Recent development of catalytic strategies for sustainable ammonia production

Presently,ammonia is an ideal candidate for future clean energy.The Haber-Bosch process has been an essential ammonia production process,and it is one of the most important technological advancements since its invention,sustaining the explosive growth of military munitions industry and fertilizers in the first half of the 20th century.However,the process is facing great challenges:the growing need for ammonia and the demands of environmental protection.High energy consumption and high CO_(2) emissions greatly limit the application of the Haber-Bosch method,and increasing research efforts are devoted to"green"ammonia synthesis.Thermocatalytic,electrocatalytic,and photocatalytic ammonia production under mild conditions and the derived chemical looping and plasma ammonia production methods,have been widely developed.Electrocatalytic and photocatalytic methods,which use low fossil fuels,are naturally being considered as future directions for the development of ammonia production.Although their catalytic efficiency of ammonia generation is not yet sufficient to satisfy the actual demands,considerable progress has been made in terms of regulating structure and morphology of catalyst and improving preparation efficiency.The chemical looping approach of ammonia production differs from the thermocatalytic,electrocatalytic,and photocatalytic methods,and is the method of reusing raw materials.The plasma treatment approach alters the overall ammonia production approach and builds up a new avenue of development in combination with thermal,photocatalytic,and electrocatalytic methods as well.This review discusses several recent effective catalysts for different ammonia production methods and explores mechanisms as well as efficiency of these catalysts for catalytic N2fixation of ammonia.

Energy Efficiency Evaluation Based on Data Envelopment Analysis Integrated Analytic Hierarchy Process in Ethylene Production

Energy efficiency data from ethylene production equipment are of high dimension, dynamic and time sequential, so their evaluation is affected by many factors. Abnormal data from ethylene production are eliminated through consistency test, making the data consumption uniform to improve the comparability of data. Due to the limit of input and output data of decision making unit in data envelopment analysis(DEA), the energy efficiency data from the same technology in a certain year are disposed monthly using DEA. The DEA data of energy efficiency from the same technology are weighted and fused using analytic hierarchy process. The energy efficiency data from different technologies are evaluated by their relative effectiveness to find the direction of energy saving and consumption reduction.

Production sharing contract: An analysis based on an oil price stochastic process

Assuming that oil price follows the stochastic processes of Geometric Brownian Motion （GBM） or the Mean-Reverting Process （MRP）, this paper takes the net present value （NPV） as an economic index and models the PSC in 11 different scenarios by changing the value of each contract element （i.e. royalty, cost oil, profit oil as well as income tax）. Then the NPVs are shown in probability density graphs to investigate the effect of different elements on contract economics. The results show that under oil price uncertainty the influence of profit oil and income tax on NPV are more significant than those of royalty and cost oil, while a tax holiday could improve the contractor＇s financial status remarkably. Results also show that MRP is more appropriate for cases with low future oil price volatility, and GBM is best for high future oil price volatility.

An Improved Analytic Hierarchy Process and Application in Grain Production

Value analysis of grain production influencing factors is a complex decision problem. This paper introduced a modified Analytic Hierarchy Process （AHP） accumulation factor, namely Solving Weight by AHP＇s Accumulation Factor Sequence Evaluating Data. We used the arithmetical average to replace the expert marking, so that the possible decision mistakes by the subjective judgments could be avoided. We computed the case with this method, which obtained attribute value of 17 influencing factors of the potential food production in Heilongjiang Province, and the result of which was reasonable

Process Development and Design of Chlorine Dioxide Production Based on Hydrogen Peroxide

This paper presents a process development and design of chlorine dioxide production based on hydrogen peroxide. The process is characterized by cleaner production, high efficiency, and waste minimization. Optimization of process conditions, selection of equipment, and experiment of recycle of waste acid are carried out. The process design is realized in consideration of several aspects such as operation, material, equipment design and safety. An industrialized process flowsheet is developed according to experiment. A pilot testing is carried out to confirm the lab results. Process design of chlorine dioxide production based on hydrogen peroxide is realized.

A Novel Close-loop Strategy for Integrating Process Operations of Fluidized Catalytic Cracking Unit with Production Planning Optimization

Production planning models generated by common modeling systems do not involve constraints for process operations, and a solution optimized by these models is called a quasi-optimal plan. The quasi-optimal plan cannot be executed in practice some time for no corresponding operating conditions. In order to determine a practi- cally feasible optimal plan and corresponding operating conditions of fluidized catalytic cracking unit （FCCU）, a novel close-loop integrated strategy, including determination of a quasi-optimal plan, search of operating conditions of FCCU and revision of the production planning model, was proposed in this article. In the strategy, a generalized genetic algorithm （GA） coupled with a sequential process simulator of FCCU was applied to search operating conditions implementing the quasi-optimal plan of FCCU and output the optimal individual in the GA search as a final genetic individual. When no corresponding operating conditions were found, the final genetic individual based correction （FGIC） method was presented to revise the production planning model, and then a new quasi-optimal production plan was determined. The above steps were repeated until a practically feasible optimal plan and corresponding operating conditions of FCCU were obtained. The close-loop integrated strategy was validated by two cases, and it was indicated that the strategy was efficient in determining a practically executed optimal plan and corresponding operating conditions of FCCU.

Comparative evaluation of energy and resource consumption for vacuum carbothermal reduction and Pidgeon process used in magnesium production

With the fast development of the application of magnesium based alloys,the demand for primary magnesium is increasing dramatically all over the world.The Pidgeon process is the most widely used process for producing magnesium in China,but suffers from problems such as high energy,resource consumption and environmental pollution.While the process of vacuum carbothermal reduction to produce magnesium(VCTRM)has attracted more and more attention as its advantages,but it has not been well-practiced in industrial applications and there also is no comprehensive and quantitative analysis of this process.This study quantified the flows of resource and energy for the Pidgeon process and the VCTRM process,then compared and analyzed these two processes with each other from three aspects.The VCTRM process results in 63.14%and 69.16%lower of non-renewable mineral resources and energy consumptions when compared to the Pidgeon process,respectively.Moreover,the low energy consumption(2.675 tce vs.8.681 tce)and material to magnesium ratio(2.953:1 vs.6.429:1)of the VCTRM process,which lead to lower greenhouse gas(GHG)emissions(8.777 t vs.26.337 t)and solid waste generation(0.522 t vs.5.465 t)with a decrease of 66.67%and 90.45%,respectively.Results indicate that the VCTRM process is a more environmentally friendly process for magnesium production with high efficiency but low cost and low pollution,and it shows a good potential to be industrialized in the future after solving the bottleneck problem of the reverse reaction.

Research on Anti-noise Processing Method of Production Signal Based on Ensemble Empirical Mode Decomposition(EEMD)

The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.

Global production, processing and utilization of lentil： A review

Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, its usage has been limited in developed countries, especially due to the lower protein digestibility, presence of anti-nutritional factors, flatulence and poor cooking qualities. Processing of lentils including dehulling and splitting and isolation of major fractions, e.g., proteins and starches are some of the strategies that can be adopted to add value and increase consumption of these legumes. This review paper intends to provide detailed overview of lentil＇s global production, nutritional composition and processing methods of lentil. Methods of isolation/characterization of lentil protein and starch and their subsequent application in foods are also presented.

Towards Production and Energy Coupling System Modeling and Simulation for Energy Optimization in the Process Industry

The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.

Change and control of nitrogen in molten steel production process

The change and control of nitrogen content in molten steel was investigated through the production process of "LDBAr-LF-RH-CC". Results show that nitrogen content reduces gradually in converter-steelmaking stage, rises rapidly from the end of converter process to the end of argon station process, continues to increase in ladle furnace process, and decreases slightly in RH refining stage. Since nitrogen is removed mainly by BOF steelmaking and vacuum refining operations, nitrogen in molten steel should be removed as much as possible in these two operations. However, nitrogen uptake should be minimized in other operations of molten steel production process.

The whole process confirmation management and its application in coal mine safe production

After analyzing the reasons for coal mine accidents and the current management methods, effective actions for the implementation of safety management were put forward by carrying out the whole process confirmation management. The ba- sic content and the five implementation steps were described, and the implementation method and the program of every step were introduced. Some rules for the implementation of the whole process confirmation management in coal mine safety pro- duction were explained, such as during the process of preproduction, before descent, descent, after descent, walking in the roadway, post-operation, shift, and hoisting after work. The results show that the guardians and the executors should both con- firm the implementation, which can improve the workers＇ attention and self-awareness to avoid errors in detail and reduce the ＂three violations＂ phenomenon. To ensure the effect of the whole process confirmation management, relevant departments should designate a person-in-charge in the specific work in all stages, make a work plan, and strengthen the internal evaluation.

Predicting Model for Complex Production Process Based on Dynamic Neural Network

Based on the comparison of several methods of time series predicting, this paper points out that it is necessary to use dynamic neural network in modeling of complex production process. Because self feedback and mutual feedback are adopted among nodes at the same layer in Elman network, it has stronger ability of dynamic approximation, and can describe any non linear dynamic system. After the structure and mathematical description being given, dynamic back propagation (BP) algorithm of training weights of Elman neural network is deduced. At last, the network is used to predict ash content of black amber in jigging production process. The results show that this neural network is powerful in predicting and suitable for modeling, predicting, and controling of complex production process.

Assessing environmental impact of magnesium production using Pidgeon process in China

Based on the practice of magnesium production in China, a quantitative evaluation of the environment impact was carried out according to the theory and framework of life cycle assessment(LCA) study. The major gaseous pollutants including CO2, SO2, NOx, CH4, HF and particulates were calculated. The accumulative environmental performances of different energy use strategies and the characterization results, including abiotic depletion potential(ADP), global warming potential(GWP), acidification potential(AP) and human-toxicity potential(HTP) were compared. The results show that the direct emission of fuel combustion in the process is the major contributor to the pollutants emission of magnesium production. Global warming potential and acidification potential make the main contribution to the accumulative environmental impact. The different fuel use strategies in the practice of magnesium production cause much different impacts on the environmental performance. The accumulative environmental impact of coal burned directly is the highest, and that of producer-gas comes to the next, while that of coke-oven gas is the lowest.

Research on Production Process Control Method Combined Stochastic Process Algebra and Stochastic Petri Nets

A hierarchical closed-loop production control scheme integrating scheduling,control and performance evaluation is discussed.Firstly,the production process is divided into two main hierarchies:the lower level is the physical operation level and the upper one is the management level.Secondly,the schedule template for the management level and the activity template for the physical operation level are constructed separately,the tasks in the schedule have the ability to make partial decisions,and the per- formance parameters are introduced into activity template.Thirdly,the two levels use different model representations:stochastic process algebra for the management level whose output is the control commands and stochastic Petri net for the physical operation lev- el which is the execution of the control commands.Then,the integration of the two levels is the control commands mapping into the lower physical operations and the responses feeding back to the upper decision-making that are defined by some transition functions. Under the proposed scheme,the production process control of a flexible assembly is exemplified.It is concluded that the process con- trol model has partial ability to make decision on-line for uncertain and dynamic environments and facilitates reasoning about the be- haviors of the process control,and performance evaluation can be done online for real-time scheduling to ensure the global optimiza- tion.

Genetic Algorithm Based Production Planning for Alternative Process Production

Production planning under flexible job shop environment is studied.A mathematic model is formulated to help improve alternative process production.This model,in which genetic algorithm is used,is expected to result in better production planning,hence towards the aim of minimizing production cost under the constraints of delivery time and other scheduling conditions.By means of this algorithm,all planning schemes which could meet all requirements of the constraints within the whole solution space are exhaustively searched so as to find the optimal one.Also,a case study is given in the end to support and validate this model.Our results show that genetic algorithm is capable of locating feasible process routes to reduce production cost for certain tasks.

ENTROPY PRODUCTION RATE OF THE MINIMAL DIFFUSION PROCESS

The entropy production rate of stationary minimal diffusion processes with smooth coefficients is calculated. As a byproduct, the continuity of paths of the minimal diffusion processes is discussed, and that the point at infinity is absorbing is proved.

Leveraging Robust Artificial Intelligence for Mechatronic Product Development—A Literature Review

Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.

A Typical Production and Elimination Process of Particles in Beijing during Early 2008 Olympic Games

[Objective] The aim was to discuss he produce and elimination rules of particles in Beijing during early 2008 Olympic Games. [Method] Based on the analysis of particulate matter online observation data and meteorological data during the corresponding period in Chinese environmental science college, Hysplit Back trace model and Numerical weather prediction graphs, and combined with the different analytical methods on meteorological flow fields, a typical process of particles in Beijing during early 2008 Olympic Games was studied. [Result] The results indicated that during the ascent stage of PM2.5 concentration, the PM showed gradually aging phenomena; the process controlled by large scale synoptic system mainly. And the weak wind and the high humidity were not in favor of dispersion; the prolonged southerly air mass to bring the pollutant of Hebei, Taijin and Shandong to Beijing; mixing height and temperature curve took the importance role to the pollution. [Conclusion] The study provided theoretical basis for the discussion on factors influencing the production and elimination of particles in the air pollution process.

Production process for ursolic acid

Production of ursolic acid, the anti-hepatitis effective composition from natural plant,Sambucus chinensis Lindl.was carried out and the scale-up preparation technology was studied.Extraction of the herb Sambucus chinensis Lindl.was extracted in reflux with 7 volume times of refluxing ethanol at 80℃ for 1 h for two times.The extract was purified with a selt-made specific impurity remover “YCXY-1” to yield ursolic acid of high purity.A new “Extraction/Gelation” technology for the production of ursolic acid was developed. The specific impurity remover “YCXY-1” showed high effectiveness in purification. The purity of the mass-produced ursolic acid was up to 99.8%. The chemical structure of the product was confirmed by the physicochemical constants and spectroscopic identification. The production of high-purity ursolic acid was optimized with natural plant as raw material and with only ethanol as extracting solvent. The difficulties such as isolation and impurity removal were addressed effectively. The novel technology is reasonable, convenient, practical, low-cost, high-yield, suitable for mass production.