Microstructure and mechanical properties of a Cr-Ni-W-Mo steel processedthermo-mechanical controlled processing

Experiments were conducted to evaluate the microstructure and tensile properties of a medium carbon Cr-Ni-W-Mo steel processedthermo-mechanical controlled processing(TMCP)with cooling at different conditions in water,oil,air or lime followedlow tempering.Compared to normal heat-treatment processing,TMCP with water-cooling after deformation enhances the yield strength and tensile strength of the steelabout 323 MPa and about 251 MPa,respectively,due to higher dislocation strengthening and grain boundary strengthening.Meanwhile,it increases the elongation by ;about 1.76%attributed to the increase in volume percentage of the retained austenite and the refined laths of tempered martensite.Slowing the cooling rate after deformation during TMCP leads to a decrease in the strength.This results the coupling effectsthe reduction in dislocation density and volume fraction of tempered martensite together with the coarseness in martensite sizes.However,cooling rate decreasing has less influences on ductility becathe improved elongation the increase in the volume fractions of both retained austenite and lower bainite together with dislocation density decreasing is compensatedthe reduced elongation coarsened grains.

Effect of Thermomechanical Controlled Processing on Mechanical Properties of 490 MPa Grade Low Carbon Cold Heading Steel

Thermomechanical controlled processing （TMCP） of low carbon cold heading steel in different austenite conditions were conducted by a laboratory hot rolling mill. Effect of various processing parameters on the mechanical properties of the steel was investigated. The results showed that the mechanical properties of the low carbon cold heading steel could be significantly improved by TMCP without heat treatment. The improvement of mechanical properties can be attributed mainly to the ferrite grain refinement due to low temperature rolling. In the experiments the better ultimate tensile strength and ductility are obtained by lowering finishing cooling temperature within the temperature range from 650 ℃ to 550 ℃ since the interlamellar space in pearlite colonies become smaller. Good mechanical properties can be obtained in a proper austenite condition and thermomechanical processing parameter. The ferrite morphology has a more pronounced effect on the mechanical behavior than refinement of the microstructure. It is possible to realize the replacement of medium-carbon by low-carbon for 490 MPa grade cold heading steel with TMCP.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Chemical simulation teaching system based on virtual reality and gesture interaction

Background Most existing chemical experiment teaching systems lack solid immersive experiences,making it difficult to engage students.To address these challenges,we propose a chemical simulation teaching system based on virtual reality and gesture interaction.Methods The parameters of the models were obtained through actual investigation,whereby Blender and 3DS MAX were used to model and import these parameters into a physics engine.By establishing an interface for the physics engine,gesture interaction hardware,and virtual reality(VR)helmet,a highly realistic chemical experiment environment was created.Using code script logic,particle systems,as well as other systems,chemical phenomena were simulated.Furthermore,we created an online teaching platform using streaming media and databases to address the problems of distance teaching.Results The proposed system was evaluated against two mainstream products in the market.In the experiments,the proposed system outperformed the other products in terms of fidelity and practicality.Conclusions The proposed system which offers realistic simulations and practicability,can help improve the high school chemistry experimental education.

Research on Quality Management Measures of Green Building Construction

Urbanization has led to the rapid development of the construction industry.However,this has also led to higher requirements for the construction engineering management.Other than the quality monitoring of engineering construction,the energy-saving properties of the building should also be considered.Therefore,a scientific management approach should be adopted to improve green building management.This paper primarily examines the importance of quality management in green building construction,along with the factors influencing it.It also identifies the quality issues present in current green building construction.Finally,it proposes measures for quality management in the green building construction process to facilitate the industry’s healthy development.

Controlled Rolling and Cooling Process for Low Carbon Cold Forging Steel

Effect of controlled rolling and cooling process on the mechanical properties of low carbon cold forging steel was investigated for different processing parameters of a laboratory hot rolling mill. The results show that the specimens with fast cooling after hot rolling exhibit very good mechanical properties, and the improvement of the mechanical properties can be attributed mainly to the ferrite-grain refinement. The mechanical properties increase with decreasing final cooling temperature within the range from 670 ℃ to 570 ℃ due to the finer interlamellar spacing of pearlite colony. The specimen with fast cooling after low temperature rolling shows the highest values of the mechanical properties. The effect of the ferrite grain size on the mechanical properties was greater than that of pearlite morphology in the present study. The mechanical properties of specimens by controlled rolling and cooling process without thermal treatment were greatly superior to that of the same specimens by the conventional rolling, and their tensile strength reached 490 MPa grade even in the case of low temperature rolling without controlled rolling. It might be expected to realize the substitution medium-carbon by low-carbon for 490 MPa grade cold forging steel with controlled rolling and cooling process.

IMPROVED PROCESSING FOR MICROSTRUCTURES AND MECHANICAL PROPERTIES OF A COMMERCIAL PIPELINE STEEL

The transformation productions of hot-deformation simulation experiments were investigated using a Gleeble-1500 hot simulator for a commercial pipeline steel. Based on the investigation results, the improved thermo-mechanical control processing (TMCP) schedules containing a two stage multi-pass controlled rolling coupled with moderate cooling rates were applied to hot rolling experiments and acicular ferrite dominated microstructure was obtained. Microstructures and mechanical properties of hot rolled plates were related to TMCP processing, and regression equations describing the relation between processing parameters and mechanical properties in the current TMCP were developed, which could be used to predict mechanical properties of the experimental steel during commercially processing. It was found that with an increase in cooling rate after hot rolling, grain size in the microstructure became smaller, the amount of polygonal ferrite decreased and acicular ferrite increased, and accordingly mechanical properties increased.

Closed-loop control system design and experimental study for controlled pulse keyhole plasma arc welding

The controlled pulse waveform is newly applied in keyhole plasma arc welding process. Two additional descending slopes can guarantee stable and smooth transition of keyhole closing and opening periodically. To develop a closed-loop control system for this special welding process, the key point is the determination of system input and output variables. The averaged efflux plasma voltage during a pulse cycle is defined as the characteristic variable reflecting the real keyhole dimension. Research and experiments are conducted to explore the relationship between the characteristic variable and weld pe^Cormance. Results show that alternated peak current can significantly change the keyhole dimension and the penetration. It is proposed that the keyhole average dimension is taken as the controlled variable, and the peak pulse current value and slopes are taken as control variables.

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS （PART I：EQUAL TIMES AND COSTS）

Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.

Study on gas metal arc welding of two types of TMCP steels

Gas metal arc welding experiments were conducted on two types of steels with 0.41% carbon equivalent(Ceq) and 0.31% Cequsing WER70T wire and 20% CO_(2)and 80% Ar as shielding gas.The two types of steels show satisfactory weldability.The transition temperatures of 50% upper shelf energy(Tk0.5) for Charpy-V impact test of both the welded joints are below-40 ℃.However, the toughness of the fusion line zone and heat-affected zone(HAZ) of the two steel joints exhibits differences, with the toughness of 0.41% Ceqsteel being better than that of 0.31% Ceqsteel.The Tk0.5of the fusion line zone and the HAZ of 0.41% Ceqsteel is below-60℃,whereas that of 0.31% Ceqsteel is above-40℃.The welded joint of 0.41% Ceqsteel has low hardness fluctuation, while that of 0.31% Ceqsteel exhibits a narrow, softened zone, which has no obvious influence on the tested tensile strength.The coarse grain heat-affected zone(CGHAZ)microstructure of 0.41% Ceqsteel is bainite, while that of 0.31% Ceqsteel is bainite with ferrite and minor pearlite.

Effect of Level of Processing Prior to Response on Cognitive Control:Evidence from ERP

Based on the idea that intentions have different penetrability to perception and thought, four Stroop-like tasks, AA, AW, WA, and WW are used. Event-related brain potentials are recorded as participants completed these tasks, and standardized low resolution brain electromagnetic tomography （sLORETA） is used to localize the sources at specific time points. These results show that there is an interference effect in the AA and WA tasks, but not in the AW or WW tasks. The activated brain areas related to the interference effect in the AA task are the PFC （prefrontal cortex） and ACC （anterior cingulated cortex）, and PFC aetivation takes place prior to ACC activation, but only in WA task. Combined with previous results, a new neural mechanism of cognitive control is proposed.

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS ： PROOF OF THEOREMS

Abstract This report is virtually the appendix part of the author's previous paper which includes the proofs for the theorems and lemmas.

A blast furnace fault monitoring algorithm with low false alarm rate:Ensemble of greedy dynamic principal component analysis-Gaussian mixture model

The large blast furnace is essential equipment in the process of iron and steel manufacturing. Due to the complex operation process and frequent fluctuations of variables, conventional monitoring methods often bring false alarms. To address the above problem, an ensemble of greedy dynamic principal component analysis-Gaussian mixture model(EGDPCA-GMM) is proposed in this paper. First, PCA-GMM is introduced to deal with the collinearity and the non-Gaussian distribution of blast furnace data.Second, in order to explain the dynamics of data, the greedy algorithm is used to determine the extended variables and their corresponding time lags, so as to avoid introducing unnecessary noise. Then the bagging ensemble is adopted to cooperate with greedy extension to eliminate the randomness brought by the greedy algorithm and further reduce the false alarm rate(FAR) of monitoring results. Finally, the algorithm is applied to the blast furnace of a large iron and steel group in South China to verify performance.Compared with the basic algorithms, the proposed method achieves lowest FAR, while keeping missed alarm rate(MAR) remain stable.

A master-slave generalized predictive synchronization control for preheating process of multi-cavity hot runner system

As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the leading cause.Hence,the solution may rest with the synchronization of those heating processes in MCHR system.This paper proposes a’Master-Slave’generalized predictive synchronization control(MS-GPSC)method with’Mr.Slowest’strategy for preheating stage of MCHR system.The core of the proposed method is choosing the heating process with slowest dynamics as the’Master’to track the setpoint,while the other heating processes are treated as‘Slaves’tracking the output of’Master’.This proposed method is shown to have the good ability of temperature synchronization.The corresponding analysis is conducted on parameters tuning and stability,simulations and experiments show the strategy is effective.

Multi-Objective Adaptive Optimization Model Predictive Control:Decreasing Carbon Emissions from a Zinc Oxide Rotary Kiln

The zinc oxide rotary kiln,as an essential piece of equipment in the zinc smelting industrial process,is presenting new challenges in process control.China’s strategy of achieving a carbon peak and carbon neutrality is putting new demands on the industry,including green production and the use of fewer resources;thus,traditional stability control is no longer suitable for multi-objective control tasks.Although researchers have revealed the principle of the rotary kiln and set up computational fluid dynamics(CFD)simulation models to study its dynamics,these models cannot be directly applied to process control due to their high computational complexity.To address these issues,this paper proposes a multi-objective adaptive optimization model predictive control(MAO-MPC)method based on sparse identification.More specifically,with a large amount of data collected from a CFD model,a sparse regression problem is first formulated and solved to obtain a reduction model.Then,a two-layered control framework including real-time optimization(RTO)and model predictive control(MPC)is designed.In the RTO layer,an optimization problem with the goal of achieving optimal operation performance and the lowest possible resource consumption is set up.By solving the optimization problem in real time,a suitable setting value is sent to the MPC layer to ensure that the zinc oxide rotary kiln always functions in an optimal state.Our experiments show the strength and reliability of the proposed method,which reduces the usage of coal while maintaining high profits.

Guide and control of thermal conduction with isotropic thermodynamic parameters based on a rotary-concentrating device

A rotary-concentrating device for thermal conduction is constructed to control and guide thermal energy transmitting in elastic plates.The designed device has the ability of concentrating for thermal conduction and controlling the processes of thermal diffusion in a plate.The multilayered isotropic material properties of the rotary-concentrating device are derived based on the transformation and rotary medium method and a rotation parameter to control the thermal diffusion process is introduced.The efficiency of the rotary-concentrating device for thermal conduction is verified.Stability of temperature fields in a plate with the rotary-concentrating device is analyzed to study the performance of rotary-concentrating.Numerical examples show that the constructed rotary-concentrating device for thermal conduction can effectively rotate and focus on the thermal energy into the device for a wide range of diffusion temperatures,which can enhance the thermal conduction.Therefore,this study can provide a theoretical support for potential applications in fields of energy harvesting and thermal conduction control.

Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

With the full development of disk-resident databases(DRDB)in recent years,it is widely used in business and transactional applications.In long-term use,some problems of disk databases are gradually exposed.For applications with high real-time requirements,the performance of using disk database is not satisfactory.In the context of the booming development of the Internet of things,domestic real-time databases have also gradually developed.Still,most of them only support the storage,processing,and analysis of data values with fewer data types,which can not fully meet the current industrial process control system data types,complex sources,fast update speed,and other needs.Facing the business needs of efficient data collection and storage of the Internet of things,this paper optimizes the transaction processing efficiency and data storage performance of the memory database,constructs a lightweight real-time memory database transaction processing and data storage model,realizes a lightweight real-time memory database transaction processing and data storage model,and improves the reliability and efficiency of the database.Through simulation,we proved that the cache hit rate of the cache replacement algorithm proposed in this paper is higher than the traditional LRU(Least Recently Used)algorithm.Using the cache replacement algorithm proposed in this paper can improve the performance of the system cache.

A Study of Detection of Outliers for Working and Non-Working Days Air Quality in Kolkata, India: A Case Study

A variety of factors affect air quality, making it a difficult issue. The level of clean air in a certain area is referred to as air quality. It is challenging for conventional approaches to correctly discover aberrant values or outliers due to the significant fluctuation of this sort of data, which is influenced by Climate change and the environment. With accelerating industrial expansion and rising population density in Kolkata City, air pollution is continuously rising. This study involves two phases, in the first phase imputation of missing values and second detection of outliers using Statistical Process Control (SPC), and Functional Data Analysis (FDA), studies to achieve the efficacy of the outlier identification methodology proposed with working days and Nonworking days of the variables NO2, SO2, and O3, which were used for a year in a row in Kolkata, India. The results show how the functional data approach outshines traditional outlier detection methods. The outcomes show that functional data analysis vibrates more than the other two approaches after imputation, and the suggested outlier detector is absolutely appropriate for the precise detection of outliers in highly variable data.

Experimental study on 830 MPa grade pipeline steel containing chromium

The diversity of microstructure and properties of 830 MPa grade pipeline steel containing chromium was investigated by optical microscope and transmission electron microscopy. The main microstructures were multiple configurations, containing lath bainite and granule bainitc. Mechanical properties test results showed that the yield strength and tensile strength improved with increasing chromium content. The toughness and elongation decreased at the same time, so temper process was introduced. Appling proper temper parameters, the values of toughness and elongation were improved dramatically, and the strength decreased slightly.

Self-Learning and Its Application to Laminar Cooling Model of Hot Rolled Strip

The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.