An evolutionary framework in modelling of multi-output characteristics of the bone drilling process

Garg, Akhil; Shankhwar, K.; Jiang, Dong; Vijayaraghavan, Vineeth; Panda, Biranchi; Panda, Sudhansu Sekhar

doi:10.1007/s00521-016-2632-x

Cited by 37 publications

(24 citation statements)

References 21 publications

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“…The findings and analysis from the proposed study can pave the way for assisting experts in making decisions on which battery to be reused, re‐manufactured, or recycled. Authors may consider using advanced optimization algorithms such as those based on evolutionary principles (genetic algorithms and particle swarm optimization) involving uncertainties in the design variables (stress, resistance, microstructure properties, etc) and compare findings with respect to the present work.…”

Section: Discussionmentioning

confidence: 99%

A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs

Garg

Liu

et al. 2019

Int J Energy Res

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Summary The present research proposes a combined framework that evaluates remaining capacity, material behavior, ions concentration of remaining metals, and current rate of chemical reactions of spent Li‐ion batteries accurately. Voltage, temperature, internal resistance, and capacity were studied during charging and discharging cycles. Genetic programming was applied on the obtained data to develop a model to predict remaining capacity. The results of experimental work and those estimated from model were found to be correlated, confirming the validation of model. Materials structure and electrochemical behavior of electrodes during cycles were studied by cyclic voltammetry, scanning electron microscopy, and energy dispersion spectrum.

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Section: Discussionmentioning

confidence: 99%

A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs

Garg

Liu

et al. 2019

Int J Energy Res

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“…However, the cost of the utilizing PEM fuel cells is high; this requires that the fuel cell should be used as efficiently as possible . Furthermore, the production and storage problem of H 2 should be solved for the operation . Researches in modeling of PEM fuel cell have begun in 1990s.…”

Section: Introductionmentioning

confidence: 99%

“…In different researches, operating parameters, viz, temperature, pressure, and current density, have been usually thought to be the main factors that influence the output power of PEMFC . Recently, a research has used a new methodology: moment‐based uncertainty evaluation technique, a framework which is accurate and reliable to study the influence of some uncontrollable factors, viz, SC, stack temperature (ST), oxygen excess ratio (OER), inlet air humidity (IAH), and hydrogen excess ratio (HER) . To some extent, these uncontrollable factors have a bad influence on the output power and operation of the fuel cell .…”

Section: Introductionmentioning

confidence: 99%

A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions

et al. 2019

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Summary The mechanisms in proton‐exchange membrane fuel cells (PEMFCs) cannot be explicitly represented by a mathematical function because the PEMFC system is multi‐dimensional and complex and represents uncertainty in operation variables, which cannot be modeled by experiments or by trial‐and‐error approach. Therefore, this work proposes to study the coupled and interactive influence of stack current (SC), stack temperature (ST), oxygen excess ratio (OER), hydrogen excess ratio (HER), and inlet air humidity (IAH) for optimizing the power output of PEMFC. The data obtained from the experiments have been inserted into architecture of automated neural‐network search, which automates the selection of error function, activation function, uncertainties in inputs and number of hidden neurons in formulation of a robust and accurate model for power density as a function of five operational variables. Among the operational variables, the correlation coefficient between the SC and the output power is the highest, followed by OER, and the ST. However, for HER and IAH, the power output follows negative nonlinear relation. The optimization converged at 130th iteration results in maximum power output of 3410 W for an optimum value of SC (51A), ST (59°C), OER (3:2), HER (1:10), and IAH (0.8).

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“…Moreover, the rate of increase in accuracy starts reducing when the order of the polynomial is up to a certain degree with the computation load grows exponentially. That is because a higher‐order polynomial involves much more unknown coefficients and thus requires more structural analyses …”

Section: Introductionmentioning

confidence: 99%

Experimental and artificial intelligence for determination of stable criteria in cyclic voltammetric process of medicinal herbs for biofuel cells

Chen

Srinivasan

et al. 2019

Int J Energy Res

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Summary This study proposed an expert system approach on the basis of artificial intelligence (AI) in the modeling of cyclic voltammogram (CV) profiles of green tea extracts. AI approach of artificial neural networks is applied to generate the model phase‐plane portraits of current output versus applied voltage through CV scan cycles. The predicted current values were validated using experiments, and generic ability of approach was examined by testing on the CV scan cycles generated from Syzygium aromaticum and Citrus reticulate. It was concluded that AI approach can be employed to reveal stable point (cycle and voltage) in CV profiles for bioenergy applications.

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An evolutionary framework in modelling of multi-output characteristics of the bone drilling process

Cited by 37 publications

References 21 publications

A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs

A combined experimental‐numerical framework for residual energy determination in spent lithium‐ion battery packs

A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions

Experimental and artificial intelligence for determination of stable criteria in cyclic voltammetric process of medicinal herbs for biofuel cells

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