Molecular simulation study of the stabilization process of NEPE propellant

In this reported study, the density functional theory(DFT) was used at the(U)B3LYP/6-311G(d,p) level to investigate the stabilization process of the nitrate ester plasticized polyether propellant(NEPE). Molecular simulations were conducted of the reaction that generates NO_(2), the autocatalytic and aging reaction triggered by the NO_(2), and the nitrogen dioxide absorption reaction of the stabilizers during the propellent stabilization process. These simulations were derived using the transition-state theory(TST)and variational transition-state theory(VTST). The simulation results suggested that the stabilization of the NEPE propellant consisted of three stages. First, heat and NO_(2) were generated during the denitrification reaction of nitroglycerine(NG) and 1,2,4-butanetriol trinitrate(BTTN) in the NEPE propellant.Second, nitroso products were generated by the reactions of N-Methyl-4-nitroaniline(MNA) and 2-nitrodiphenylamine(2NDPA) with NO_(2). Third, the stabilizers were exhausted and the autocatalytic reaction of NG and BTTN and the aging reaction of polyethylene glycol(PEG) were triggered by the heat and NO_(2)generated in the first stage. By comparing the energy barriers of the various reactions, it was found that the NO_(2)generated from the denitrification reaction significantly reduced the reaction energy barrier to 105.56-126.32 kJ/mol, also increased the reaction rate constant, and decreased the thermal stability and energetic properties of the NEPE propellant. In addition, the NO_(2)also weakened the mechanical properties of the NEPE propellant by attacking the-CH2groups and the O atoms in the PEG molecular chain. The energy barriers of the reactions of MNA and 2NDPA with NO_(2)(94.61-133.61 k J/mol) were lower than those of the autocatalytic and decomposition reactions of NG, BTTN, and the aging reactions of PEG(160.30-279.46 kJ/mol). This indicated that, by eliminating NO_(2), the stabilizer in the NEPE propellant can effectively prevent NO_(2)from reacting with the NG, BTTN, and PEG in the NEPE propellant. Consequently, this would help maintain the energy and mechanical properties of the NEPE propellant, thereby improving its thermal stability.

Co-inhibition of methanogens for methane mitigation in biodegradable wastes

The inhibition effects and mechanisms of chlorinated methane and acetylene on methanogenesis in the anaerobic digestion process of the biodegradable wastes were investigated.It was found that both chloroform and acetylene could effectively inhibit methanogens while the biodegradability of the wastes was not affected.Acetylene inhibited the activity of methanogens,while chloroform inhibited metabolic process of methanogenesis.A central composite design（CCD） and response surface regression analysis（RSREG） were employed to determine the optimum conditions and interaction effects of chloroform and acetylene in terms of inhibition effciency,production of volatile fatty acids（VAF） and molar ratio of propionic acid to acetic acid.Chloroform had significant effect on enhancing the production of VFA（F = 121.3;p 〈 0.01）,and acetylene promoted the inhibition effciency（F = 99.15;p 〈 0.05） more effectively than chloroform（F = 9.72;p 〉 0.05）.In addition,a maximum molar ratio of propionic acid to acetic acid of 1.208 was estimated under the optimum conditions of chloroform concentration of 9.05 mg/kg and acetylene concentration of 3.6×10^-3（V/V）.Hence,methanogens in the wastes can be inhibited while the stabilization process of the biodegradable wastes can still work well,as propionic acid generated during the inhibition process could hardly be utilized by methanogens.

Approximate entropy——a new statistic to quantify arc and welding process stability in short-circuiting gas metal arc welding

Based on the phase state reconstruction of welding current in short-circuiting gas metal arc welding using carbon dioxide as shielding gas, the approximate entropy of welding current as well as its standard deviation has been calculated and analysed to investigate their relation with the stability of electric arc and welding process. The extensive experimental and calculated results show that the approximate entropy of welding current is significantly and positively correlated with arc and welding process stability, whereas its standard deviation is correlated with them negatively. A larger approximate entropy and a smaller standard deviation imply a more stable arc and welding process, and vice versa. As a result, the approximate entropy of welding current promises well in assessing and quantifying the stability of electric arc and welding process in short-circuiting gas metal arc welding.

Evaluation model for arc fluctuations of triple-electrode high speed fillet welding

To improve the welding efficiency of conventional arc welding, triple-electrode fillet welding was proposed and developed. Stability of triple-electrode fillet welding process is the assurance for ideal joint. The evaluation model for arc fluctuations of triple-electrode fillet welding was established based on the characteristic parameters and their variation coefficients. This model indicated that variation coefficients could reflect arc voltage flnctuations of welding process, and its analysis result was consistent with the actual welding process.

Stochastic stability of the derivative unscented Kalman filter

This is the second of two consecutive papers focusing on the filtering algorithm for a nonlinear stochastic discretetime system with linear system state equation. The first paper established a derivative unscented Kalman filter（DUKF） to eliminate the redundant computational load of the unscented Kalman filter（UKF） due to the use of unscented transformation（UT） in the prediction process. The present paper studies the error behavior of the DUKF using the boundedness property of stochastic processes. It is proved that the estimation error of the DUKF remains bounded if the system satisfies certain conditions. Furthermore, it is shown that the design of the measurement noise covariance matrix plays an important role in improvement of the algorithm stability. The DUKF can be significantly stabilized by adding small quantities to the measurement noise covariance matrix in the presence of large initial error. Simulation results demonstrate the effectiveness of the proposed technique.

Real-time digital image stabilization based on regional field image gray projection

Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.

Exponential stability of stochastic generalized porous media equations with jump

Stochastic generalized porous media equation with jump is considered. The aim is to show the moment exponential stability and the almost certain exponential stability of the stochastic equation.

Evaluation model for process stability of short-circuiting arc welding

stability of welding process is the prerequisite and assurance for ideal joint. The structure of stability model and its optimization are the key to on-line evaluation technology of arc welding. Characteristic parameters are extracted from the single transfer period while variation coefficients of the characteristic parameters are concerned for whole welding process of continuous drop transfer. Based on the characteristic parameters and their variation coefficients, stability model of short-circuit arc welding process is established by partial-least-square regression （PLSR） that can overcome multicollinearity of input parameters. The experiment results show that this model can meet the requirement of accuracy.

STUDIES ON PROCESS AND STABILITY OF BONDED Sm_2TM_(17)MAGNETS WITH HIGH COERCIVITY AND HIGH ENERGY PRODUCT

The process of the epoxy-bonded Sm_2TM_(17) magnets includes:(1)after melting,the ingots are treated by solid soluiion,and then aged and pulverized;(2)the obtained alloy powder is mixed with epoxy resin bind- er;(3)the mixture is pressed in a magnetic field;(4)the compacts are cured.When the SmCo_(4.9)Fe_(2.7)Cu_(0.54)Zr_(0.13) alloy is heat treated and pressed with optimum pressing parameters,the high quality bonded magnets with B_r=8250 G,_iH_c=13000 Oe,and(BH)_(max)=16MGOe can be obtained.The stability of the magnets is studied also.The irreversible loss of O.C.(open circuit)remanence B_r in the temperature range between 25 and 150℃,is less than 4%.The average temperature coefficient at temperatures between 25 and 70℃ is-0.03%/℃.The magnets obtained have heat resistance up to 130℃ even in long-term service, and have good corrosion resistance in acid,alkali and salt solutions.

Influence of Different Tougheners on the Properties of PC/PBT Alloy

This paper focuses on the influence of glycidyl methacrylate functionalized polyolefin elastomer (SOG-03) on the properties of PC/PBT alloys, and also made a contrastive analysis with ethylene-methyl acrylate-glycidyl methacrylate terpolymer (EMA-co-GMA) and methyl methacrylate-butadiene-styrene terpolymer (MBS), the common toughener in PC/PBT alloy. The impact performance test results of PC/PBT alloys with different addition of SOG-03 showed that the brittle-ductile transition began when SOG-03 content reached 3 wt%. The microstructure, differential scanning calorimeter (DSC) and multi-extrusion process results of PC/PBT alloys all showed that SOG-03 tends to be dispersed in PBT phase and the dispersed SOG-03 presents typical rubber-toughened polymer morphology. The toughening efficiency of MBS on PC/PBT alloy was much lower than EMA-co-GMA and SOG-03, and showed a worse processing stability after multi-extrusion process and long-term thermal ageing properties. The EMA-co-GMA and SOG-03 toughened PC/PBT alloys showed an equivalent toughness, while the PC/PBT alloy with SOG-03 showed a better processing stability during the multi-extrusion process and long-term thermal ageing property when the thermal aging time is more than 600 h.

Evaluation of the stability of shortcut nitrification-denitrification process based on online specific oxygen uptake rate monitoring

Shortcut nitrification-denitrification(SCND)is widely concerned because of its low energy consumption and high nitrogen removal efficiency.However,the current difficulty lies in the stable maintenance of SCND performance,which leads to the challenge of large-scale application of this new denitrification technology.In this study,the nitrogen removal pathway from complete nitrification-denitrification(CND)to SCND was rapidly realized under high free ammonia(FA),high pH and low dissolved oxygen(DO)conditions.The variations of specific oxygen uptake rate(SOUR)of activated sludge in both processes were investigated by an online SOUR monitoring device.Different curves of SOUR from CND to SCND process were observed,and the ammonia peak obtained based on SOUR monitoring could be used to control aeration time accurately in SCND process.Accordingly,the SOUR ratio of ammonia oxidizing bacteria(AOB)to nitrite oxidizing bacteria(NOB)(SOURAOB/SOURNOB)was increased from 1.40 to 2.93.16S rRNA Miseq high throughput sequencing revealed the dynamics of AOB and NOB,and the ratio of relative abundance(AOB/NOB)was increased from 1.03 to 3.12.Besides,SOURAOB/SOURNOB displayed significant correlations to ammonia removal rate(P<0.05),ammonia oxidation rate/nitrite oxidation rate(P<0.05),nitrite accumulation rate(P<0.05)and the relative abundance of AOB/NOB(P<0.05).Thus,a strategy for evaluation the SCND process stability based on online SOUR monitoring is proposed,which provides a theoretical basis for optimizing the SCND performance.

Multiconditional machining process quality prediction using deep transfer learning network

The quality prediction of machining processes is essential for maintaining process stability and improving component quality. The prediction accuracy of conventional methods relies on a significant amount of process signals under the same operating conditions. However, obtaining sufficient data during the machining process is difficult under most operating conditions, and conventional prediction methods require a certain amount of training data. Herein, a new multiconditional machining quality prediction model based on a deep transfer learning network is proposed. A process quality prediction model is built under multiple operating conditions. A deep convolutional neural network (CNN) is used to investigate the connections between multidimensional process signals and quality under source operating conditions. Three strategies, namely structure transfer, parameter transfer, and weight transfer, are used to transfer the trained CNN network to the target operating conditions. The machining quality prediction model predicts the machining quality of the target operating conditions using limited data. A multiconditional forging process is designed to validate the effectiveness of the proposed method. Compared with other data-driven methods, the proposed deep transfer learning network offers enhanced performance in terms of prediction accuracy under different conditions.

Simulation of stabilizing process of dielectric nanoparticle in optical trap using counter-propagating pulsed laser beams

The stabilizing process of glass particle in water by optical trap using the pulsed counter-propagating Gaussian beams is investigated. The influence of the optical power and the particle dimension on the rate and time of the stabilizing process is simulated and discussed.

Synthesis and stability evaluation of hierarchical silicoaluminophosphates with different structural frameworks in the methanol to olefins process

Silicoaluminophosphates （SAPOs） with different pore structures were synthesized through the implementation of polyethylene glycol （PEG） as a mesopores impregnation agent. Using PEGs with different molecular weights （MWs） and concentrations in the synthesis precursor, several samples were synthesized and characterized. Applying a PEG capping agent to the precursors led to the formation of tuned mesopores within the microporous matrix of the SAPO. The effects of the PEG molecular weight and PEG/Al molar ratio were investigated to maximize the efficiency of the catalyst in the methanol-to-olefin （MTO） process. Using PEG with a MW of 6000 resulted in the formation of both Zeolite Rho and chabazite structural frameworks （i.e., DNL-6 and SAPO-34）. Pure SAPO-34 samples were successfully prepared using PEG with a MW of 4000. Our results showed that the PEG concentrations affect the porosity and acidity of the synthesized materials. Furthermore, the SAPO-34 sample synthesized with PEG （MW of 4000） and a PEG/Al molar ratio of 0.0125 showed a superior catalytic stability in the MTO reaction owing to the tuned bi-modal porosity and tailored acidity pattern. Finally, through reactivation experiments, it was found that the catalyst is stable even after several regeneration cycles.

Global attracting sets and stability of neutral stochastic functional differential equations driven by Rosenblatt process

We are concerned with a class of neutral stochastic partial differential equations driven by Rosenblatt process in a Hilbert space. By combining some stochastic analysis techniques, tools from semigroup theory, and stochastic integral inequalities, we identify the global attracting sets of this kind of equations. Especially, some sufficient conditions ensuring the exponent p-stability of mild solutions to the stochastic systems under investigation are obtained. Last, an example is given to illustrate the theory in the work.