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- Biollaz, S., et al.
(författare)
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Gas analysis in gasification of biomass and waste : Guideline report: Document 1
- 2018
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Rapport (refereegranskat)abstract
- Gasification is generally acknowledged as one of the technologies that will enable the large-scale production of biofuels and chemicals from biomass and waste. One of the main technical challenges associated to the deployment of biomass gasification as a commercial technology is the cleaning and upgrading of the product gas. The contaminants of product gas from biomass/waste gasification include dust, tars, alkali metals, BTX, sulphur-, nitrogen- and chlorine compounds, and heavy metals. Proper measurement of the components and contaminants of the product gas is essential for the monitoring of gasification-based plants (efficiency, product quality, by-products), as well as for the proper design of the downstream gas cleaning train (for example, scrubbers, sorbents, etc.). In practice, a trade-off between reliability, accuracy and cost has to be reached when selecting the proper analysis technique for a specific application. The deployment and implementation of inexpensive yet accurate gas analysis techniques to monitor the fate of gas contaminants might play an important role in the commercialization of biomass and waste gasification processes.This special report commissioned by the IEA Bioenergy Task 33 group compiles a representative part of the extensive work developed in the last years by relevant actors in the field of gas analysis applied to(biomass and waste) gasification. The approach of this report has been based on the creation of a team of contributing partners who have supplied material to the report. This networking approach has been complemented with a literature review. The report is composed of a set of 2 documents. Document 1(the present report) describes the available analysis techniques (both commercial and underdevelopment) for the measurement of different compounds of interest present in gasification gas. The objective is to help the reader to properly select the analysis technique most suitable to the target compounds and the intended application. Document 1 also describes some examples of application of gas analysis at commercial-, pilot- and research gasification plants, as well as examples of recent and current joint research activities in the field. The information contained in Document 1 is complemented with a book of factsheets on gas analysis techniques in Document 2, and a collection of video blogs which illustrate some of the analysis techniques described in Documents 1 and 2.This guideline report would like to become a platform for the reinforcement of the network of partners working on the development and application of gas analysis, thus fostering collaboration and exchange of knowledge. As such, this report should become a living document which incorporates in future coming progress and developments in the field.
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| 3. |
- Biollaz, S., et al.
(författare)
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Gas analysis in gasification of biomass and waste : Guideline report: Document 2 - Factsheets on gas analysis techniques
- 2018
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Rapport (refereegranskat)abstract
- Gasification is generally acknowledged as one of the technologies that will enable the large-scale production of biofuels and chemicals from biomass and waste. One of the main technical challenges associated to the deployment of biomass gasification as a commercial technology is the cleaning and upgrading of the product gas. The contaminants of product gas from biomass/waste gasification include dust, tars, alkali metals, BTX, sulphur-, nitrogen- and chlorine compounds, and heavy metals. Proper measurement of the components and contaminants of the product gas is essential for the monitoring of gasification-based plants (efficiency, product quality, by-products), as well as for the proper design of the downstream gas cleaning train (for example, scrubbers, sorbents, etc.). The deployment and implementation of inexpensive yet accurate gas analysis techniques to monitor the fate of gas contaminants might play an important role in the commercialization of biomass and waste gasification processes.This special report commissioned by the IEA Bioenergy Task 33 group compiles a representative part of the extensive work developed in the last years by relevant actors in the field of gas analysis applied to (biomass and waste) gasification. The approach of this report has been based on the creation of a team of contributing partners who have supplied material to the report. This networking approach has been complemented with a literature review. This guideline report would like to become a platform for the reinforcement of the network of partners working on the development and application of gas analysis, thus fostering collaboration and exchange of knowledge. As such, this report should become a living document which incorporates in future coming progress and developments in the field.
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| 4. |
- Tang, R., et al.
(författare)
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A literature review of Artificial Intelligence applications in railway systems
- 2022
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Ingår i: Transportation Research Part C. - : Elsevier Ltd. - 0968-090X .- 1879-2359. ; 140
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective, covering sub-domains such as maintenance and inspection, planning and management, safety and security, autonomous driving and control, revenue management, transport policy, and passenger mobility. This review makes an initial step towards shaping the role of AI in future railways and provides a summary of the current focuses of AI research connected to rail transport. We reviewed about 139 scientific papers covering the period from 2010 to December 2020. We found that the major research efforts have been put in AI for rail maintenance and inspection, while very limited or no research has been found on AI for rail transport policy and revenue management. The remaining sub-domains received mild to moderate attention. AI applications are promising and tend to act as a game-changer in tackling multiple railway challenges. However, at the moment, AI research in railways is still mostly at its early stages. Future research can be expected towards developing advanced combined AI applications (e.g. with optimization), using AI in decision making, dealing with uncertainty and tackling newly rising cybersecurity challenges.
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