Optimization of the Biomethane Production Process by Anaerobic Digestion of Wheat Straw Using Chemical Pretreatments Coupled with Ultrasonic Disintegration

Ouahabi, Yasmine Ryma; Bensadok, K.; Ouahabi, Abdeldjalil

doi:10.3390/su13137202

Cited by 24 publications

(17 citation statements)

References 51 publications

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“…The industrial revolution led to a transition to a fossil fuel-dominated energy mix led by coal and later petroleum products like diesel and natural gas. The early 1970s to late 1980s witnessed a high increase in oil price which necessitated the search and development of renewable, sustainable, and environmentally friendly sources with biogas being among the top sources of alternative energy [46][47][48]. According to [49], there is a need to conserve the environment and dispose of wastes in an eco-friendly manner to prevent environmental degradation and greenhouse gas emissions.…”

Section: Introductionmentioning

confidence: 99%

Biogas Production and Applications in the Sustainable Energy Transition

2022

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Biogas is competitive, viable, and generally a sustainable energy resource due to abundant supply of cheap feedstocks and availability of a wide range of biogas applications in heating, power generation, fuel, and raw materials for further processing and production of sustainable chemicals including hydrogen, and carbon dioxide and biofuels. The capacity of biogas based power has been growing rapidly for the past decade with global biogas based electricity generation capacity increasing from 65 GW in 2010 to 120 GW in 2019 representing a 90% growth. This study presents the pathways for use of biogas in the energy transition by application in power generation and production of fuels. Diesel engines, petrol or gasoline engines, turbines, microturbines, and Stirling engines offer feasible options for biogas to electricity production as prme movers. Biogas fuel can be used in both spark ignition (petrol) and compression ignition engines (diesel) with varying degrees of modifications on conventional internal combustion engines. In internal combustion engines, the dual-fuel mode can be used with little or no modification compared to full engine conversion to gas engines which may require major modifications. Biogas can also be used in fuel cells for direct conversion to electricity and raw material for hydrogen and transport fuel production which is a significant pathway to sustainable energy development. Enriched biogas or biomethane can be containerized or injected to gas supply mains for use as renewable natural gas. Biogas can be used directly for cooking and lighting as well as for power generation and for production of Fischer-Tropsch (FT) fuels. Upgraded biogas/biomethane which can also be used to process methanol fuel. Compressed biogas (CBG) and liquid biogas (LBG) can be reversibly made from biomethane for various direct and indirect applications as fuels for transport and power generation. Biogas can be used in processes like combined heat and power generation from biogas (CHP), trigeneration, and compression to Bio-CNG and bio-LPG for cleaned biogas/biomethane. Fuels are manufactured from biogas by cleaning, and purification before reforming to syngas, and partial oxidation to produce methanol which can be used to make gasoline. Syngas is used in production of alcohols, jet fuels, diesel, and gasoline through the Fischer-Tropsch process.

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Section: Introductionmentioning

confidence: 99%

Biogas Production and Applications in the Sustainable Energy Transition

2022

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“…In this study, the analysis of the ultrasonic wave propagation [24][25][26] is performed using 2 sensors located on opposite sides of the analyzed specimen (see Figures 4 and 5).…”

Section: Ndt Methodsmentioning

confidence: 99%

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

et al. 2021

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In this paper, we propose a new methodology for crack detection and monitoring in concrete structures. This approach is based on a multiresolution analysis of a sample or a specimen of concrete material subjected to several types of solicitation. The image obtained by ultrasonic investigation and processed by a customized wavelet is analyzed at various scales in order to detect internal cracks and crack initiation. The ultimate objective of this work is to propose an automatic crack type identification scheme based on convolutional neural networks (CNN). In this context, crack propagation can be monitored without access to the concrete surface and the goal is to detect cracks before they are visible. This is achieved through the combination of two major data analysis tools which are wavelets and deep learning. This original procedure is shown to yield a high accuracy close to 90%. In order to evaluate the performance of the proposed CNN architectures, we also used an open access database, SDNET2018, for the automatic detection of external cracks.

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“…ultrasound) or pull-off methods [24] which are semi-destructive. In the second category, the techniques are much more numerous: we can mention, among others, acoustic methods [25,26] (e.g. acoustic emission, echo, ultrasonic, impact echo), electromagnetic methods [27] (e.g.…”

Section: Ultrasonic Tests On Concrete Specimensmentioning

confidence: 99%

Wavelet-based multiresolution analysis coupled with deep learning to efficiently monitor cracks in concrete

Arbaoui

Ouahabi

Jacques

et al. 2021

Frattura Ed Integrità Strutturale

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This paper proposes an efficient methodology to monitor the formation of cracks in concrete after non-destructive ultrasonic testing of a structure. The objective is to be able to automatically detect the initiation of cracks early enough, i.e. well before they are visible on the concrete surface, in order to implement adequate maintenance actions on civil engineering structures. The key element of this original approach is the wavelet-based multiresolution analysis of the ultrasonic signal received from a sample or a specimen of the studied material subjected to several types of solicitation. This analysis is finally coupled to an automatic identification scheme of the types of cracks based on artificial neural networks (ANNs), and in particular deep learning by convolutional neural networks (CNNs); a technology today at the cutting edge of machine learning, in particular for all applications of pattern recognition. Wavelet-based multiresolution analysis does not add any value in detecting fractures in concrete visible by optical inspection. However, the results of its implementation coupled with different CNN architectures show cracks in concrete can be identified at an early stage with a very high accuracy, i.e. around 99.8%, and a loss function of less than 0.1, regardless of the implemented learning architecture.

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Optimization of the Biomethane Production Process by Anaerobic Digestion of Wheat Straw Using Chemical Pretreatments Coupled with Ultrasonic Disintegration

Cited by 24 publications

References 51 publications

Biogas Production and Applications in the Sustainable Energy Transition

Biogas Production and Applications in the Sustainable Energy Transition

Concrete Cracks Detection and Monitoring Using Deep Learning-Based Multiresolution Analysis

Wavelet-based multiresolution analysis coupled with deep learning to efficiently monitor cracks in concrete

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