scholarly journals Development of Probability Concept for Thermal Fatigue Life Cycle Prediction

2020 ◽  
Vol 9 (3S) ◽  
pp. 57-60
Keyword(s):  
Life Cycle ◽  
Induction Furnace ◽  
Electrical Power ◽  
Melting Furnace ◽  
Furnace Wall ◽  
Raw Material ◽  
Induction Melting ◽  
Minor Variation ◽  
Refractory Wall ◽  
Probability Concept

Furnaces are most commonly used for melting of Ferrous Metals and its alloy materials. Induction furnaces use Electrical Power so that they are more advantageous as no fuel is required. It is a very critical problem to find life span of Induction Melting Furnace Wall under thermal load variation. The life cycle of induction furnace refractory wall is a variable as minor variation is always present due to effect of skill of workers and many other factors. The life cycle of furnace wall will vary minor with some miscellaneous factors and cannot be justified as a single value always. The probability concept is utilized here in the forecast of life cycle calculation to justify the miscellaneous factors effected for the damage of the induction furnace refractory wall. The probability concept initially defines a minimum life of induction furnace wall for a certain case then it is assumed to vary with different probability as given below. So, all the cases of induction furnace wall are having minimum life always but some cases of induction furnace wall are having much longer life. It is due to effect from many miscellaneous factors like skills of workers, efficiency of workers, raw material quality used for construction of wall, tools applied for ramming of it, row material employed for melting, etc.

scholarly journals Development of Empirical Correlation for Thermal Fatigue Life Cycle Prediction

2020 ◽  
Vol 9 (3S) ◽  
pp. 45-48
Keyword(s):  
Life Cycle ◽  
Fatigue Life ◽  
Refractory Material ◽  
Thermal Fatigue ◽  
Induction Furnace ◽  
Melting Furnace ◽  
Life Time ◽  
Empirical Correlation ◽  
Induction Melting ◽  
Thermal Fatigue Life

Furnaces are most commonly used for melting of Iron and its various alloy materials. Induction furnaces are using electric power supply so they are more beneficial as no fuel is required. It is an extremely critical to find life span or life cycle of Induction Melting Furnace Wall under thermal load change conditions. The low cycle thermal fatigue life time L is depended upon various parameters like thickness of induction furnace refractory wall t, density of refractory material , inside film co-efficient outside film co efficient , thermal expansion coefficient outside temperature , specific heat of refractory material C, elasticity constant E, ultimate strength S, thermal conductivity of refractory material k, Volume V, time period of melting cycle τ. An expression for thermal fatigue life time of induction furnace melting wall is derived by dimensional analysis using bunkingham’s π theorem. Then the empirical correlation is derived from the data available from theory as well as experimental and numerical results.

scholarly journals Evaluation of Strength and Microstructural Properties of Heat Treated High-Molybdenum Content Maraging Steel

Crystals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1446
Author(s):  
Asiful H. Seikh ◽  
Hossam Halfa ◽  
Mahmoud S. Soliman
Keyword(s):  
Optimum Condition ◽  
Tensile Properties ◽  
Maraging Steel ◽  
Melting Furnace ◽  
Steel Sample ◽  
Molybdenum Content ◽  
Raw Material ◽  
Induction Melting ◽  
Microstructural Properties ◽  
Heat Treated

Effect of high molybdenum content ~10% as an alloying element on the strength and microstructural properties of 11% nickel—1.25% titanium maraging steel was evaluated. To increase the homogeneity and cleanliness of produced ingot, the investigated steel sample was produced by melting the raw material in an open-air induction melting furnace followed by refining utilizing a direct current electro-slag refining machine. The produced steel samples were both forged and heat-treated in optimum condition to acquire the full capacity of mechanical properties especially the tensile properties. After Forging and heat treatment at optimum condition, steel samples were evaluated by optical microscopy (OM), X-ray diffraction (XRD), differential scanning calorimetry (DSC) analysis, electron backscattering diffraction (EBSD), and transmission electron microscopy (TEM). The experimental data showed that this steel sample has ultimate strength ~2100 MPa and elongation around 14%. High tensile properties obtained may be attributed on one hand due to the presence of high alloying lamellar martensite phase and lamellar austenite phase which has high dislocation intensity, and on the other hand, due to the high homogeneity and cleanliness of investigated samples from large nonmetallic inclusions. The results also show that a high amount of intermetallic compounds (NiMo3 and NiTi3) which are completely round and have a very low size not more than hundred nanometers.

scholarly journals Heat Transfer Simulation on the Wall of Rotary Cast Iron Smelting Furnace Capacity of 1 ton/hour

2018 ◽  
Vol 2 (1) ◽  
pp. 7
Author(s):  
Amir Syam ◽  
Zulfikar Zulfikar ◽  
Muhammad Idris Hutasuhut
Keyword(s):  
Heat Transfer ◽  
Cast Iron ◽  
Temperature Distribution ◽  
Simulation Analysis ◽  
Melting Furnace ◽  
Furnace Wall ◽  
Raw Material ◽  
Smelting Furnace ◽  
Iron Smelting ◽  
Heat Transfer Simulation

<span class="12paswordenglishChar"><span>The rotary smelting furnace is a cast iron smelting furnace with the working principle of raw material rotated in a melting drum. The difficulty of this type of furnace is if the furnace wall is damaged, it will be very difficult to determine the appropriate conduction coefficient material as a replacement material. Numerical simulations are required to obtain the heat transfer information that occurs on the furnace wall. This analysis aims to (1) obtain the temperature distribution occurring in the furnace wall, and (2) obtain the heat transfer coefficient on the wall surface on the inside, center, and outside of the melting furnace. Calculation of numerical simulation in this research is assisted by using Ansys software. The theoretical basis of numerical heat transfer simulation analysis can be determined by using the conduction temperature equation in each node. The load conditions in this case are assumed as thermal loads. The result obtained temperature distribution on the inner wall is 1590 <sup>o</sup>C, middle 1470 <sup>o</sup>C, and outside 1104 <sup>o</sup>C.</span></span>

scholarly journals The possibility of using high-quality fused magnesia in the manufacture of crucibles for vacuum-induction melting

2019 ◽  
pp. 60-64
Author(s):  
B. L. Krasnii ◽  
K. I. Ikonnikov ◽  
V. S. Anikanov ◽  
A. L. Galganova ◽  
M. A. Mikhailov
Keyword(s):  
Induction Furnace ◽  
Raw Material ◽  
Molar Ratio ◽  
Vacuum Induction Melting ◽  
Vacuum Induction Furnace ◽  
Induction Melting ◽  
Concrete Technology ◽  
Nickel Cobalt ◽  
Subsequent Decomposition ◽  
Physical And Mechanical Characteristics

The prospect of using crystalline fused magnesia (FL LC) in the manufacture technology of melting crucibles by the method of isostatic pressing is shown. It has been established that the production of a material based on MgO using concrete technology is limited to the hydration and loosening of the structure due to the formation and subsequent decomposition of brucite (native magnesia). The physical and mechanical characteristics of the obtained products are given. The effect of the CaO/SiO2 ratio on the corrosion and erosion resistance of products is considered. The raw material should have a molar ratio of these oxides of more than 1,7. Pressed crucibles were tested in the production of nickel, cobalt and tin based alloys in a vacuum induction furnace. The parameters of operation of products in the enterprise are shown. The effect of clogging by crucible materials during smelting of pure nickel has also been studied. The absence of contamination of the melt with crucible materials such as silicon dioxide, aluminosilicates and oxide films, etc., has been established.

scholarly journals Life Cycle Cost of Electricity Production: A Comparative Study of Coal-Fired, Biomass, and Wind Power in China

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3463
Author(s):  
Xueliang Yuan ◽  
Leping Chen ◽  
Xuerou Sheng ◽  
Mengyue Liu ◽  
Yue Xu ◽  
...  
Keyword(s):  
Power Generation ◽  
Life Cycle ◽  
Wind Power ◽  
Life Cycle Cost ◽  
Raw Material ◽  
Electricity Production ◽  
Maintenance Cost ◽  
External Cost ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity

Economic cost is decisive for the development of different power generation. Life cycle cost (LCC) is a useful tool in calculating the cost at all life stages of electricity generation. This study improves the levelized cost of electricity (LCOE) model as the LCC calculation methods from three aspects, including considering the quantification of external cost, expanding the compositions of internal cost, and discounting power generation. The improved LCOE model is applied to three representative kinds of power generation, namely, coal-fired, biomass, and wind power in China, in the base year 2015. The external cost is quantified based on the ReCiPe model and an economic value conversion factor system. Results show that the internal cost of coal-fired, biomass, and wind power are 0.049, 0.098, and 0.081 USD/kWh, separately. With the quantification of external cost, the LCCs of the three are 0.275, 0.249, and 0.081 USD/kWh, respectively. Sensitivity analysis is conducted on the discount rate and five cost factors, namely, the capital cost, raw material cost, operational and maintenance cost (O&M cost), other annual costs, and external costs. The results provide a quantitative reference for decision makings of electricity production and consumption.

scholarly journals Life-Cycle Assessment of Carbon Footprint of Bike-Share and Bus Systems in Campus Transit

2020 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Sishen Wang ◽  
Hao Wang ◽  
Pengyu Xie ◽  
Xiaodan Chen
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Energy Consumption ◽  
Carbon Footprint ◽  
Co2 Emission ◽  
Raw Material ◽  
Transit System ◽  
Two Systems ◽  
Bus System ◽  
Bike Share

Low-carbon transport system is desired for sustainable cities. The study aims to compare carbon footprint of two transportation modes in campus transit, bus and bike-share systems, using life-cycle assessment (LCA). A case study was conducted for the four-campus (College Ave, Cook/Douglass, Busch, Livingston) transit system at Rutgers University (New Brunswick, NJ). The life-cycle of two systems were disaggregated into four stages, namely, raw material acquisition and manufacture, transportation, operation and maintenance, and end-of-life. Three uncertain factors—fossil fuel type, number of bikes provided, and bus ridership—were set as variables for sensitivity analysis. Normalization method was used in two impact categories to analyze and compare environmental impacts. The results show that the majority of CO2 emission and energy consumption comes from the raw material stage (extraction and upstream production) of the bike-share system and the operation stage of the campus bus system. The CO2 emission and energy consumption of the current campus bus system are 46 and 13 times of that of the proposed bike-share system, respectively. Three uncertain factors can influence the results: (1) biodiesel can significantly reduce CO2 emission and energy consumption of the current campus bus system; (2) the increased number of bikes increases CO2 emission of the bike-share system; (3) the increase of bus ridership may result in similar impact between two systems. Finally, an alternative hybrid transit system is proposed that uses campus buses to connect four campuses and creates a bike-share system to satisfy travel demands within each campus. The hybrid system reaches the most environmentally friendly state when 70% passenger-miles provided by campus bus and 30% by bike-share system. Further research is needed to consider the uncertainty of biking behavior and travel choice in LCA. Applicable recommendations include increasing ridership of campus buses and building a bike-share in campus to support the current campus bus system. Other strategies such as increasing parking fees and improving biking environment can also be implemented to reduce automobile usage and encourage biking behavior.

scholarly journals Sustainability of Extraction of Raw Material by a Combination of Mobile and Stationary Mining Machines and Optimization of Machine Life Cycle

2020 ◽  
Vol 12 (24) ◽  
pp. 10454
Author(s):  
Katarína Teplická ◽  
Martin Straka
Keyword(s):  
Life Cycle ◽  
Raw Materials ◽  
Simulation Method ◽  
Raw Material ◽  
Optimal Distribution ◽  
Transport Costs ◽  
Scientific Discussion ◽  
Mining Companies ◽  
Conveyor Belts ◽  
The Impact

This article summarizes the arguments within the scientific discussion on the issue of using mining machines and their life cycle. The main goal of the article is to investigate the impact of a combination of mobile and stationary mining machines and their optimal distribution in the mining process to increase the efficiency of mining and processing of raw materials. The following methods of research were focused on the use of technical indicators for the valuation efficiency of the mining process: a simulation method was used for the distribution of mining machines, comparison analysis was used for the real and past state of mining machines, and a decision tree was used as managerial instrument for optimal alternatives of mining machines. The research empirically confirms and theoretically proves that optimal distribution of mining machines and machine parks is very important for mining companies. The benefit of this research for the mining company was the new location of the machines and the combination of stationary production lines and mobile equipment. The optimal layout of the machines reduced the number of conveyor belts and improved the transfer of limestone processing to mobile devices, saving time, which was reflected in transport costs. The results can be useful for other mining companies seeking to create an optimal machine park.

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