scholarly journals Fine Wrinkling on Coarsely Meshed Thin Shells

2021 ◽  
Vol 40 (5) ◽  
pp. 1-32
Author(s):  
Zhen Chen ◽  
Hsiao-Yu Chen ◽  
Danny M. Kaufman ◽  
Mélina Skouras ◽  
Etienne Vouga
Keyword(s):  
Degrees Of Freedom ◽  
Ad Hoc ◽  
Geometric Analysis ◽  
Thin Shells ◽  
High Definition ◽  
Material Forces ◽  
Physical Experiments ◽  
Training Examples ◽  
Coarse Meshes ◽  
Tension Field Theory

We propose a new model and algorithm to capture the high-definition statics of thin shells via coarse meshes. This model predicts global, fine-scale wrinkling at frequencies much higher than the resolution of the coarse mesh; moreover, it is grounded in the geometric analysis of elasticity, and does not require manual guidance, a corpus of training examples, nor tuning of ad hoc parameters. We first approximate the coarse shape of the shell using tension field theory, in which material forces do not resist compression. We then augment this base mesh with wrinkles, parameterized by an amplitude and phase field that we solve for over the base mesh, which together characterize the geometry of the wrinkles. We validate our approach against both physical experiments and numerical simulations, and we show that our algorithm produces wrinkles qualitatively similar to those predicted by traditional shell solvers requiring orders of magnitude more degrees of freedom.

scholarly journals Task space adaptation via the learning of gait controllers of magnetic soft millirobots

2021 ◽  
pp. 027836492110218
Author(s):  
Sinan O. Demir ◽  
Utku Culha ◽  
Alp C. Karacakol ◽  
Abdon Pena-Francesch ◽  
Sebastian Trimpe ◽  
...  
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Bayesian Optimization ◽  
Small Scale ◽  
Soft Robots ◽  
Modeling And Control ◽  
Walking Gait ◽  
Physical Experiments ◽  
Efficient Learning ◽  
Task Environments

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

Computation and cognition: issues in the foundations of cognitive science

1980 ◽  
Vol 3 (1) ◽  
pp. 111-132 ◽  
Author(s):  
Zenon W. Pylyshyn
Keyword(s):  
Tacit Knowledge ◽  
Degrees Of Freedom ◽  
Ad Hoc ◽  
Physical Systems ◽  
Symbolic Representations ◽  
Natural Domain ◽  
Human Functioning ◽  
Biological Laws ◽  
Post Hoc ◽  
Level Of Analysis

AbstractThe computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach (the “proprietary vocabulary hypothesis”) is that there is a natural domain of human functioning (roughly what we intuitively associate with perceiving, reasoning, and acting) that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis.Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the “cognitive impenetrability condition.” Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind (called its “functional architecture”) from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the “degrees of freedom” problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories.

Numerical and Geometrical Analysis of the Onshore Oscillating Water Column Wave Energy with a Ramp

2021 ◽  
Vol 412 ◽  
pp. 11-26
Author(s):  
Marla Rodrigues Oliveira ◽  
Elizaldo Domingues Santos ◽  
Liércio André Isoldi ◽  
Luiz Alberto Oliveira Rocha ◽  
Mateus das Neves Gomes
Keyword(s):  
Water Column ◽  
Wave Energy ◽  
Degrees Of Freedom ◽  
Design Method ◽  
Geometric Analysis ◽  
Relative Difference ◽  
Front Wall ◽  
Multiphase Model ◽  
Oscillating Water Column ◽  
Worst Case

This study is about a two-dimensional numerical analysis of the influence of a ramp in front on an oscillating water column wave energy converter (OWC-WEC). The main purpose was to evaluate, numerically and geometrically, the effect of using a ramp variation in relation to the frontal wall on the hydropneumatic power of the OWC-WEC. The constructal design method was applied for geometric analysis. The problem had a geometric constraint: the area of the ramp (A2) and two degrees of freedom: H2 / L2 (ratio of the height and length of the ramp) and L4 (the distance of the ramp concerning the OWC-WEC front wall). In numerical simulations, the equations of conservation of mass, momentum, and an equation for the transport of volumetric fraction were solved using the finite volume method (FVM). The multiphase model volume of fluid (VOF) was applied for the air-water interaction. Thus, the increase in the H2/L2 ratio resulted in a decrease of the root mean square (RMS) of the available hydropneumatic power (Phyd). By varying the distance L4, the better case was = 6 m and / = 0.025 and the worst case was = 1 m and / = 0.2. The relative difference between the better RMS Phyd = 150.7957 W and the worst Phyd = 73.1164 W reached up to a hundred and six percent.

Updating of Non-Conservative Systems Using Inverse Methods

1997 ◽  
Author(s):  
Ladislav Starek ◽  
Milos Musil ◽  
Daniel J. Inman
Keyword(s):  
Analytical Model ◽  
Degrees Of Freedom ◽  
Ad Hoc ◽  
Natural Frequencies ◽  
Eigenvalue Problems ◽  
Model Updating ◽  
Analytical Models ◽  
Mode Shapes ◽  
Element Analysis ◽  
Modal Data

Abstract Several incompatibilities exist between analytical models and experimentally obtained data for many systems. In particular finite element analysis (FEA) modeling often produces analytical modal data that does not agree with measured modal data from experimental modal analysis (EMA). These two methods account for the majority of activity in vibration modeling used in industry. The existence of these discrepancies has spanned the discipline of model updating as summarized in the review articles by Inman (1990), Imregun (1991), and Friswell (1995). In this situation the analytical model is characterized by a large number of degrees of freedom (and hence modes), ad hoc damping mechanisms and real eigenvectors (mode shapes). The FEM model produces a mass, damping and stiffness matrix which is numerically solved for modal data consisting of natural frequencies, mode shapes and damping ratios. Common practice is to compare this analytically generated modal data with natural frequencies, mode shapes and damping ratios obtained from EMA. The EMA data is characterized by a small number of modes, incomplete and complex mode shapes and non proportional damping. It is very common in practice for this experimentally obtained modal data to be in minor disagreement with the analytically derived modal data. The point of view taken is that the analytical model is in error and must be refined or corrected based on experimented data. The approach proposed here is to use the results of inverse eigenvalue problems to develop methods for model updating for damped systems. The inverse problem has been addressed by Lancaster and Maroulas (1987), Starek and Inman (1992,1993,1994,1997) and is summarized for undamped systems in the text by Gladwell (1986). There are many sophisticated model updating methods available. The purpose of this paper is to introduce using inverse eigenvalues calculated as a possible approach to solving the model updating problem. The approach is new and as such many of the practical and important issues of noise, incomplete data, etc. are not yet resolved. Hence, the method introduced here is only useful for low order lumped parameter models of the type used for machines rather than structures. In particular, it will be assumed that the entries and geometry of the lumped components is also known.

Singularity Analysis of Closed Kinematic Chains

1999 ◽  
Vol 121 (1) ◽  
pp. 32-38 ◽  
Author(s):  
F. C. Park ◽  
J. W. Kim
Keyword(s):  
Configuration Space ◽  
Degrees Of Freedom ◽  
Geometric Analysis ◽  
Singularity Analysis ◽  
Geometric Framework ◽  
End Effector ◽  
Kinematic Chains ◽  
Closed Chain ◽  
High Level ◽  
Kinematic Singularities

This paper presents a coordinate-invariant differential geometric analysis of kinematic singularities for closed kinematic chains containing both active and passive joints. Using the geometric framework developed in Park and Kim (1996) for closed chain manipulability analysis, we classify closed chain singularities into three basic types: (i) those corresponding to singular points of the joint configuration space (configuration space singularities), (ii) those induced by the choice of actuated joints (actuator singularities), and (iii) those configurations in which the end-effector loses one or more degrees of freedom of available motion (end-effector singularities). The proposed geometric classification provides a high-level taxonomy for mechanism singularities that is independent of the choice of local coordinates used to describe the kinematics, and includes mechanisms that have more actuators than kinematic degrees of freedom.

scholarly journals Manufacturing large shafts by a novel flexible skew rolling process

2021 ◽  
Author(s):  
Longfei Lin ◽  
Baoyu Wang ◽  
Jing Zhou ◽  
Jinxia Shen
Keyword(s):  
Degrees Of Freedom ◽  
Longitudinal Section ◽  
Rolling Process ◽  
Single Step ◽  
Maximum Deviation ◽  
Center Crack ◽  
Physical Experiments ◽  
Skew Rolling ◽  
Forging Press ◽  
Forming Defects

Abstract When manufacturing large shafts with multi-specification and small-batch production, both the conventional forging and rolling process bring a high tooling cost due to heavy forging press or large-size specialized roller. In this study, a novel flexible skew rolling (FSR) process is proposed by adding degrees of freedom to the rollers as compared to the typical skew rolling process. Since each of the FSR rollers has three degrees of freedom (circle rotating, radial rotating and radial feeding), the FSR process can be divided into four stages: radial rolling, rollers inclining, skew rolling and rollers levelling. Therefore, the FSR process can produce various shafts with same rollers via programming different movements. To verify the feasibility of FSR process, a physical investigation corresponding with a numerical simulation for a single-step shaft is undertaken with a Φ80×390 mm C45 steel billet. According to the results from physical experiments and numerical simulations, the FSR formed shaft has a maximum deviation of 0.99 mm, and its microstructure and properties have been improved obviously. Moreover, although there is a tendency of center crack in FSR products as predicted by numerical results, both the transverse and longitudinal section of the physical shaft are free from central cracking. The major forming defects existed on the rolled shaft are knurled pockmarks, surface threads and side cavity, which are the typical defects of the conventional skew rolling and cross-wedge rolling and can be removed by machining. To the authors’ knowledge, this novel process has a good combination of flexible production and less loading, which will be of great engineering significance to reduce the tooling cost in large shafts manufacturing.

scholarly journals Automated Dynamic Mascon Generation for GRACE and GRACE-FO Harmonic Processing

2021 ◽  
Vol 13 (16) ◽  
pp. 3134
Author(s):  
Yara Mohajerani ◽  
David Shean ◽  
Anthony Arendt ◽  
Tyler C. Sutterley
Keyword(s):  
Degrees Of Freedom ◽  
Ad Hoc ◽  
Region Of Interest ◽  
Arbitrary Point ◽  
High Mountain ◽  
Regional Trends ◽  
Goddard Space Flight Center ◽  
Geophysical Signal ◽  
Range Rate ◽  
Gravity Recovery

Commonly used mass-concentration (mascon) solutions estimated from Level-1B Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, provided by processing centers such as the Jet Propulsion Laboratory (JPL) or the Goddard Space Flight Center (GSFC), do not give users control over the placement of mascons or inversion assumptions, such as regularization. While a few studies have focused on regional or global mascon optimization from spherical harmonics data, a global optimization based on the geometry of geophysical signal as a standardized product with user-defined points has not been addressed. Finding the optimal configuration with enough coverage to account for far-field leakage is not a trivial task and is often approached in an ad-hoc manner, if at all. Here, we present an automated approach to defining non-uniform, global mascon solutions that focus on a region of interest specified by the user, while maintaining few global degrees of freedom to minimize noise and leakage. We showcase our approach in High Mountain Asia (HMA) and Alaska, and compare the results with global uniform mascon solutions from range-rate data. We show that the custom mascon solutions can lead to improved regional trends due to a more careful sampling of geophysically distinct regions. In addition, the custom mascon solutions exhibit different seasonal variation compared to the regularized solutions. Our open-source pipeline will allow the community to quickly and efficiently develop optimized global mascon solutions for an arbitrary point or polygon anywhere on the surface of the Earth.

Optimal Sequence Planning for Robotic Sorting of Recyclables From Source-Segregated Municipal Solid Waste

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Sathish Paulraj Gundupalli ◽  
Rishabh Shukla ◽  
Rohit Gupta ◽  
Subrata Hait ◽  
Atul Thakur
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Degrees Of Freedom ◽  
Search Space ◽  
Optimal Sequence ◽  
Sequence Generation ◽  
Sorting Time ◽  
Physical Experiments ◽  
Sorting System ◽  
Material Recovery Facility

Abstract Sorting of recyclables from source-segregated municipal solid waste (MSW) stream is an essential step in the recycling chain in a material recovery facility (MRF) for waste management. Manual sorting of recyclables in an MRF is a highly hazardous operation for human health as well as time-consuming. Application of robotics for automated waste sorting can alleviate these problems to a large extent. The total sorting time depends upon the pick-and-place (PAP) sequence used in a robotic sorting system. In this context, the generation of optimal PAP sequence plan is a key challenge considering that it cannot be solved by an exhaustive search due to the combinatorial explosion of the search space. This paper reports an approach for generating optimal PAP sequence plan for robotic sorting of recyclables from source-segregated MSW stream in a system equipped with thermal-imaging technique. The PAP sequence generation is formulated as an optimization problem wherein the objective is to minimize the total sorting time. The formulated problem has been solved using a genetic algorithm (GA)-based approach. Numerical simulations as well as physical experiments using a 6 degrees-of-freedom (DOF) articulated manipulator have been performed to test and validate the developed optimal sequence generation algorithm. Results revealed an improvement of up to 4.28% speedup in total sorting time over that of randomly generated sequences. It is envisaged that the developed approach can substantially improve the sorting performance in an MRF.

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