Composition optimization and performance prediction for ultra-stable water-based aerosol based on thermodynamic entropy theory

Water-based aerosol is widely used as an effective strategy in electro-optical countermeasure on the battlefield used to the preponderance of high efficiency,low cost and eco-friendly.Unfortunately,the stability of the water-based aerosol is always unsatisfactory due to the rapid evaporation and sedimentation of the aerosol droplets.Great efforts have been devoted to improve the stability of water-based aerosol by using additives with different composition and proportion.However,the lack of the criterion and principle for screening the effective additives results in excessive experimental time consumption and cost.And the stabilization time of the aerosol is still only 30 min,which could not meet the requirements of the perdurable interference.Herein,to improve the stability of water-based aerosol and optimize the complex formulation efficiently,a theoretical calculation method based on thermodynamic entropy theory is proposed.All the factors that influence the shielding effect,including polyol,stabilizer,propellant,water and cosolvent,are considered within calculation.An ultra-stable water-based aerosol with long duration over 120 min is obtained with the optimal fogging agent composition,providing enough time for fighting the electro-optic weapon.Theoretical design guideline for choosing the additives with high phase transition temperature and low phase transition enthalpy is also proposed,which greatly improves the total entropy change and reduce the absolute entropy change of the aerosol cooling process,and gives rise to an enhanced stability of the water-based aerosol.The theoretical calculation methodology contributes to an abstemious time and space for sieving the water-based aerosol with desirable performance and stability,and provides the powerful guarantee to the homeland security.

Composite Structural Optimization by Genetic Algorithm and Neural Network Response Surface Modeling

Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.

Concurrent multi-scale design optimization of composite frame structures using the Heaviside penalization of discrete material model

This paper deals with the concurrent multi-scale optimization design of frame structure composed of glass or carbon fiber reinforced polymer laminates. In the composite frame structure, the fiber winding angle at the micro-material scale and the geometrical parameter of components of the frame in the macro-structural scale are introduced as the independent variables on the two geometrical scales. Considering manufacturing requirements, discrete fiber winding angles are specified for the micro design variable. The improved Heaviside penalization discrete material optimization interpolation scheme has been applied to achieve the discrete optimization design of the fiber winding angle. An optimization model based on the minimum structural compliance and the specified fiber material volume constraint has been established. The sensitivity information about the two geometrical scales design variables are also deduced considering the characteristics of discrete fiber winding angles. The optimization results of the fiber winding angle or the macro structural topology on the two single geometrical scales, together with the concurrent two-scale optimization, is separately studied and compared in the paper. Numerical examples in the paper show that the concurrent multi-scale optimization can further explore the coupling effect between the macro-structure and micro-material of the composite to achieve an ultralight design of the composite frame structure. The novel two geometrical scales optimization model provides a new opportunity for the design of composite structure in aerospace and other industries.

Contrastive analysis and crashworthiness optimization of two composite thin-walled structures

For the safety protection of passengers when train crashes occur, special structures are crucially needed as a kind of indispensable energy absorbing device. With the help of the structures, crash kinetic-energy can be completely absorbed or dissipated for the aim of safety. Two composite structures(circumscribed circle structure and inscribed circle structure) were constructed. In addition, comparison and optimization of the crashworthy characteristic of the two structures were carried out based on the method of explicit finite element analysis(FEA) and Kriging surrogate model. According to the result of Kriging surrogate model, conclusions can be safely drawn that the specific energy absorption(SEA) and ratio of specific energy absorption to initial peak force(REAF) of circumscribed circle structure are lager than those of inscribed circle structure under the same design parameters. In other words, circumscribed circle structure has better performances with higher energy-absorbing ability and lower initial peak force. Besides, error analysis was adopted and the result of which indicates that the Kriging surrogate model has high nonlinear fitting precision. What is more, the SEA and REAF optimum values of the two structures have been obtained through analysis, and the crushing results have been illustrated when the two structures reach optimum SEA and REAF.

Almost Sure Convergence of Proximal Stochastic Accelerated Gradient Methods

Proximal gradient descent and its accelerated version are resultful methods for solving the sum of smooth and non-smooth problems. When the smooth function can be represented as a sum of multiple functions, the stochastic proximal gradient method performs well. However, research on its accelerated version remains unclear. This paper proposes a proximal stochastic accelerated gradient (PSAG) method to address problems involving a combination of smooth and non-smooth components, where the smooth part corresponds to the average of multiple block sums. Simultaneously, most of convergence analyses hold in expectation. To this end, under some mind conditions, we present an almost sure convergence of unbiased gradient estimation in the non-smooth setting. Moreover, we establish that the minimum of the squared gradient mapping norm arbitrarily converges to zero with probability one.

Composition Optimization and Microstructure Design in MOFs-Derived Magnetic Carbon-Based Microwave Absorbers:A Review

Magnetic carbon-based composites are the most attractive candidates for electromagnetic(EM)absorption because they can terminate the propagation of surplus EM waves in space by interacting with both electric and magnetic branches.Metal-organic frameworks(MOFs)have demonstrated their great potential as sacrificing precursors of magnetic metals/carbon composites,because they provide a good platform to achieve high dispersion of magnetic nanoparticles in carbon matrix.Nevertheless,the chemical composition and microstructure of these composites are always highly dependent on their precursors and cannot promise an optimal EM state favorable for EM absorption,which more or less discount the superiority of MOFs-derived strategy.It is hence of great importance to develop some accompanied methods that can regulate EM properties of MOFs-derived magnetic carbon-based composites e ectively.This review comprehensively introduces recent advancements on EM absorption enhancement in MOFs-derived magnetic carbon-based composites and some available strategies therein.In addition,some challenges and prospects are also proposed to indicate the pending issues on performance breakthrough and mechanism exploration in the related field.

Enhanced recovery of zinc and lead by slag composition optimization in rotary kiln

High-efficiency recovery of Zn and Pb from silicon-rich zinc leaching residues is realized in a rotary kiln.Characterizations by means of XRD,SEM,EDS and ICP reveal that the leaching residue contains 12.4 wt.%SiO_(2),16.1 wt.%Zn,and 7.4 wt.%Pb.Thermodynamic analysis shows that metallic vapor of Zn and Pb can be easily generated from the zinc leaching residue at 1150-1250°C inside the rotary kiln.Viscosities and melting points of 13 slag compositions were analyzed and three slag compositions(47wt.%SiO_(2)-23wt.%CaO-30wt.%FeO,40wt.%SiO_(2)-28wt.%CaO-32wt.%FeO,and 40wt.%SiO_(2)-30wt.%CaO-30wt.%FeO)possessed the desirable physical properties,with the melting point and viscosity in the range of 1150-1280°C and 0.2-0.5 Pa·s,respectively.The industrial tests show that adopting the optimized slag composition can contribute to very high recovery rates of Zn and Pb(97.3%for Zn and 94.5%for Pb),corresponding to slags with very low average contents of Zn and Pb(0.51 wt.%Zn and 0.45 wt.%Pb).The National-Standard leaching tests of the water-quenched slags result in 1.82 mg/L Zn,~0.01 mg/L Cu,0.0004 mg/L As,~0.01 mg/L Cd,0.08 mg/L Pb,and~0.02 mg/L Hg in the leachate,verifying the detoxification of the zinc leaching residue at the same time.

A Simultaneous Optimization Method for the Structure and Compo-sition Differences of a Mass Exchange Network

This article presents a new method to calculate the composition differences （e） for tar g.etin.g the minimum total annualized cost （TAC） of a mass exchange network （MEN）,which is based on the combination of composition interval diagram （CID） with mathematical programming.The total cost target consists of the capital cost of the process units and the operating cost for mass separating agents （MS.As）. The value of total cost varies considerablv with the composition differences, so the values of e should be optimized in order to obtain minimum TAC of a MEN. This articleconsiders ε as a set of unequal variables for each equilibrium equation of a rich-lean stream pair, employing them to build the CID and mathematical model, which optimizes the structure and composition differences simultaneously. Two examples are applied to illustrate the proposed method and the results demonstrate that the approach introduced by this article is simpler and more convenient than the methods in previous literatures.

Study on the Optimal Composition of Chitosan/Nano-TiO_2 Composite Film and Its Application in the Preservation of Jinqiu Pear

Water permeability can be used as a parameter to evaluate the effects of chitosan / nano-TiO2 composite film on the preservation of fruits and vegetables. In this study, using water permeability as the objective function, an L9 （3）3 orthogonal experiment was conducted with addition amounts of chitosan, nano-TiO2 and glycerin as three factors at three levels. According to the experimental results, when the percentages of chitosan, nano-TiO2 and glycerin in chitosan / nano-TiO2 composite film was 2%, 0.03% and 2.5%, respectively （ i. e. , there were 2.0 g of chitosan, 0.03 g of nano-TiO2 and 2.5 g of glycerin per 1130 g composite film solution）, the water permeability of chitesan / nano-TiO2 composite fdm reached the minimum. Chitosan / nano-TiO2 composite film prepared with the optimal composition was used for preservation of Jinqiu pear. The water loss rate, respiratory intensity and good fruit rate of preserved Jinqiu pear were determined, which indicated that the prepared chitosan / nano-TiO2 composite film exhibited good preservative effects.

DEVELOPING A NEW GENERATION OF HIGH PERFORMANCE COMPOSITE CEMENT

This paper proposed a new generation of high performance composite cement which is designed according to the optimization of composition and structure of cement paste and is manufactured by blending the differ ent components with special composite techniques. Each of these components has its different special property, and should be compatible with each other and match each other, and the properties of them are complementary mutually. At present, such kind of high performance composite cement can be manufactured with high reactivity cement clinker, ground granulated blast - furnace slag, high grade fly ash, silica fume etc..

STACKING SEQUENCE OPTIMIZA-TION OF LAMINATED COMPOSITE CYLINDER SHELL FOR MAXIMAL BUCKLING LOAD

A new optimization method for the optimization of stacking of composite glass fiber laminates is developed. The fiber orientation and angle of the layers of the cylindrical shells are sought considering the buckling load. The proposed optimization algorithm applies both finite element analysis and the mode-pursuing sampling （MPS）method. The algorithms suggest the optimal stacking sequence for achieving the maximal buckling load. The procedure is implemented by integrating ANSYS and MATLAB. The stacking sequence designing for the symmetric angle-ply three-layered and five-layered composite cylinder shells is presented to illustrate the optimization process, respectively. Compared with the genetic algorithms, the proposed optimization method is much faster and efficient for composite staking sequence plan.

Isolation of Cordyceps ophioglossoides L2 from Fruit Body and Optimization of Fermentation Conditions for Its Mycelial Growth

A strain isolated from the fruiting body of a fungus parasitized on Elaphomyces was identified as Cordyceps ophioglossoides based on the morphological characteristics and the analysis of ITS-5.8s rDNA sequence. The optimal medium, composition （g·L^-1）, containing sucrose 66.0, yeast powder 10.0, silkworm chrysalises digest 30.0, MgSO4· 7H2O 0.4, and KH2PO4 0.4, Was found using fractional factorial design ancl a central composite design, and the optimization of cultural conditions obtained a result of seed age 6 days, inoculum size 6% （by volume）, initial pH 5.6, temperature 24℃, shaking speed 160 ·＇min^-1 by one-factor-at-a-time method. The maximum biomass reached about 20.2 g·L^-1 after 90 hours culture under the optimal conditions. Elementary nharmaeclogical actlwtties showed that mycelia of C. ophioglossoides L2 from submerged culture promoted Uterus growth in estrogen- depleted mice. In the 15-litre scale-up fermentation, the mycelial biomass was around 19.1 g·L^-1, indicating a promising prospect for this biotechnoloagy and the potency to develoo its medical value.

Service composition based on discrete particle swarm optimization in military organization cloud cooperation

This paper addresses the problem of service composition in military organization cloud cooperation（MOCC）. Military service providers（MSP） cooperate together to provide military resources for military service users（MSU）. A group of atom services, each of which has its level of quality of service（QoS）, can be combined together into a certain structure to form a composite service. Since there are a large number of atom services having the same function, the atom service is selected to participate in the composite service so as to fulfill users＇ will. In this paper a method based on discrete particle swarm optimization（DPSO） is proposed to tackle this problem. The method aims at selecting atom services from service repositories to constitute the composite service, satisfying the MSU＇s requirement on QoS. Since the QoS criteria include location-aware criteria and location-independent criteria, this method aims to get the composite service with the highest location-aware criteria and the best-match location-independent criteria. Simulations show that the DPSO has a better performance compared with the standard particle swarm optimization（PSO） and genetic algorithm（GA）.

A New Nonmonotonic Trust Region Algorithm for A Class of Unconstrained Nonsmooth Optimization

This paper presents a new trust region algorithm for solving a class of composite nonsmooth optimizations. It is distinguished by the fact that this method does not enforce strict monotonicity of the objective function values at successive iterates and that this method extends the existing results for this type of nonlinear optimization with smooth, or piecewise smooth, or convex objective functions or their composition. It is proved that this algorithm is globally convergent under certain conditions. Finally, some numerical results for several optimization problems are reported which show that the nonmonotonic trust region method is competitive with the usual trust region method.

Approximate Optimality Conditions for Composite Convex Optimization Problems

The purpose of this paper is to study the approximate optimality condition for composite convex optimization problems with a cone-convex system in locally convex spaces,where all functions involved are not necessarily lower semicontinuous.By using the properties of the epigraph of conjugate functions,we introduce a new regularity condition and give its equivalent characterizations.Under this new regularity condition,we derive necessary and sufficient optimality conditions ofε-optimal solutions for the composite convex optimization problem.As applications of our results,we derive approximate optimality conditions to cone-convex optimization problems.Our results extend or cover many known results in the literature.

Topology optimization of compliant adaptive wing leading edge with composite materials

An approach for designing the compliant adaptive wing leading edge with composite material is proposed based on the topology optimization. Firstly, an equivalent constitutive relationship of laminated glass fiber reinforced epoxy composite plates has been built based on the symmetric laminated plate theory. Then, an optimization objective function of compliant adaptive wing leading edge was used to minimize the least square error（LSE） between deformed curve and desired aerodynamics shape. After that, the topology structures of wing leading edge of different glass fiber ply-orientations were obtained by using the solid isotropic material with penalization（SIMP） model and sensitivity filtering technique. The desired aerodynamics shape of compliant adaptive wing leading edge was obtained based on the proposed approach. The topology structures of wing leading edge depend on the glass fiber ply-orientation. Finally, the corresponding morphing experiment of compliant wing leading edge with composite materials was implemented, which verified the morphing capability of topology structure and illustrated the feasibility for designing compliant wing leading edge. The present paper lays the basis of ply-orientation optimization for compliant adaptive wing leading edge in unmanned aerial vehicle（UAV） field.

A single-level composite structure optimization method based on a blending tapered model

In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Compared with the conventional multi-level composite structure opti- mization method, this single-level method has many advantages. First, by using a distance variable and a ply group variable, the number of design variables is decreased evidently and independent with the density of sub-regions, which makes the single-level method very suitable for large-scale composite structures. Second, it is very convenient to optimize laminate thickness and stacking sequence in the same level, which probably improves the quality of optimal result. Third, ply con-tinuity can be guaranteed between sub-regions in the single-level method, which could reduce stress concentration and manufacturing difficulty. An example of a composite wing is used to demonstrate the advantages and competence of the single-level method proposed.

Improvement of xylanase production by Aspergillus niger XY-1 using response surface methodology for optimizing the medium composition

Objective: To study the optimal medium composition for xylanase production by Aspergillus niger XY-1 in solid-state fermentation (SSF). Methods: Statistical methodology including the Plackett-Burman design (PBD) and the central composite design (CCD) was employed to investigate the individual crucial component of the medium that significantly affected the enzyme yield. Results: Firstly, NaNO3, yeast extract, urea, Na2CO3, MgSO4, peptone and (NH4)2SO4 were screened as the significant factors positively affecting the xylanase production by PBD. Secondly, by valuating the nitrogen sources effect, urea was proved to be the most effective and economic nitrogen source for xylanase production and used for further optimization. Finally, the CCD and response surface methodology (RSM) were applied to determine the optimal concentration of each sig-nificant variable, which included urea, Na2CO3 and MgSO4. Subsequently a second-order polynomial was determined by multiple regression analysis. The optimum values of the critical components for maximum xylanase production were obtained as follows: x1 (urea)=0.163 (41.63 g/L), x2 (Na2CO3)=?1.68 (2.64 g/L), x3 (MgSO4)=1.338 (10.68 g/L) and the predicted xylanase value was 14374.6 U/g dry substrate. Using the optimized condition, xylanase production by Aspergillus niger XY-1 after 48 h fermentation reached 14637 U/g dry substrate with wheat bran in the shake flask. Conclusion: By using PBD and CCD, we obtained the optimal composition for xylanase production by Aspergillus niger XY-1 in SSF, and the results of no additional expensive medium and shortened fermentation time for higher xylanase production show the potential for industrial utilization.

APPLICATION OF SURROGATE BASED PARTICLE SWARM OPTIMIZATION TO THE RELIABILITY-BASED ROBUST DESIGN OF COMPOSITE PRESSURE VESSELS

A surrogate based particle swarm optimization （SBPSO） algorithm which combines the surrogate modeling technique and particle swarm optimization is applied to the reliability- based robust design （RBRD） of composite pressure vessels. The algorithm and efficiency of SBPSO are displayed through numerical examples. A model for filament-wound composite pressure vessels with metallic liner is then studied by netting analysis and its responses are analyzed by using Finite element method （performed by software ANSYS）. An optimization problem for maximizing the performance factor is formulated by choosing the winding orientation of the helical plies in the cylindrical portion, the thickness of metal liner and the drop off region size as the design variables. Strength constraints for composite layers and the metal liner are constructed by using Tsai-Wu failure criterion and Mises failure criterion respectively. Numerical examples show that the method proposed can effectively solve the RBRD problem, and the optimal results of the proposed model can satisfy certain reliability requirement and have the robustness to the fluctuation of design variables.

Optimized Composition of Functional Bacteria for Bioremediation of Sediment Environment of Shrimp Culture

After the single-strain abilities of organic-pollutant-degrading bacteria in bioremediation of sediment environment of shrimp culture are determined, the multi- strain degrading effect of the compositions of different strains is measured. The results indicate that the multi-strains groups have higher degrading ability than the single -strain groups. Three-strain groups are better than two-strain groups, and four-strain groups are better than three-strain groups and five-strain groups, the groups composed of strains Lt7222, Lt7511, Fc6308 and Gy7018 has the best degrading effect, the CODMn removal rate is 73.2 % in 66 h, and gets to 82.7 % in 114 h, 30 % higher than that of the best single-strain group; Groups of Lt7222, Lt7511, Lt7451 and Gy7018 are the second, whose CODMn removal rate is 82.1 % in 114 h. It is suggested that multi-species bacteria be used as functional bacteria in bioremediation of mariculture environment.