  
Chandran Nithin ◽  
Astha Joshi ◽  
Filip Stefaniak ◽  
Tomasz K. Wirecki ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Structure Prediction ◽  
3D Structure ◽  
Modeling Methods ◽  
3D Structure Prediction
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