The steel industry is among the highest carbon-emitting industrial sectors. Since the steel production process is already exhaustively optimized, alternative routes are sought in order to increase carbon efficiency and reduce these emissions. During steel production, three main carbon-containing off-gases are generated: blast furnace gas, coke oven gas and basic oxygen furnace gas. In the present work, the addition of renewable hydrogen by electrolysis to those steelworks off-gases is studied for the production of methane and methanol. Different case scenarios are investigated using AspenPlusTM flowsheet simulations, which differ on the end-product, the feedstock flowrates and on the production of power. Each case study is evaluated in terms of hydrogen and electrolysis requirements, carbon conversion, hydrogen consumption, and product yields. The findings of this study showed that the electrolysis requirements surpass the energy content of the steelwork’s feedstock. However, for the methanol synthesis cases, substantial improvements can be achieved if recycling a significant amount of the residual hydrogen.
This paper proposes a sEMG-based method for on-line torque prediction and control of robot joints. More in detail, the Mean Absolute Value (MAV) features extracted from the sEMG signals acquired from five muscles of the shoulder and of the elbow are used as input to two trained time delayed neural networks (TDNNs) to estimate the joint torque of an active exoskeleton robot for movements executed in the sagittal plane. The sEMG-driven TDNNs, trained with a dataset composed by shoulder and elbow joint torque values registered in isometric conditions, allow to on-line control the exoskeleton joints for slow movements of the upper limbs. Finally, the method was tested and validated through experiments conducted on a healthy subject
Within integrated steelmaking industries significant research efforts are devoted to the efficient use of resources and the reduction of CO2 emissions. Integrated steelworks consume a considerable quantity of raw materials and produce a high amount of by-products, such as off-gases, currently used for the internal production of heat, steam or electricity. These off-gases can be further valorized as feedstock for methane and methanol syntheses, but their hydrogen content is often inadequate to reach high conversions in synthesis processes. The addition of hydrogen is fundamental and a suitable hydrogen production process must be selected to obtain advantages in process economy and sustainability. This paper presents a comparative analysis of different hydrogen production processes from renewable energy, namely polymer electrolyte membrane electrolysis, solid oxide electrolyze cell electrolysis, and biomass gasification. Aspen Plus® V11-based models were developed, and simulations were conducted for sensitivity analyses to acquire useful information related to the process behavior. Advantages and disadvantages for each considered process were highlighted. In addition, the integration of the analyzed hydrogen production methods with methane and methanol syntheses is analyzed through further Aspen Plus®-based simulations. The pros and cons of the different hydrogen production options coupled with methane and methanol syntheses included in steelmaking industries are analyzed.
The European Steel industry is spending considerable efforts in order to improve the socio-economic and environmental sustainability of its processes by promoting any development, which can increase efficiency and lower the environmental impact of the steel production processes. In particular, the European iron and steel sector is strongly committed toward the reduction of energy consumptions and CO2 emissions. Process gases are a very valuable resource: possibilities exist to consider these gases as an intermediate by-product for the production of other valuable energy carriers or products with an associated environmental benefit. Therefore, the process gas networks, especially inside the integrated steelworks, have a fundamental function, as they allow meeting the demand of many processes and producing energy through dedicated facilities. They can also support the production processes by internal electric energy generation and often by supplying energy outside the plant boundaries. On the other hand, such networks are very complex systems interacting with many different production steps and the management of such complex systems is a very difficult task, where many often-counteracting factors need to be jointly taken into account. This paper presents the first outcomes of the research project entitled “Optimization of the management of the process gas network within the integrated steelworks (GASNET)”, which aims at developing a Decision Support System helping the energy managers and other concerned technical personnel to implement an optimized off-gases management and exploitation considering environmental and economic objectives. A series of Key Performance Indicators has been elaborated, in order to monitor the efficiency of the gas management and the objectives of the optimization have been defined. The overall structure of the project and the ongoing work will also be outlined in the paper.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.