Mechanical strength predictability of full factorial, Taguchi, and Box Behnken designs: Optimization of thermal settings and Cellulose Nanofibers content in PA12 for MEX AM

Vidakis, Nectarios; Petousis, Markos; Mountakis, Nikolaos; Papadakis, Vassilis; Moutsopoulou, Amalia

doi:10.1016/j.jmbbm.2023.105846

Cited by 29 publications

(15 citation statements)

References 85 publications

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“…The integration of active control, such as µ-analysis technologies, into smart structures has been the subject of the present work [4,36,40]. When utilizing the Hifoo controller in tandem with non-parametric and non-convex optimization methodologies, it ensures that the control output does not surpass operational constraints despite the desirable characteristics of low steady-state errors, rapid recovery, minimal maximum uplift, and reduced vibration, as outlined in [34,35,45].…”

Section: Discussionmentioning

confidence: 99%

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μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

Moutsopoulou,

Petousis,

Stavroulakis

et al. 2024

Algorithms

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In this study, we created an accurate model for a homogenous smart structure. After modeling multiplicative uncertainty, an ideal robust controller was designed using μ-synthesis and a reduced-order H-infinity Feedback Optimal Output (Hifoo) controller, leading to the creation of an improved uncertain plant. A powerful controller was built using a larger plant that included the nominal model and corresponding uncertainty. The designed controllers demonstrated robust and nominal performance when handling agitated plants. A comparison of the results was conducted. As an example of a general smart structure, the vibration of a collocated piezoelectric actuator and sensor was controlled using two different approaches with strong controller designs. This study presents a comprehensive simulation of the oscillation suppression problem for smart beams. They provide an analytical demonstration of how uncertainty is introduced into the model. The desired outcomes were achieved by utilizing Simulink and MATLAB (v. 8.0) programming tools.

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Section: Discussionmentioning

confidence: 99%

“…In addition, fe(t) can be defined as Bu(t) by expressing it as F * e u, where F * e (of size 2n × n) stands for the piezoelectric force for a unit established on the associated actuator [34][35][36], and u represents the voltages on the actuators [34][35][36]. Finally, d(t) = fm(t) denotes the disturbance vector.…”

Section: Application In Smart Structuresmentioning

confidence: 99%

μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

Moutsopoulou,

Petousis,

Stavroulakis

et al. 2024

Algorithms

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“…Additionally, to define f e (t) as Bu(t), we express it as F * e u, where F * e (of size 2n × n) is the piezoelectric force for a unit applied on the corresponding actuator, and u stands for the voltages on the actuators [40][41][42]. Lastly, d(t) = f m (t) is the disturbance vector.…”

Section: Application In Smart Structuresmentioning

confidence: 99%

Applications of the Order Reduction Optimization of the H-Infinity Controller in Smart Structures

Moutsopoulou,

Petousis,

Vidakis

et al. 2023

Inventions

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In this paper, our strategy is to look for locally optimum answers to a non-smooth optimization problem that has been constructed to include minimization goals and restrictions for smart structures’ vibration suppression. In both theoretical analysis and practical implementation, it is widely recognized that designing multi-objective control systems poses a considerable challenge. In this study, we assess the effectiveness of this method by employing the open-source Matlab toolbox Hifoo 2.0 and juxtapose our findings with established industry standards. We start by framing the control problem as a mathematical optimization issue and proceed to identify the controller that effectively addresses this optimization. This approach introduces the potential application of intelligent structures in tackling the challenge of vibration suppression. This study makes use of the most recent version of the freely available application Hifoo which tries to study vibration suppression with the limits outlined above in the context of multi-objective controller design. A controller directive is initially set, allowing for a lower order.

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“…Although slightly larger, the data were still considered reliable. [49][50][51][52][53][54] F I G U R E 3 Curves of temperature, pressure, and displacement with sintering time of composite under the optimal sintering process.…”

Section: Influence Of Sps Process Parameters On the Density And Hardn...mentioning

confidence: 99%

The effect of spark plasma sintering parameters on the densification and mechanical properties of TiB₂‐TiC‐TiB composites

Liu

Zhang

Jia

et al. 2023

Int J Applied Ceramic Tech

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Spark plasma sintering (SPS) tests were designed using the Taguchi method to create high‐performance composites consisting of 60 wt% TiB2, 30 wt% TiC, and 10 wt% Ti. The effects of SPS parameters on the microstructure and mechanical properties of TiB2‐TiC‐TiB composites were systematically investigated. Additionally, the evolution of phase and microstructure during the densification of the composites was analyzed in detail. It has been demonstrated that composites can achieve a high relative density of 99.8%, a hardness of 22.2 GPa, a strength of 739 MPa, and a fracture toughness of 7.07 MPa m1/2, as well as a dense structure and small grain size. These properties can be obtained by sintering at a temperature of 1500°C, a pressure of 50 MPa, and a holding time of 5 min. Sintering temperature is the primary factor that promotes the densification of the composite and influences its relative density, grain size, and morphology. Holding time and sintering pressure are relatively minor factors, but they play important roles at different stages of the sintering process.

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Mechanical strength predictability of full factorial, Taguchi, and Box Behnken designs: Optimization of thermal settings and Cellulose Nanofibers content in PA12 for MEX AM

Cited by 29 publications

References 85 publications

μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

Applications of the Order Reduction Optimization of the H-Infinity Controller in Smart Structures

The effect of spark plasma sintering parameters on the densification and mechanical properties of TiB₂‐TiC‐TiB composites

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Mechanical strength predictability of full factorial, Taguchi, and Box Behnken designs: Optimization of thermal settings and Cellulose Nanofibers content in PA12 for MEX AM

Cited by 29 publications

References 85 publications

μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

μ-Analysis and μ-Synthesis Control Methods in Smart Structure Disturbance Suppression with Reduced Order Control

Applications of the Order Reduction Optimization of the H-Infinity Controller in Smart Structures

The effect of spark plasma sintering parameters on the densification and mechanical properties of TiB2‐TiC‐TiB composites

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Product

Resources

About

The effect of spark plasma sintering parameters on the densification and mechanical properties of TiB₂‐TiC‐TiB composites