Furnace Temperature Curve Optimization Model Based on Differential Evolution Algorithm

When soldering electronic components onto circuit boards,the temperature curves of the reflow ovens across different zones and the conveyor belt speed significantly influence the product quality.This study focuses on optimizing the furnace temperature curve under varying settings of reflow oven zone temperatures and conveyor belt speeds.To address this,the research sequentially develops a heat transfer model for reflow soldering,an optimization model for reflow furnace conditions using the differential evolution algorithm,and an evaluation and decision model combining the differential evolution algorithm with the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method.This approach aims to determine the optimal furnace temperature curve,zone temperatures of the reflow oven,and the conveyor belt speed.

CLOF Based Outlier Detection Algorithm of Temperature Data for Ethylene Cracking Furnace

The flue temperature is one of the important indicators to characterize the combustion state of an ethylene cracker furnace,the outliers of temperature data can lead to the false alarm.Conventional outlier detection algorithms such as the Isolation Forest algorithm and 3-sigma principle cannot detect the outliers accurately.In order to improve the detection accuracy and reduce the computational complexity,an outlier detection algorithm for flue temperature data based on the CLOF(Clipping Local Outlier Factor,CLOF)algorithm is proposed.The algorithm preprocesses the normalized data using the cluster pruning algorithm,and realizes the high accuracy and high efficiency outlier detection in the outliers candidate set.Using the flue temperature data of an ethylene cracking furnace in a petrochemical plant,the main parameters of the CLOF algorithm are selected according to the experimental results,and the outlier detection effect of the Isolation Forest algorithm,the 3-sigma principle,the conventional LOF algorithm and the CLOF algorithm are compared and analyzed.The results show that the appropriate clipping coefficient in the CLOF algorithm can significantly improve the detection efficiency and detection accuracy.Compared with the outlier detection results of the Isolation Forest algorithm and 3-sigma principle,the accuracy of the CLOF detection results is increased,and the amount of data calculation is significantly reduced.

The clutch size,incubation behavior of Reeves’s Pheasant(Syrmaticus reevesii) and their responses to ambient temperature and precipitation

Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.

Ladle Furnace Temperature Prediction Model Based on Large-scale Data With Random Forest

In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can not satisfy practical production. Fortunately, the large sample set is accumulated from the practical production process. However, a large sample set makes it difficult to build a liquid steel temperature model. To deal with the issue, the random forest method is preferred in this paper, which is a powerful regression method with low complexity and can be designed very quickly. It is with the parallel ensemble structure,uses sample subsets,and employs a simple learning algorithm of sub-models. Then, the random forest method is applied to establish a temperature model by using the data sampled from the production process. The experiments show that the random forest temperature model is more precise than other temperature models.

Effect of sintering temperature on the microstructure and properties of foamed glass-ceramics prepared from high-titanium blast furnace slag and waste glass

Foamed glass-ceramics were prepared via a single-step sintering method using high-titanium blast furnace slag and waste glass as the main raw materials The influence of sintering temperature(900–1060℃) on the microstructure and properties of foamed glass-ceramics was studied. The results show that the crystal shape changed from grainy to rod-shaped and finally turned to multiple shapes as the sintering temperature was increased from 900 to 1060℃. With increasing sintering temperature, the average pore size of the foamed glass-ceramics increased and subsequently decreased. By contrast, the compressive strength and the bulk density decreased and subsequently increased. An excessively high temperature, however, induced the coalescence of pores and decreased the compressive strength. The optimal properties, including the highest compressive strength(16.64 MPa) among the investigated samples and a relatively low bulk density(0.83 g/cm^3), were attained in the case of the foamed glass-ceramics sintered at 1000℃.

Analysis of temperature,stress,and displacement distributions of staves for a blast furnace

The temperature of gas flow inside a blast furnace （BF） changes significantly when the blast furnace is under unstable operations, and the temperature and stress distributions of cooling staves （CS） for BF work the same pattern. The effect of gas temperature on the temperature, stress, and displacement distributions of the cooling stave were analyzed as the gas temperature inside the blast furnace rose from 1000 to 1600℃ in 900 s. The results show that both the temperature and temperature gradient of the hot side of CS increase when the gas flow temperature inside BF rises. The temperature gradient of the hot side of CS is greater than that of the other area of CS and it can reach 65℃/mm. In the vertical direction of the hot side of CS, closer to the central part of CS, the stress intensity is greater than that of the other area of the hot side of CS, which causes cracks on the hot side of CS in the vertical di- rection. As the gas temperature increases, the stress intensity rate near the fixed pin increases and finally reaches 45 MPa/s. Fatigues near the fixed pin and bolts are caused by great stress intensity rate and the area around the pin can be damaged easily. The edge of CS bends toward the cold side and the central part of CS shifts toward the hot surface.

Transient Temperature Analysis for Industrial AC Arc Furnace Bottom

Heat losses from the furnaces depend on the design and size. The surface heat loss from the bottom of an industrial AC electric arc furnace (EAF) possesses an important fraction of overall losses. So in this study the transient temperature variation at the bottom of the EAF was investigated. The transient temperature analysis was carried out using MATLAB computer program. T=T(r, t) for different bottom lining layers was depicted.

Designing for Long Campaign Life Blast Furnace (2)-The Simulation of Temperature Field of Lining and Cooling Apparatus

Through the numerical modeling of temperature field for Blast Furnace (BF) lining and stave coolers, it can tell designers how to design a cooler which the hot surface temperature is less than its critical temperature under very high heat flux. Applying low heat re- sistance lining and staves cooler to BF is good for a layer of slag skull frozen on the hot surface of cooling stave. As long as the slag skull can stand, the furnace wall is stable and the heat loss of furnace does not increase. This is the basic principle for designing long campa- ignship BF.

Antibacterial Properties of V-doped Titanium-bearing Blast Furnace Slag Prepared at Different Calcination Temperatures

Perovskite-type V-doped titanium-bearing blast furnace slag (VTBBFS) photocatalyst was prepared by high-temperature solid phase method.The influence of calcination temperature on the photocatalytic and antibacterial properties of VTBBFS was studied in details.Its composition and microstructure were evaluated by X-ray diffractometer,ultraviolet-visible absorption spectrometer,Fourier transform infrared spectrometer and scanning electron microscope.The antibacterial properties of VTBBFS to Candida albicans were investigated by flask oscillation method.The results showed that the optical absorption and antibacterial properties of VTBBFS were the best with 10%(ω) doping of vanadium,prepared at 800℃ for 2 h,and its sterilization rate was close to 100% to Candida albicans (ATCC10231).The minimum inhibitory and minimum bactericidal concentrations were 25 and 50 mg/mL.When the concentration was 0.2 μg/mL,the catalyst had the least toxic toxicity.

Temperature Intelligent Control System of Large-Scale Standing Quench Furnace

Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.

Temperature control for thermal treatment of aluminum alloy in a large-scale vertical quench furnace

The temperature control of the large-scale vertical quench furnace is very difficult due to its huge volume and complex thermal exchanges. To meet the technical requirement of the quenching process, a temperature control system which integrates temperature calibration and temperature uniformity control is developed for the thermal treatment of aluminum alloy workpieces in the large-scale vertical quench furnace. To obtain the aluminum alloy workpiece temperature, an air heat transfer model is newly established to describe the temperature gradient distribution so that the immeasurable workpiece temperature can be calibrated from the available thermocouple temperature. To satisfy the uniformity control of the furnace temperature, a second order partial differential equation(PDE) is derived to describe the thermal dynamics inside the vertical quench furnace. Based on the PDE, a decoupling matrix is constructed to solve the coupling issue and decouple the heating process into multiple independent heating subsystems. Then, using the expert control rule to find a compromise of temperature rising time and overshoot during the quenching process. The developed temperature control system has been successfully applied to a 31 m large-scale vertical quench furnace, and the industrial running results show the significant improvement of the temperature uniformity, lower overshoot and shortened processing time.

Finite-time Stability of Heating Furnace Temperature Control System

A finite-time stabilization controller for the heating furnace temperature control system is proposed.Based on the extended Lyapunov finite-time stability theory and power integral method,a finite-time stable condition of the heating furnace temperature control system is given.The temperature of the heating furnace is directed by the finite-time stabilization controller to make it stable in finite time.And the quality and quantity of slabs is improved.The simulation example is presented to illustrate the applicability of the developed results.

A rapid analysis of coal with furnace under controlled multiple temperature areas

A novel thermogravimetric analyzer system of furnace with multiple temperature controller was described,which mainly decreased the analysis cycle duration down to 20 min.Furthermore,the present C591 rapid analyzer system under software can monitor and control some coal physical and chemical properties like change of coal,control com- bustion regulation,operation of coal mixture,and improvement of the turnover rate of the transportation facilities as well.

Various admixtures to mitigate the long-term strength retrogression of Portland cement cured under high pressure and high temperature conditions

In order to investigate the problem of long-term strength retrogression in oil well cement systems exposed to high pressure and high temperature(HPHT)curing conditions,various influencing factors,including cement sources,particle sizes of silica flour,and additions of silica fume,alumina,colloidal iron oxide and nano-graphene,were investigated.To simulate the environment of cementing geothermal wells and deep wells,cement slurries were directly cured at 50 MPa and 200?C.Mineral compositions(as determined by X-ray diffraction Rietveld refinement),water permeability,compressive strength and Young’s modulus were used to evaluate the qualities of the set cement.Short-term curing(2e30 d)test results indicated that the adoption of 6 m m ultrafine crystalline silica played the most important role in stabilizing the mechanical properties of oil well cement systems,while the addition of silica fume had a detrimental effect on strength stability.Long-term curing(2e180 d)test results indicated that nano-graphene could stabilize the Young’s modulus of oil well cement systems.However,none of the ad-mixtures studied here can completely prevent the strength retrogression phenomenon due to their inability to stop the conversion of amorphous to crystalline phases.

Revamping design of an EAF automatic temperature measurement and sampling robot

The function,features,and architecture of a robot that performs automatic temperature measurement and sampling applied on a 150-t AC electric arc furnace(EAF)production line of Baosteel were presented,and the key points of design and revamping experience on the site layout,device protection,lance tool,probe container,measuring position control,and system safety were summarized.Furthermore,a valuable reference for the application of automatic temperature measuring and sampling robots in EAF steelmaking plants will be provided.

Insight into the effect of gel drying temperature on the structure and desulfurization performance of ZnO/SiO_(2)adsorbents

A series of ZnO/SiO_(2) adsorbents were prepared by a sol-gel method using tetraethyl orthosilicate,ethylene glycol(EG)and nitrates as precursors.The effect of gel drying temperature on the structure and desulfurization performance of the adsorbents were investigated in detail.It is found that the low drying temperature led to a weak interaction among EG,Si AOH/H_(2)O and the nitrates in the gel system,which caused the oxidation of EG by NO3-and formed zinc glyoxylate complex during the gel calcination process,whereas this oxidation process also occurred at a high drying temperature during the gel drying process.The formed zinc glyoxylate complex promoted the generation of monodentate carbonate on the surface of Zn O,which resulted in the inferior desulfurization performance of adsorbents despite they have smaller Zn O nanoparticles.The gel dried at 120°C formed the hydrogen bonds between EG and Si AOH/H_(2)O and a strong interaction between zinc oxo-clusters and NO3-was also found in the gel system,which avoided the oxidation of EG by NO3-during the preparation process and the Zn O nanoparticles with sizes of 6 nm were formed by a combustion method.The adsorbent affords a highest sulfur capacity of 104.9 mg·g^(-1) in this case.In addition,the gel drying temperature has a significant influence on the textural properties of the adsorbents except their surface area.

Changes in Rainfall and Temperature and Its Impact on Crop Production in Moyamba District, Southern Sierra Leone

Rainfall and temperature are the important variables that are often used to trace climate variability and change. A Perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from Farmer-Based Organizations (FBOs) in 4 chiefdoms and 30 Agricultural Extension Workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analyses were used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the significance and magnitude of the trends respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that;adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge, technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practicing some CSA practices on their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties whilst the AEWs need training on CSA practices.

Modeling Daily Average Temperatures in a Coastal Site of Central Africa: An Analysis of Seasonal Divisions

The seasonality and day-to-day variation of near-surface temperature patterns can greatly control nearly all physical and biological processes though temperature predictions at such scales remain challenging. This paper implements a simple analytical approach in order to generate daily average temperatures which implicitly accounts for surface heating and drivers through a comprehensive representation of station-based temperature records on a universal standard calendar propagated by the earth’s dynamics features. The modeled and observed pattern of daily temperatures exhibits a close agreement with the level of strength agreement exceeding 0.56. The extreme high and low values of the observed temperature patterns are equally well captured although model underestimates the probability of temperatures around the two modal peaks (~25.6℃ and 27.5℃). Additionally, a theoretical thermal-based division led to the identification of six seasons, including two hot and cold periods along with two pairs of mixed hot-cold. The theoretical division proposed here appears to be a good approximation for the understanding of rainfall seasonality in this area.

Zonal method solution of radiative heat transfer in a one-dimensional long roller-hearth furnace in CSP

A radiative heat transfer mathematical model for a one-dimensional long furnace was set up in a through-type roller-hearth furnace （TTRHF） in compact strip production （CSP）. To accurately predict the heat exchange in the furnace, modeling of the complex gas energy-balance equation in volume zones was considered, and the heat transfer model of heating slabs and wall lines was coupled with the radiative heat transfer model to identify the surface zonal temperature. With numerical simulation, the temperature fields of gas, slabs, and wall lines in the furnace under one typical working condition were carefully accounted and analyzed. The fundamental theory for analyzing the thermal process in TI＇RI-IF was provided.

Effects of Temperature and Pressure on Stress Corrosion Cracking Behavior of 310S Stainless Steel in Chloride Solution

310S is an austenitic stainless steel for high temperature applications, having strong resistance of oxidation, hydrogen embrittlement and corrosion. Stress corrosion cracking（SCC） is the main corrosion failure mode for 310S stainless steel. Past researched about SCC of 310S primarily focus on the corrosion mechanism and influence of temperature and corrosive media, but few studies concern the combined influence of temperature, pressure and chloride. on SCC of 310S stainless steel, prepared samples are investigated via For a better understanding of temperature and pressure＇s effects slow strain rate tensile test（SSRT） in different temperature and pressure in NACE A solution. The result shows that the SCC sensibility indexes of 310S stainless steel increase with the rise of temperature and reach maximum at 10MPa and 160~C, increasing by 22.3% compared with that at 10 MPa and 80 ℃. Instead, the sensibility decreases with the pressure up. Besides, the fractures begin to transform from the ductile fracture to the brittle fracture with the increase of temperature. 310S stainless steel has an obvious tendency of stress corrosion at 10MPa and 160℃ and the fracture surface exists cleavage steps, river patterns and some local secondary cracks, having obvious brittle fracture characteristics. The SCC cracks initiate from inclusions and tiny pits in the matrix and propagate into the matrix along the cross section gradually until rupture. In particular, the oxygen and chloride play an important role on the SCC of 310S stainless steel in NACE A solution. The chloride damages passivating film, causing pitting corrosion, concentrating in the cracks and accelerated SSC ultimately. The research reveals the combined influence of temperature, pressure and chloride on the SCC of 310S, which can be a guide to the application of 310S stainless steel in super-heater tube.