The performance of variable cycle engine was optimized both in single and double bypass mode with an improved differential evolution algorithm. The variable cycle engine's major cycle parameters, the varying schedules of the geometry components and the fuel flow were used as optimization variables. The required thrust and compressor surge margins were used as constraints. The optimization goal was to minimize fuel consumption or maximize thrust performance. Two different base vectors and self-adaptive control parameters were applied to accelerate convergence speed. A uniformity mutation operation was used for poor fitness individuals and a Gaussian mutation operation for the current best fitness individual was added to enhance population diversity. It is shown that the developed differential evolution algorithms present better performance. The procedure provides variable cycle engine's design point optimization and off-design point optimization. Besides, an integrated optimization of both points optimizations was developed, presenting the most remarkable performance. The present work obtains the most favorable match on design parameters and the adjusting schedule of variable cycle engine. Np= the number of population vectors D = the number of parameters g = generation counter X i,g = target vector V i,g = mutation vector U i,g = trial vector i = target vector index j = parameter index F = mutation scale factor Cr = crossover rate Cp = mutation rate X U = upper limit of parameter X L = lower limit of parameter F U = upper limit of F F L = lower limit of F Cr U = upper limit of Cr Cr L = lower limit of Cr f(X) = fitness function π = pressure ratio B = bypass ratio T 4 = burner exit total temperature S = surge margin A = area 2 θ = inlet guide vanes angle Fn = net thrust sfc = special fuel consumption wf = fuel flow H = height Ma = Mach number

Herein, we developed a dual fluorescent aptasensor based on mesoporous silica to simultaneously detect sulfadimethoxine (SDM) and oxytetracycline (OTC) in animal-derived foods. We immobilized two types of aptamers modified with FAM and CY5 on the silica surface by base complementary pairing reaction with the cDNA modified with a carboxyl group and finally formed the aptasensor detection platform. Under optimal conditions, the detection range of the aptasensor for SDM and OTC was 3–150 ng/mL (R2 = 0.9831) and 5–220 ng/mL (R2 = 0.9884), respectively. The limits of detection for SDM and OTC were 2.2 and 1.23 ng/mL, respectively. The limits of quantification for SDM and OTC were 7.3 and 4.1 ng/mL, respectively. Additionally, the aptasensor was used to analyze spiked samples. The average recovery rates ranged from 91.75 to 114.65% for SDM and 89.66 to 108.94% for OTC, and all coefficients of variation were below 15%. Finally, the performance and practicability of our aptasensor were confirmed by HPLC, demonstrating good consistency. In summary, this study was the first to use the mesoporous silica-mediated fluorescence aptasensor for simultaneous detection of SDM and OTC, offering a new possibility to analyze other antibiotics, biotoxins, and biomolecules.

The inter-turbine burner (ITB) engine, which is introduced ITB between high and low pressure turbines, is a relatively new concept for increasing specific thrust and lowering high altitude specific fuel consumption (SFC) than engine with afterburner. While ITB engine brings outstanding performance improvement, it also brings challenges to the ITB engine control law design under unknown matching mechanism and multi-constraint. In this study, a self-scheduling control law design method for ITB engine mode transition that takes into account the ITB ignition and flameout characteristics and cooling air volume is proposed. This method derives the control law based on the global optimal algorithm and SHAP-value (SHapley additive exPlanation) analysis method, which avoids manual analysis and reduces the number of adjustment of variable geometric components. An ITB transient model is established to verify the control laws under the switching of ignition and flameout modes. Both flow fluctuations do not exceed 2%, and thrust fluctuations do not exceed 4% and 2% respectively. During the transition between the two modes, at most one variable geometry component is adjusted.

This work presents an optimization design process for a high bypass unmixed turbofan engine. The optimization design process contains a constraint analysis model, a mission analysis model, an engine cycle parameter optimization model, an engine performance model and an emission prediction model. The constraint analysis model is provided to establish the relationship between thrust to weight ratio and wing loading at takeoff. The mission analysis model is adopted to calculate the aircraft takeoff weight, the maximum thrust at takeoff and the required thrust in cruise. The engine cycle parameter optimization model is based on the self-adaptive three times variation differential evolution (STTVDE) which is developed from the differential evolution algorithm to find the engine cycle parameters minimizing the specific fuel consumption in cruise. The high compressor exit temperature limit, combustor exit temperature limit, engnine size, engnine weight and turbine expansion ratio as well as required thrust in cruise and takeoff which calculated from the constraint analysis and the mission analysis are used as constraint parameters in the engine cycle parameter optimization model. The emission prediction model is used to calculate the landing takeoff (LTO) emission cycle for NO x , CO and UHC based on Boeing fuel flow methodology and T 3 -P 3 methodology. The engine performance model and the mission analysis model are employed to calculate the fuel consumption in the flight mission when engine cycle parameters are determined. Finally, five optimization cases are to be optimized, and their fuel consumptions are compared with each other in the mission analysis model. NomenclaturePropulsion and Energy Forum MFP = mass flow rate parameter m • = mass flow rate NO x = nitrous dioxide N = number n = load factor P = pressure q = dynamic pressure R = additional drage; range S = wing planform area T = temperature t = time; total UHC = unburned hydrocarbon u = total drag to thrust ratio V = velocity W = weight x = variable in function Geek letter α = installed thrust lapse β = instantaneous weight fraction γ = path angle θ = pitch angle ϑ = dimensionless temperature ratio (T/T Ref ) μ = coefficient of friction σ = standard deviation Γ = empty aircraft weight fraction Superscript -= average Subscripts C = constraint c = compressor cor = corrected mass flow rate e = empty f = fuel L = lower boundary p = payload pe = expendable payload pp = permanent payload Ref = reference SLS = sea level static th = throat TO = takeoff U = upper boundary V = variable 0 = upstream of an engine 3 = high pressure compressor exit section 4 = combustor exit section Abbreviations BPR = bypass ratio FAR = fuel air ratio HPCR = high pressure compressor pressure ratio HPT = high pressure turbine LPT = low pressure turbine IFPR = inner fan pressure ratio OFPR = outer fan pressure ratio American Institute of Aeronautics and Astronautics 2 Downloaded by PRINCETON UNIVERSITY on August 11, 2015 | http://arc.aiaa.org |