Theories and Methodologies

Ahmadian, Amir Sharif

doi:10.1016/b978-0-12-802413-3.00004-3

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…The feedforward method calculates the weights and biases of the Neural Network by employing the Levenberg-Marquardt optimisation method 35,36 in order to minimise the following objective function:…”

Section: Modelling Methods and Toolsmentioning

confidence: 99%

A novel methodology for marine dual fuel engines sensors diagnostics and health management

Stoumpos

Theotokatos

2021

International Journal of Engine Research

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The sensors abnormalities, faults, failure detection and diagnosis for marine engines are considered crucial for ensuring the engine safe and smooth operation. The development of such system(s) is typically based on the manufacturers experience on sensors and actuators faults and failure events. This study aims to introduce a novel methodology for the sensors diagnostics and health management in marine dual fuel engines by employing a combination of thermodynamic, functional control and data-driven models. The concept of an Engine Diagnostics System (EDS) is developed to provide intelligent engine monitoring, advanced sensors’ faults detection as well as timely and profound corrective actions. This system employs a neural networks (NN) Data-Driven (DD) model along with appropriate logic controls. The DD model is set up based on the derived steady state data from a thermodynamic model of high fidelity and is capable of real-time prediction of the engine health condition behaviour. The concept of a novel Unified Digital System (UDS) is proposed that combines the engine’s existing control and diagnostic systems with the EDS. The functionality of the UDS system is validated by employing a digital twin of the considered marine dual fuel engine by investigating scenarios for assessing the engine performance that entail abnormalities in the engine’s speed and boost pressure sensors. The simulation results demonstrate that the developed UDS is capable of sufficiently capturing the engine’s sensors abnormalities and applying appropriate corrective actions to restore the engine operation in its original state. This study benefits the development future systems facilitating the engines condition assessment and self-correction of the engine sensors’ abnormalities, which will be required for smart and autonomous shipping.

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Section: Modelling Methods and Toolsmentioning

confidence: 99%

A novel methodology for marine dual fuel engines sensors diagnostics and health management

Stoumpos

Theotokatos

2021

International Journal of Engine Research

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“…This is a hybrid optimization technique that uses both Gauss–Newton and steepest descent approaches to converge to an optimal solution [ 21 ]. It takes advantage of the high speed of the Gauss–Newton algorithm and the high stability of the steepest descent method [ 22 ]. In this work, the algorithm finds the best set of unknown parameters in order to minimize error between the response variable (environmental impacts obtained from the non-linear functions) and the actual values (actual observations of the response).…”

Section: Methodsmentioning

confidence: 99%

Non-Linear Regression Modelling to Estimate the Global Warming Potential of a Newspaper

Lozano

Cabrera

Blanco-Marigorta

2020

Entropy

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Technological innovations are not enough by themselves to achieve social and environmental sustainability in companies. Sustainable development aims to determine the environmental impact of a product and the hidden price of products and services through the concept of radical transparency. This means that companies should show and disclose the impact on the environment of any good or service. This way, the consumer can choose in a transparent manner, not only for the price. The use of the eco-label as a European eco-label, which bases its criteria on life cycle assessment, could provide an indicator of corporate social responsibility for a given product. However, it does not give a full guarantee that the product was obtained in a sustainable manner. The aim of this work is to provide a way of calculating the value of the environmental impacts of an industrial product, under different operating conditions, so that each company can provide detailed information on the impacts of its products, information that can form part of its "green product sheet". As a case study, the daily production of a newspaper, printed by coldset, has been chosen. Each process involved in production was configured with raw material and energy consumption information from production plants, manufacturer data and existing databases. Four non-linear regression models have been trained to estimate the impact of a newspaper’s circulation from five input variables (pages, grammage, height, paper type, and print run) with 5508 data samples each. These non-linear regression models were trained using the Levenberg–Marquardt nonlinear least squares algorithm. The mean absolute percentage errors (MAPE) obtained by all the non-linear regression models tested were less than 5%. Through the proposed correlations, it is possible to obtain a score that reports on the impact of the product for different operating conditions and several types of raw materials. Ecolabelling can be further developed by incorporating a scoring system for the impact caused by the product or process, using a standardised impact methodology.

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Theories and Methodologies

Cited by 2 publications

References 28 publications

A novel methodology for marine dual fuel engines sensors diagnostics and health management

A novel methodology for marine dual fuel engines sensors diagnostics and health management

Non-Linear Regression Modelling to Estimate the Global Warming Potential of a Newspaper

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