Mechanisms as Components of Dynamic Systems: A Bond Graph Approach

1977 ◽  
Vol 99 (1) ◽  
pp. 104-111 ◽  
Author(s):  
R. R. Allen ◽  
S. Dubowsky
Keyword(s):  
Dynamic Systems ◽  
Bond Graph ◽  
General Mechanism ◽  
Kinematics And Dynamics ◽  
Bond Graphs ◽  
Complex Dynamic ◽  
Automatic Computation ◽  
Mechanism Model ◽  
Complex Dynamic Systems ◽  
System Variables

In recent years, bond graphs have been used to analyze complex dynamic systems. In this paper a bond graph study is made of the kinematics and dynamics of a general mechanism treated as a component of a dynamic system. The method is applicable to multiple-loop, multiple degree-of-freedom mechanisms for which the displacement and velocity loop equations are known. A bond graph multiport representing the kinematic relations forms a power-conserving core to which dissipative, inertial, and compliance effects may be added to form a dynamic mechanism model. A constitutive relation suitable for automatic computation is derived in terms of system variables. A numerical example is presented illustrating an application of the technique.

scholarly journals Variability as normal as apple pie

2021 ◽  
Vol 7 (s2) ◽  
Author(s):  
Marjolijn Verspoor ◽  
Wander Lowie ◽  
Kees de Bot
Keyword(s):  
Dynamic Systems ◽  
Dynamic Systems Theory ◽  
Complex Dynamic ◽  
Controlled Processes ◽  
Complex Dynamic Systems ◽  
L2 Development ◽  
Limited Degree ◽  
Development Phases ◽  
Longitudinal Case Studies ◽  
Over Time

Abstract In recent studies in second language (L2) development, notably within the focus of Complex Dynamic Systems Theory (CDST), non-systematic variation has been extensively studied as intra-individual variation, which we will refer to as variability. This paper argues that variability is functional and is needed for development. With examples of four longitudinal case studies we hope to show that variability over time provides valuable information about the process of development. Phases of increased variability in linguistic constructions are often a sign that the learner is trying out different constructions, and as such variability can be evidence for change, and change can be learning. Also, a limited degree of variability is inherent in automatic or controlled processes. Conversely, the absence of variability is likely to show that no learning is going on or the system is frozen.

Toward a transdisciplinary integration of research purposes and methods for complex dynamic systems theory: beyond the quantitative–qualitative divide

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Phil Hiver ◽  
Ali H. Al-Hoorie ◽  
Diane Larsen-Freeman
Keyword(s):  
Systems Theory ◽  
Dynamic Systems ◽  
Applied Linguistics ◽  
Integrated Approach ◽  
Dynamic Systems Theory ◽  
Complex Dynamic ◽  
Transdisciplinary Approach ◽  
Complex Dynamic Systems ◽  
Human And Social Sciences ◽  
Starting Point

Abstract Complexity theory/dynamic systems theory has challenged conventional approaches to applied linguistics research by encouraging researchers to adopt a pragmatic transdisciplinary approach that is less paradigmatic and more problem-oriented in nature. Its proponents have argued that the starting point in research design should not be the quantitative–qualitative distinction, or even mixed methods, but the distinction between individual versus group-based designs (i.e., idiographic versus nomothetic). Taking insights from transdisciplinary complexity research in other human and social sciences, we propose an integrative transdisciplinary framework that unites these different perspectives (quantitative–qualitative, individual–group based) from the starting point of exploratory–falsificatory aims. We discuss the implications of this transdisciplinary approach to applied linguistics research and illustrate how such an integrated approach might be implemented in the field.

Use of Measured Mobility to Improve SEA Predictions in the Mid-Frequency Range

1999 ◽  
Author(s):  
Jerome E. Manning
Keyword(s):  
Dynamic Systems ◽  
Broad Band ◽  
Measured Data ◽  
Hybrid Technique ◽  
Complex Dynamic ◽  
Low Frequencies ◽  
Large Variability ◽  
High Frequencies ◽  
Complex Dynamic Systems ◽  
Light Coupling

Abstract Statistical energy analysis provides a technique to predict acoustic and vibration levels in complex dynamic systems. The technique is most useful for broad-band excitation at high frequencies where many modes contribute to the response in any given frequency band. At mid and low frequencies, the number of modes contributing to the response may be quite small. In this case SEA predictions show large variability from measured data and may not be useful for vibroacoustic design. This paper focuses on the use of measured data to improve the accuracy of the predictions. Past work to measure the SEA coupling and damping loss factors has not been successful for a broad range of systems that do not have light coupling. This paper introduces a new hybrid SEA technique that combines measured mobility functions with analytical SEA predictions. The accuracy of the hybrid technique is shown to be greatly improved at mid and low frequencies.

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