Material and energy flows of the iron and steel industry: status quo, challenges and perspectives

Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flow research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

Doctor of Philosophy

dissertationThis work details an investigation of how to modify slag flow so as to maintain a clear line of sight across the reaction section of an entrained-flow coal gasifier. Physical and computational models were developed to study methods of diverting the molten slag that flows vertically down the walls of the reactor. The physical models employed silicone oil of varying viscosity. The computational models were developed using the Fluent software package. Based on the insight gained from the results of the models, two devices were created and tested in a pilot scale gasifier located at the University of Utah. The first method of slag diversion studied employed a gas jet to impact the slag film and cause it to flow around a sight port in the gasifier wall. By studying the film and jet interactions, it was discovered that the resulting behavior of such a system can be described by a dimensionless ratio of the kinetic energy of the jet and the surface energy of the film. The development of the dimensionless number, called a Lotte number in this work, is presented in detail. Generally, viscous films will be broken by a jet when the Lotte number is greater than 5 and will reclose when the Lotte number falls below a value of 1.5. The second slag diversion method studied used a round alumina tube protruding horizontally into the reaction section to break up the film. As the film impacts the tube, it progresses horizontally along the length of the tube before resuming the downward flow

Development and application of a rapid sampling technique for identification and quantification of compounds in high temperature process gas streams produced from biomass gasification and pyrolysis

A commercially applicable measurement technique for measuring volatile organic compounds (VOCs) in hot process gas streams was developed. The method was validated by quantifying the amount tar in a syngas stream generated from a pilot-scale gasification reactor and gas cleaning process development unit (PDU) and comparing the value to that of conventional measurements. Conventional approaches to measuring VOCs suffer from extensive amounts of equipment and require substantial preparation time in the lab before data are recovered. This makes them impractical for use in rapid process monitoring and drastically inhibits attempts to optimize new tar removal techniques for syngas. The novel method is capable of sampling directly from process piping and provides results within the time-resolution of the analytical equipment (typically 1-2 h for mass spectrometry or flame ionization detection). The method is based on time-weighted average solid-phase microextraction (TWA-SPME) theory. Testing the theory on a lab scale system for the analytes of interest (benzene, toluene, styrene, indene, and naphthalene) yielded important limitations to the technique using high temperature (\u3e115C) process environments. The TWA-SPME method was applied on the pilot-scale (20 kg/h of switchgrass feed) PDU within appropriate sample extraction conditions dictated by the lab-scale testing. The method returned results within 10% of the conventional impinger approach for most analytes, and within 20% for all analytes downstream of the gas cleaning unit. When coupled with a new rapid measurement technique for heavy tar using a pressure cooker, the new method is capable of providing the concentration of tar for any syngas stream in an hour or less compared to the conventional method that requires several days for wet-chemical analysis. Additional applications of the technique are currently underway including the measurement of key light VOCs generated in a free-fall pyrolysis reactor in an attempt to gain valuable process kinetics data. An extension of this research is based on the development of a method for measurement of VOCs at much higher temperatures (exceeding 300C) using an internally-cooled SPME fiber

Hardened concrete properties and durability assessment of high volume fly ash concrete

Concrete is produced more than any other material in the world. Sustainable construction is extremely important in today\u27s industry and fly ash is the leading material for sustainable concrete design. The addition of fly ash improves many fresh and hardened concrete properties. However, the slow hydration process associated with fly ash makes the use of the material in large amounts undesirable in conventional construction. This study evaluated the hardened concrete and durability performance of several high-volume fly ash (HVFA) concrete mixes. The various HVFA concrete mixes evaluated within this study consisted of 70 percent replacement of portland cement by weight of cementitious material and water-to-cementitious ratios (w/cm) ranging from 0.30 to 0.45. Studies were conducted on hardened properties including: compressive strength, flexural strength, splitting tensile strength, and modulus of rupture. A shrinkage analysis was also performed to evaluate drying and free shrinkage. The durability performance of the HVFA concrete was also evaluated. Results obtained from the tests revealed that compressive strengths of HVFA concrete are comparable to portland cement concrete with a reduced w/cm. Also, a reduction in concrete shrinkage was observed for HVFA concrete. The durability testing showed HVFA concrete increased the corrosion resistance and decreased the chloride penetration. Finally, existing relationships for hardened material properties and durability of conventional concretes are applicable to HVFA concretes --Abstract, page iii

Towards A Computational Intelligence Framework in Steel Product Quality and Cost Control

Steel is a fundamental raw material for all industries. It can be widely used in vari-ous fields, including construction, bridges, ships, containers, medical devices and cars. However, the production process of iron and steel is very perplexing, which consists of four processes: ironmaking, steelmaking, continuous casting and rolling. It is also extremely complicated to control the quality of steel during the full manufacturing pro-cess. Therefore, the quality control of steel is considered as a huge challenge for the whole steel industry. This thesis studies the quality control, taking the case of Nanjing Iron and Steel Group, and then provides new approaches for quality analysis, manage-ment and control of the industry. At present, Nanjing Iron and Steel Group has established a quality management and control system, which oversees many systems involved in the steel manufacturing. It poses a high statistical requirement for business professionals, resulting in a limited use of the system. A lot of data of quality has been collected in each system. At present, all systems mainly pay attention to the processing and analysis of the data after the manufacturing process, and the quality problems of the products are mainly tested by sampling-experimental method. This method cannot detect product quality or predict in advance the hidden quality issues in a timely manner. In the quality control system, the responsibilities and functions of different information systems involved are intricate. Each information system is merely responsible for storing the data of its corresponding functions. Hence, the data in each information system is relatively isolated, forming a data island. The iron and steel production process belongs to the process industry. The data in multiple information systems can be combined to analyze and predict the quality of products in depth and provide an early warning alert. Therefore, it is necessary to introduce new product quality control methods in the steel industry. With the waves of industry 4.0 and intelligent manufacturing, intelligent technology has also been in-troduced in the field of quality control to improve the competitiveness of the iron and steel enterprises in the industry. Applying intelligent technology can generate accurate quality analysis and optimal prediction results based on the data distributed in the fac-tory and determine the online adjustment of the production process. This not only gives rise to the product quality control, but is also beneficial to in the reduction of product costs. Inspired from this, this paper provide in-depth discussion in three chapters: (1) For scrap steel to be used as raw material, how to use artificial intelligence algorithms to evaluate its quality grade is studied in chapter 3; (2) the probability that the longi-tudinal crack occurs on the surface of continuous casting slab is studied in chapter 4;(3) The prediction of mechanical properties of finished steel plate in chapter 5. All these 3 chapters will serve as the technical support of quality control in iron and steel production