Bistable morphing composites have shown promising applications in energy harvesting due to their capabilities to change their shape and maintain two different states without any external loading. In this review article, the application of these composites in energy harvesting is discussed. Actuating techniques used to change the shape of a composite structure from one state to another is discussed. Mathematical modeling of the dynamic behavior of these composite structures is explained. Finally, the applications of artificial-intelligence techniques to optimize the design of bistable structures and to predict their response under different actuating schemes are discussed.

https://www.mdpi.com/2073-4360/14/9/1893/pdf?version=1651762488

Bistable Morphing Composites for Energy-Harvesting Applications

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American Society of Mechanical Engineers (ASME)

Vibration analysis of FGM plates in thermal environment resting on elastic foundation using ES-MITC3 element and prediction of ANN

The drying mechanism of the myristicin enriched nutmeg mace has been optimized in a microwave assisted fluidization bed dryer (MWFBD) through multiple linear regression (MLR) and artificial neural network (ANN) modeling. The developed drying technique overcomes the non-uniformity heating problems in microwave heating and prolonged drying in fluidized bed drying. During the novel method of drying selected input variables were drying air temperature (DT) (40–50 °C) and microwave power (MP) (480–800 W) and output variables involving colour, oil yield, and myristicin quantity have been investigated by a continuous air velocity of 5.1 m/s. Six mathematical models about one to four conditions have fitted with an experimental design. Suitable enforcement of such models was evaluated through statistical measures. The coefficient of determination (R2) of MLR varied from 0.89 to 0.98, and the sum of squared error (SSE) varied within 6 × 10−3 to 158.18, while R2 of ANN fluctuated from 0.82 to 0.95, and the mean squared error (MSE) varied between 0.006 and 0.1450, which shows MLR design performance superior than ANN design. The processing conditions of 48.24 °C DT and 637.431 W MP with a drying time of 1.3 h were identified as optimum conditions with a desirability value of 0.98 to obtain maximum oil yield (13.38%) and good colour (L* (20.83), a* (17.34), b* (8.62)) of nutmug mace. Moreover, no myristicin (5.92%) degradation was observed compared with the sun and convective drying. Among the tested models, page and logarithmic models gave a better prediction of moisture ratio.

Microwave assisted fluidized bed drying of nutmeg mace for essential oil enriched extracts: An assessment of drying kinetics, process optimization and quality

This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time.

Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS

A multi-response optimal design of bistable compliant mechanism using efficient approach of desirability, fuzzy logic, ANFIS and LAPO algorithm

This paper proposes an efficient hybrid approach for solving multi-objective optimization design of a compliant mechanism. The approach is developed by integrating desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system, and Lightning attachment procedure optimization. Box–Behnken design is used to form a numerically experimental matrix. First, a refinement of design variables is conducted through analysis of variance and Taguchi approach in terms of considerably eliminating space of design variables and computation efforts. Next, desirability of two objective functions is computed and transferred into the fuzzy logic system. The output of fuzzy logic system is regarded as single combined objective function. Subsequently, a modeling for fuzzy output is developed via adaptive neuro-fuzzy inference system. Then, LAPO algorithm is adopted for solving the optimization problem. By investigating three different numerical examples, performance of the proposed approach is validated. Numerical results revealed that the proposed approach has a computational accuracy better than that of Taguchi-based fuzzy logic reasoning. Finally, case study 1 is chosen as an optimal solution for the mechanism. Furthermore, the effectiveness of proposed approach is greater than that of the Jaya algorithm and TLBO algorithm through Wilcoxon signed rank test and Friedman test. The proposed approach can be used for related engineering fields.

An effective hybrid approach of desirability, fuzzy logic, ANFIS and LAPO algorithm for optimizing compliant mechanism

This study proposes a combination of kinematics-based design method, statistic method, and TLBO algorithm to solve computing optimization for a compliant gripper. It is employed in an assembly system of mini direct current motor. First, the kinematic models of the gripper are developed. The static model is paid attention. Next, the dynamic model is established based on Lagrange's principle. Then, a multi-criteria optimization for the gripper is conducted by Taguchi method integrated with TLBO algorithm. Finally, the FEA and experiments are implemented to verify the optimal results and evaluate the performances of the compliant gripper. The results indicated that theoretical models are in good accord with the results from simulations and experiments. Additionally, the performance of the present method is superior to PSO algorithm. The results revealed that the compliant gripper allows a displacement up to 3000 µm and the amplification ratio of 12 times. The compliant gripper is a potential application for the mini direct-current motor assembly system.

Analytical Model and Computing Optimization of a Compliant Gripper for the Assembly System of Mini Direct-Current Motor

Flexure-based compliant mechanisms are increasingly promising in precision engineering, robotics, and other applications, thanks to the excellent advantages of no friction, no backlash, no wear, and minimal assembly. However, their design and analysis are still challenging due to the coupling of kinematic-mechanical behaviors with large nonlinear deflections in comparison to their rigid-body counterparts. Optimal design is an important aspect in the field of compliant mechanisms and has attracted much attention during the last decades. Especially, when considering a multiobjective optimization design for compliant mechanisms, the problem is becoming more complicated. Thus, this article presents a new efficient hybrid computational method to resolve multiobjective optimization design of compliant mechanisms. A Scott Russell compliant mechanism is employed as the design example and to show the advantages of the proposed optimizing method. The proposed method is developed by hybridizing the desirability function approach, fuzzy logic system, adaptive neuro-fuzzy inference system (ANFIS), and lightning attachment procedure optimization (LAPO). First of all, a 3D finite element model is created and central composite design is employed to build a numerical matrix. First, design variables are refined by using analysis of variance and Taguchi approach in terms of considerably eliminating space of design variables. Subsequently, desirability values of two objective functions are determined and transferred into the fuzzy logic system. The output of the fuzzy logic system is considered as a single combined objective function. Next, modeling for fuzzy output is established via developing the ANFIS model. At last, the LAPO algorithm is adopted for solving the multiobjective optimization problem for the mechanism. Three numerical examples are investigated to validate the feasibility and the effectiveness of performance efficiency of the proposed methodology. The results find that the proposed methodology is more efficient than traditional Taguchi-based fuzzy logic. Besides, the performance efficiency of the proposed approach outperforms the Jaya algorithm and TLBO algorithm through the Wilcoxon signed rank test and Friedman test. The results of this article give a useful approach for complex optimization problems.

/pdf/a-hybrid-computational-method-of-desirability-fuzzy-logic-56onrff930.pdf

A Hybrid Computational Method of Desirability, Fuzzy Logic, ANFIS, and LAPO Algorithm for Multiobjective Optimization Design of Scott Russell Compliant Mechanism

In order to permit a large deflection, three lamina emergent torsional flexure hinges are reconfigured to create a new triple LET-type flexure hinge (TLET) in this paper. The TLET consists of flexure hinges in a series coupled with others in parallel configuration. This arrangement is aimed to enhance the displacement of the joint. The proposed joint is capable of generating a large displacement and a large capacity of load within safety working conditions. The closed-form models are derived to calculate the equivalent spring constant, rotation angle, and displacement of the proposed joint. Failure analysis of the TLET joint with different materials is conducted by finite element analysis. The closed-form models are validated by simulations and experimentations. The validated results are well coincided each other. The result found that the joint achieves a maximum large displacement of 16.97 mm in the x-axis with respect to a maximum load of 20 N. When the joint slides a maximum displacement of 16.97 mm along the x-axis, the output displacement emerges out the z-axis up to 23.12 mm, respectively. The joint can achieve an angle displacement of 38.92°. The displacement of the TLET joint is 2.4 times greater than that of the traditional LET joint. The proposed joint is considered for engineering applications where a large working stroke and a large capacity of load are expected.

/pdf/design-and-performance-analysis-of-a-tlet-type-flexure-hinge-3rvwjv2u83.pdf

Ngoc Thoai Tran

Papers

A multi-response optimal design of bistable compliant mechanism using efficient approach of desirability, fuzzy logic, ANFIS and LAPO algorithm

An effective hybrid approach of desirability, fuzzy logic, ANFIS and LAPO algorithm for optimizing compliant mechanism

Analytical Model and Computing Optimization of a Compliant Gripper for the Assembly System of Mini Direct-Current Motor

A Hybrid Computational Method of Desirability, Fuzzy Logic, ANFIS, and LAPO Algorithm for Multiobjective Optimization Design of Scott Russell Compliant Mechanism

Design and Performance Analysis of a TLET-Type Flexure Hinge