Affecting Factors and Improving Measures for Converter Gas Recovery

To change the undesirable present situation of recovering and using converter gas in steel plants in China, the basic approaches to improving the converter gas recovery rate were analyzed theoretically along with the change curves of the converter gas component content, based on the converter gas recovery system of Baosteel No. 2 steel- making plant. The effects of converter device, raw material, air imbibed quantity, recovery restricted condition, and intensity of oxygen blowing on the converter gas recovery rate were studied. Among these, the effects of the air im bibed quantity, recovery restricted condition, and intensity of oxygen blowing are remarkable. Comprehensive measures were put forward for improving the converter gas recovery from the point of devices, etc. , and good results were achieved.

Gas Flow Distribution in Pelletizing Shaft Furnace

Through thermal test, cold state experiment, analysis and simulation of thermal process, the gas flow distribution in pelletizing shaft furnace （PSF） was discussed. The results show that there are five flowing trends among them, the downward roasting gas and the upward cooling gas are the most unsteady, which influence flow distribution greatly. Among the operating parameters, the ratio of inflow is a key factor affecting the flow distribution. The roasting and cooling gases will entirely flow into the roasting zone and internal vertical air channels （IVAC）, respectively, if the ratio of inflow is critical. From such a critical operating condition increasing roasting gas flow or decreasing cooling gas flow, the roasting gas starts flowing downwards so as to enter the inside of IVAC the greater the ratio of inflow, the larger the downward flowrate. Among constructional parameters, the width of roasting zone b1, width of IVAC b2 and width of cooling zone b3, and the height of roasting zone h1, height of soaking zone h2 and height of cooling zone hs are the main factors affecting flow distribution. In case the ratio of b2/b3, or h3/h2, or h1/h2 is increased, the upward cooling gas tends to decrease while the downward roasting gas tends to increase with a gradual decrease in the ratio of inflow.

Disposal of Waste Plastics With Traditional Coking Process

A new technology for treating waste plastics （WP） by traditional coking process was introduced. With a thermo-balance and a 10 g atmospheric fixed bed reactor, the thermo-gravimetric behavior and product were studied during co-coking of WP with blended coal. And then, using a coke-oven with capacity of 200 kg, the characteristics of products were assessed. The results showed that there is an overlapping temperature range （200-550℃ ） of decomposition between WP and blended coal, and the pyrolysis synergism index η and synergism strength β proposed could evaluate the synergism between them. 1% of added WP results in the maximum synergism in all series experiments. The increase of added WP decreases the synergism. Tar yield in co-coking is increased with the decrease of water yield for synergism. Moreover, it was also found that the quality indexes of coke, such as M10, M40, CRI and CSR, are degraded with the increase of WP until 4%, though the quality of tar and gas is optimized for WP addition.

钢铁生产的水能关系分析

从钢铁生产过程中水资源使用时的能耗角度研究了钢铁联合企业的水能关系,提出了水能强度的概念来评价企业生产过程中水资源利用的节能水平,建立了钢铁企业的水能关系模型。以中国某大型钢铁联合企业为例,计算并分析了该企业的水能关系。该企业总的水能量为55 709kW·h/h,重复用水水能量占整个钢铁企业全部水能量的82%,补水水能量占16%,排水水能量占1%;各工序中热轧工序占比最大,其次是炼铁、炼钢工序,冷轧、烧结和炼焦工序较低。该企业的吨钢水能强度为0.208kW·h/m^3,炼铁工序的水能强度最高,热轧、炼钢工序次之,烧结、冷轧和炼焦工序较低。最后,从钢铁生产过程水资源利用的角度得到节能的方向及措施。

钢铁企业水系统中的“有效水”及其分析方法

敞开间接冷却水是钢铁企业水系统的主要形式,研究补水、用水过程中水量与水质的相互关系,对认识敞开间接冷却水系统的规律是十分必要的。将用水过程中的水量与水质指标结合起来,提出'有效水'概念,建立了数学模型及相关分析方法。对某钢铁企业补水、用水实际案例的研究表明,补水和用户两方面的水质变化都将导致系统补水有效性改变,进而使系统的新水消耗和废水排放量发生改变。与单纯的水量指标相比,'有效水'概念及其分析方法能够更科学地评价敞开冷却水系统的用水特性。

Change in Carbon Dioxide (CO_2) Emissions From Energy Use in China's Iron and Steel Industry

As the largest energy consuming manufacturing sector and one of the most important sources of carhon dioxide （CO2） emissions, the China＇s iron and steel industry has paid attention to the study of changing trend and influencing factors of CO2 emissions from energy use. The logarithmic mean Divisia index （LMD1） technique is used to decompose total change in CO2 emissions into four factors： emission factor effect, energy structure effect, energy consumption effect, and steel production effect. The results show that the steel production effect is the major factor which is responsible for the rise in CO2 emissions; whereas the energy consumption effect contributes most to the reduction in CO2 emissions. And the emission factor effect makes a weak negative contribution to the increase of CO2 emis- sions. To find out the detailed relationship between change in energy consumption or steel production and change in CO2 emissions, the correlation equations are also proposed.

Plant-Wide Supply-Demand Forecast and Optimization of Byproduct Gas System in Steel Plant

Considerable energy is consumed during steel manufacturing process. Byproduct gas emerges as secondary energy in the process; however, it is also an atmospheric pollution source if it is released into the air. Therefore, the optimal utilization of byproduct gas not only saves energy but also protects environment. To solve this issue, a fore- cast model of gas supply, gas demand and surplus gas in a steel plant was proposed. With the progress of energy conservation, the amount of surplus gas was very large. In a steel plant, the surplus gas was usually sent to boilers to generate steam. However, each boiler had an individual efficiency. So the optimization of the utilization of surplus gas in boilers was a key topic. A dynamic programming method was used to develop an optimal utilization strategy for surplus gas. Finally, a case study providing a sound confirmation was given.

Shift From Coke to Coal Using Direct Reduction Method and Challenges

Ironmaking involves the separation of iron ores. It not only represents the first step in steelmaking but also is the most capital-intensive and energy-intensive process in the production of steel. The main route for producing iron for steelmaking is to use the blast furnace, which uses metallurgical coke as the reductant. Concerns over the limited resources, the high cost of coking coals, and the environmental impacts of coking and sinter plants have driven steelmakers to develop alternative ironmaking processes that can use non-coking coals to reduce iron ores directly. Since the efficiency and productivity of modern large capacity blast furnaces will be difficult to surpass, blast furnaces will continue to retain their predominant position as the foremost ironmaking process for some time to come. The alternative ironmaking processes are therefore expected to play an increasingly significant role in the iron and steel industry, especially in meeting the needs of small-sized local and regional markets. It is likely that the importance of direct reduced iron （DRI） and hot metal as sources of virgin iron will continue to increase, especially in the developing countries where steelmaking is, and will be, primarily based on electric arc furnace （EAF） minimills. Consequently, the challenges that are faced by the new technology have to be embraced.

Multi-Period Optimal Distribution Model of Energy Medium and Its Application

A mathematical model of optimal energy medium distribution in steelmaking process is formulated. In this model, three kinds of important energy mediums including byproduct gases, steam and electricity are considered, and the objective function accounts for both the change of generation and consumption of the byproduct gases and the demand of low （or middle） pressure steam and electricity for each period to maximize the benefit of products cost and minimize the consumption of energy. The results indicate that the optimal distribution scheme of byproduct gases, middle pressure steam, low pressure steam and electricity is achieved and case study shows that 6% of operation cost is reduced by using the proposed model comparing with the previous model.