Operationalization

Summary

In research design, especially in psychology, social sciences, life sciences and physics, operationalization or operationalisation is a process of defining the measurement of a phenomenon which is not directly measurable, though its existence is inferred from other phenomena. Operationalization thus defines a fuzzy concept so as to make it clearly distinguishable, measurable, and understandable by empirical observation. In a broader sense, it defines the extension of a concept—describing what is and is not an instance of that concept. For example, in medicine, the phenomenon of health might be operationalized by one or more indicators like body mass index or tobacco smoking. As another example, in visual processing the presence of a certain object in the environment could be inferred by measuring specific features of the light it reflects. In these examples, the phenomena are difficult to directly observe and measure because they are general/abstract (as in the example of health) or they are latent (as in the example of the object). Operationalization helps infer the existence, and some elements of the extension, of the phenomena of interest by means of some observable and measurable effects they have. Sometimes multiple or competing alternative operationalizations for the same phenomenon are available. Repeating the analysis with one operationalization after the other can determine whether the results are affected by different operationalizations. This is called checking robustness. If the results are (substantially) unchanged, the results are said to be robust against certain alternative operationalizations of the checked variables. The concept of operationalization was first presented by the British physicist N. R. Campbell in his 'Physics: The Elements' (Cambridge, 1920). This concept spread to humanities and social sciences. It remains in use in physics. Operational definition and Theoretical definition Operationalization is the scientific practice of operational definition, where even the most basic concepts are defined through the operations by which we measure them.

Official source

https://en.wikipedia.org/wiki/Operationalization

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Adaptive structures modify their geometry and internal forces through sensing and mechanical actuation in order to maintain optimal performance under changing actions. Previous work has shown that well-conceived adaptive design strategies achieve substantial whole-life energy savings compared to traditional passive designs. The whole-life energy comprises an embodied part in the material and an operational part for structural adaptation This thesis presents a new method to design adaptive structures capable of large and reversible shape changes achieved through actuation. To this end, linear actuators are strategically fitted within selected elements of reticular (e.g. trusses and frames) structures. Structural adaptation through controlled large shape changes allows a significant stress redistribution so that the design is not governed by extreme loads with long return periods. This way, material utilization is maximized and thus, embodied energy is reduced. A set of target shapes that counteract the effect of peak loads are first obtained through geometry and sizing optimization. Strategies have been developed to reduce the uncertainty due to the presence of multiple local minima so that the computational efficiency is improved and the convergence is guaranteed. A method is formulated to obtain a suitable actuator layout in order to control the structure into the target shapes. This is a challenging task due to the combinatorial nature of the actuator placement process which, in this case, includes geometric nonlinearity. A heuristic for near-neighbor generation based on the actuator control efficacy is employed to explore effectively the large search space. The heuristic has significantly improved convergence, which is important for structures with complex topologies that are made of many elements. A framework for real-time control combining shape optimization and nonlinear force method is proposed. The objective of the control framework is to minimize the operational energy for shape adaptation while satisfying stress and element buckling limits. A linear-sequential formulation is presented, allowing a computationally-efficient implementation of real-time shape control through a mechanics-based formulation. Through a nested univariate optimization scheme, an adaptive structure with minimum whole-life energy requirements is synthesized. Numerical case studies demonstrate that whole-life energy savings can be achieved compared to weight-optimized passive structures for the configurations studied in this thesis. Structures that adapt to loading through large shape changes achieve marginal whole-life energy savings with respect to structures that adapt to loading through small shape changes. Nevertheless, significant embodied energy (and thus material mass) savings are achieved with respect to weight-optimized passive structures as well as to structures that adapt through small shape changes. Experimental studies at various scales are carried out to verify numerical findings and investigate the feasibility of the design method. Experimental testing has demonstrated that significant stress homogenization through large-shape changes is achievable. The control framework allows for real-time shape adaptation to achieve stress homogenization under various loading conditions. An energy appraisal carried out on a near-full-scale prototype confirms that considerable savings of the total energy can be achieved by adaptive solutions.

EPFL2020

Force and Shape Control Strategies for Minimum Energy Adaptive Structures

Gennaro Senatore, Arka Prabhata Reksowardojo

This work presents force and shape control strategies for adaptive structures subjected to quasi-static loading. The adaptive structures are designed using an integrated structure-control optimization method developed in previous work, which produces minimum “whole-life energy” configurations through element sizing and actuator placement optimization. The whole-life energy consists of an embodied part in the material and an operational part for structural adaptation during service. Depending on the layout, actuators are placed in series with the structural elements (internal) and/or at the supports (external). The effect of actuation is to modify the element forces and node positions through length changes of the internal actuators and/or displacements of the active supports. Through active control, the stress is homogenized and the displacements are kept within required limits so that the design is not governed by peak demands. Actuation has been modeled as a controlled non-elastic strain distribution, here referred to as eigenstrain. Any eigenstrain can be decomposed into two parts: an impotent eigenstrain only causes a change of geometry without altering element forces while a nilpotent eigenstrain modify element forces without causing displacements. Four control strategies are formulated: (C1) force and shape control to obtain prescribed changes of forces and node positions; (C2) shape control through impotent eigenstrain when only displacement compensation is required without affecting the forces; (C3) force control through nilpotent eigenstrain when displacement compensation is not required; and (C4) force and shape control through operational energy minimization. Closed-form solutions to decouple force and shape control through nilpotent and impotent eigenstrain are given. Simulations on a slender high-rise structure and an arch bridge are carried out to benchmark accuracy and energy requirements for each control strategy and for different actuator configurations that include active elements, active supports and a combination of both.

2020

Force and Shape Control Strategies for Minimum Energy Adaptive Structures

Gennaro Senatore, Arka Prabhata Reksowardojo

2020

EPFL2020