Visualizing the Time Motion of Planar Mechanisms With Volume Methods

2005 ◽  
Author(s):  
Mike Bailley
Keyword(s):  
Volume Visualization ◽  
Spatial Dimension ◽  
Three Dimensions ◽  
Time Dimension ◽  
Modeling And Analysis ◽  
Planar Mechanism ◽  
Time Motion ◽  
Novel Approach ◽  
3D Volume ◽  
Visualization Techniques

Two dimensional, or planar, mechanism design is a mainstay of Mechanical Engineering modeling and analysis. An important part of the design process is the visualizing of the motion of the mechanism. This paper describes a novel approach to visualizing the time motion of a planar mechanism — turning the time dimension into a spatial dimension. All three dimensions (x,y,time) are then treated as a 3D volume. From there, we use interactive volume visualization techniques, including slicing and thresholding. As is seen, this method is able to produce new insights into planar mechanism motion, particularly when more than one mechanism is working cooperatively.

scholarly journals Contrasting Definitions of High Energy Performance Buildings

2020 ◽  
Vol 172 ◽  
pp. 16005
Author(s):  
Charlotte Verhaeghe ◽  
Audenaert Amaryllis ◽  
Stijn Verbeke
Keyword(s):  
Energy Use ◽  
Spatial Dimension ◽  
Energy Performance ◽  
High Energy ◽  
Three Dimensions ◽  
Positive Energy ◽  
Time Dimension ◽  
End Use ◽  
Passive Houses ◽  
End Uses

The rising interest in low energy building has led to an inflation in related terminology: (nearly) zero energy buildings, or (n)ZEBs, passive houses, positive energy buildings and districts, off-grid buildings, energy autarkic buildings, etc. Each of these terms involves (sometimes subtle) differences in interpretations, system boundaries, included energy end uses, etc. This paper maps the differences and overlaps in applications of various cases of residential High Energy Performance Buildings (HEPBs), aiming to contribute in the development of a novel taxonomy to evaluate the extent to which a building can be considered energy or carbon neutral. Three dimensions are suggested for specification in novel taxonomy for HEPBs: (i) the spatial dimension (energy use, locally renewable energy production and sometimes energy storage), (ii) the time dimension (during which period is the building and its systems balanced, e.g. yearly or momentary) and (iii) the end-use dimension (these are the end-uses that are included or excluded for the calculation of the total energy needs of the buildings).

scholarly journals Design of a Didactical Activity for the Analysis of Uncertainties in Thermography through the Use of Robust Statistics as Teacher-Oriented Approach

2021 ◽  
Vol 13 (3) ◽  
pp. 402
Author(s):  
Pablo Rodríguez-Gonzálvez ◽  
Manuel Rodríguez-Martín
Keyword(s):  
Open Source ◽  
Robust Statistics ◽  
Three Dimensional ◽  
Learning Material ◽  
Novel Approach ◽  
Learning Programs ◽  
Institutional Learning ◽  
Thermographic Image ◽  
Visualization Techniques ◽  
Free Open Source

The thermography as a methodology to quantitative data acquisition is not usually addressed in the degrees of university programs. The present manuscript proposes a novel approach for the acquisition of advanced competences in engineering courses associated with the use of thermographic images via free/open-source software solutions. This strategy is established from a research based on the statistical and three-dimensional visualization techniques over thermographic imagery to improve the interpretation and comprehension of the different sources of error affecting the measurements and, thereby, the conclusions and analysis arising from them. The novelty is focused on the detection of non-normalities in thermographic images, which is illustrates in the experimental section. Additionally, the specific workflow for the generation of learning material related with this aim is raised for asynchronous and e-learning programs. These virtual materials can be easily deployed in an institutional learning management system, allowing the students to work with the models by means of free/open-source solutions easily. Subsequently, the present approach will give new tools to improve the application of professional techniques, will improve the students’ critical sense to know how to interpret the uncertainties in thermography using a single thermographic image, therefore they will be better prepared to face future challenges with more critical thinking.

scholarly journals A Clustering-Based Automatic Transfer Function Design for Volume Visualization

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Tianjin Zhang ◽  
Zongrui Yi ◽  
Jinta Zheng ◽  
Dong C. Liu ◽  
Wai-Mai Pang ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
Spatial Information ◽  
Transfer Functions ◽  
Clustering Algorithms ◽  
Volume Visualization ◽  
Automatic Generation ◽  
Volume Data ◽  
3D Volume ◽  
Ap Clustering ◽  
Different Tissues

The two-dimensional transfer functions (TFs) designed based on intensity-gradient magnitude (IGM) histogram are effective tools for the visualization and exploration of 3D volume data. However, traditional design methods usually depend on multiple times of trial-and-error. We propose a novel method for the automatic generation of transfer functions by performing the affinity propagation (AP) clustering algorithm on the IGM histogram. Compared with previous clustering algorithms that were employed in volume visualization, the AP clustering algorithm has much faster convergence speed and can achieve more accurate clustering results. In order to obtain meaningful clustering results, we introduce two similarity measurements: IGM similarity and spatial similarity. These two similarity measurements can effectively bring the voxels of the same tissue together and differentiate the voxels of different tissues so that the generated TFs can assign different optical properties to different tissues. Before performing the clustering algorithm on the IGM histogram, we propose to remove noisy voxels based on the spatial information of voxels. Our method does not require users to input the number of clusters, and the classification and visualization process is automatic and efficient. Experiments on various datasets demonstrate the effectiveness of the proposed method.

scholarly journals A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

2013 ◽  
Vol 26 (3) ◽  
pp. 766-776 ◽  
Author(s):  
Xiaodong Tan ◽  
Jing Qiu ◽  
Guanjun Liu ◽  
Kehong Lv ◽  
Shuming Yang ◽  
...  
Keyword(s):  
Evolution Mechanism ◽  
Modeling And Analysis ◽  
Novel Approach ◽  
Failure Evolution

scholarly journals Discrete element method approach to modelling VPP dampers

2018 ◽  
Vol 157 ◽  
pp. 02014
Author(s):  
Pawel Chodkiewicz ◽  
Jakub Lengiewicz ◽  
Robert Zalewski
Keyword(s):  
Discrete Element Method ◽  
Granular Medium ◽  
Discrete Element ◽  
Modeling And Analysis ◽  
Novel Approach ◽  
Particle Dampers ◽  
Pressure Boundary Conditions ◽  
Dem Model ◽  
Method Approach ◽  
Element Method

In this paper, we present a novel approach to modeling and analysis of Vacuum Packed Particle dampers (VPP dampers) with the use of Discrete Element Method (DEM). VPP dampers are composed of loose granular medium encapsulated in a hermetic envelope, with controlled pressure inside the envelope. By changing the level of underpressure inside the envelope, one can control mechanical properties of the system. The main novelty of the DEM model proposed in this paper is the method to treat special (pressure) boundary conditions at the envelope. The model has been implemented within the open-source Yade DEM software. Preliminary results are presented and discussed in the paper. The qualitative agreement with experimental results has been achieved.

scholarly journals All fingers are not the same: Handling variable-length sequences in a discriminative setting using conformal multi-instance kernels

2017 ◽  
Author(s):  
Sarvesh Nikumbh ◽  
Peter Ebert ◽  
Nico Pfeifer
Keyword(s):  
Binary Classification ◽  
Positional Information ◽  
Weight Vector ◽  
Variable Length ◽  
Genomic Sequences ◽  
String Kernels ◽  
Promoter Sequences ◽  
Novel Approach ◽  
The Individual ◽  
Visualization Techniques

AbstractMost string kernels for comparison of genomic sequences are generally tied to using (absolute) positional information of the features in the individual sequences. This poses limitations when comparing variable-length sequences using such string kernels. For example, profiling chromatin interactions by 3C-based experiments results in variable-length genomic sequences (restriction fragments). Here, exact position-wise occurrence of signals in sequences may not be as important as in the scenario of analysis of the promoter sequences, that typically have a transcription start site as reference. Existing position-aware string kernels have been shown to be useful for the latter scenario.In this work, we propose a novel approach for sequence comparison that enables larger positional freedom than most of the existing approaches, can identify a possibly dispersed set of features in comparing variable-length sequences, and can handle both the aforementioned scenarios. Our approach, CoMIK, identifies not just the features useful towards classification but also their locations in the variable-length sequences, as evidenced by the results of three binary classification experiments, aided by recently introduced visualization techniques. Furthermore, we show that we are able to efficiently retrieve and interpret the weight vector for the complex setting of multiple multi-instance kernels.

scholarly journals The bias of avoiding spatial dynamic panel models

REGION ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 153-180
Author(s):  
Lorenz Benedikt Fischer
Keyword(s):  
Dynamic Models ◽  
Regional Economics ◽  
Empirical Work ◽  
Optimal Estimation ◽  
Spatial Dimension ◽  
The Other ◽  
Omitted Variables ◽  
Time Dimension ◽  
Opposite Case ◽  
Dynamic Panel Models

Many questions in urban and regional economics can be characterized as including both a spatial and a time dimension. However, often one of these dimensions is neglected in empirical work. This paper highlights the danger of methodological inertia, investigating the effect of neglecting the spatial or the time dimension when in fact both are important. A tale of two research teams, one living in a purely dynamic and the other in a purely spatial world of thinking, sets the scene. Because the researcher teams' choices to omit a dimension change the assumed optimal estimation strategies, the issue is more difficult to analyze than a typical omitted variables problem. First, the bias of omitting a relevant dimension is approximated analytically. Second, Monte Carlo simulations show that the neglected dimension projects onto the other, with potentially disastrous results. Interestingly, dynamic models are bound to overestimate autoregressive behavior whenever the spatial dimension is important. The same holds true for the opposite case. An application using the well-known, openly available cigarette demand data supports these findings.

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