Performance of pulsed plasma thruster at low discharge energy

As the size of satellites scales down, low-power and compact propulsion systems such as the pulsed plasma thruster(PPT) are needed for stabilizing these miniature satellites in orbit. Most PPT systems are operated at 2 J or more of discharge energy. In this work, the performance of a PPT with a side-fed, tongue-flared electrode configuration operated within a lower discharge energy range of 0.5-2.5 J has been investigated. Ablation and charring of the polytetrafluoroethylene propellant surface were analyzed through field-effect scanning electron microscopy imaging and energy-dispersive X-ray spectroscopy. When the discharge energy fell below 2 J, inconsistencies occurred in the specific impulse and the thrust efficiency due to the measurement of the low mass bit. At energy ≥2 J, the performance parameters are compared with other PPT systems of similar configuration and discussed in depth.

Determination of Physiological Biochemical Parameters and Reproductive Performance in Transgenic sFat-1 Gene Pigs

[Objective] The aim was to evaluate the health of transgenic sFat-1 gene pigs in order to provide a reference for the breeding selection of pig excellent individuals. [Method] 15 physiological biochemical parameters and reproductive performances of 21 negative control pigs and 20 transgenic sFat-1 gene pigs were determined. [Result] The liver functions of some transgenic sFat-1 gene pigs were hurted lightly,and the reproductive performance also decreased lightly. [Conclusion] The determination of physiological biochemical parameters and reproductive performance in transgenic pigs could be taken as one of effective methods in environmental safety evaluation of transgenic pigs.

Aeroengine Performance Parameter Prediction Based on Improved Regularization Extreme Learning Machine

Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.

Effects of early energy and protein restriction on growth performance, clinical blood parameters, carcass yield, and tibia parameters of broilers

financially supported by the Science and Technology Develop Project of Northern Jiangsu, China （BN2015136）;the Priority Academic Program Development of Jiangsu Higher Education Institution, China

Performance characteristics of an energy selective electron refrigerator with double resonances

This paper establishes the energy selective electron （ESE） engine with double resonances as a refrigerator in one dimensional （1D） system. It consists of two infinitely large electron reservoirs with different temperatures and chemical potentials, and they are perfectly thermally insulated from each other and interaction only via a double ＇idealized energy filter＇ whose widths are all finite. Taking advantage of the density of state and Fermi distribution in the 1D system, the heat flux into each reservoir may then be calculated. Moreover, the coefficient of performance may be derived from the expressions for the heat flux into the hot and cold reservoirs. The performance characteristic curves are plotted by numerical analysis. The influences of the resonances widths, the energy position of resonance and the space of two resonances on performance of the ESE refrigerator are discussed. The results obtained here have theoretical significance for the understanding of thermodynamic performance of the micro-nano devices.

Performance of an irreversible quantum refrigeration cycle

A new model of a quantum refrigeration cycle composed of two adiabatic and two isomagnetic field processes is established. The working substance in the cycle consists of many non-interacting spin-1/2 systems. The performance of the cycle is investigated, based on the quantum master equation and semi-group approach. The general expressions of several important performance parameters, such as the coefficient of performance, cooling rate, and power input, are given. It is found that the coefficient of performance of this cycle is in the closest analogy to that of the classical Carnot cycle. Furthermore, at high temperatures the optimal relations of the cooling rate and the maximum cooling rate are analysed in detail. Some performance characteristic curves of the cycle are plotted, such as the cooling rate versus the maximum ratio between high and low ＂temperatures＂ of the working substances, the maximum cooling rate versus the ratio between high and low ＂magnetic fields＂ and the ＂temperature＂ ratio between high and low reservoirs. The obtained results are further generalized and discussed, so that they may be directly applied to describing the performance of the quantum refrigerator using spin-J systems as the working substance. Finally, the optimum characteristics of the quantum Carnot and Ericsson refrigeration cycles are derived by analogy.

Assessment of Patulin Content in Apple Puree and Apple and Fruit Puree by High Performance Liquid Chromatography

An analytical method was developed and validated for determination of patulin in apple puree by HPLC. Extraction and clean-up ofpatulin from clear extract are achieved on AFFINIMIP SPEPATULIN cartridges. Patulin is then separated on a Hypersil GOLD column 150 mm × 4 mm, 5 μtmand detected at 276 nm. The recovery in the range of 5 μg/kg-80 μg/kg was 81.47%. The limit of detection （LOD） was 1.36 μg/kg, and the limit of quantification （LOQ） was 4.55 μg/kg. The patulin content of the commercial samples of apple puree and samples of apple and fruit puree forinfants and young children as well as the samples of apple puree prepared from two apple varieties intended for processing （Jonathan, Florina） and obtained from conventional and uncertified organic cultures has been evaluated in this paper. The 44.83% patulin concentration of the analyzed samples were under the maximum level of the European Commission Regulation （EC） 1881/2006, in 46.55% of the analyzed samples patulin was not detected and in 8.62% of samples patulin concentration was lower than LOQ （European Comission, 2006a） Patulin was not detected in samples of apple puree intended for infants and young children consumption.

Performance Study of Refrigeration Units That Use the Refrigerant R-404A by Using Computer Simulation

The performance parameters of vapor compression refrigeration units that used the refrigerant R-404A were studied by developing a computer simulation algorithm. The various performance parameters investigated per one kilowatt of refrigeration capacity, such as the mass flow rate, the compressor power consumption, the condenser heat rejection rate, the compressor exit temperature and the coefficient of performance. Two refrigeration cycles were tested under various evaporating and condensing temperatures: the standard cycle and the ideal cycle with superheating and sub-cooling. The results of the present work reveal that the compressor power variation over the evaporating temperature range from –10℃ to 15℃at Tc = 40℃ is decreased by 38.8% for standard cycle and by 43.8% for ideal cycle. The compressor power variation over the condensing temperature range from 30℃ to 50℃ at Te = 10℃ is increased by 122% for standard cycle and by 54.5% for ideal cycle. On the other hand, the COP for the ideal cycle with 5℃ superheating and sub-cooling is approximately 25% higher than that of the standard cycle at Te = 10℃ and Tc = 40℃ for the refrigerant R-404A.

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.

液氧煤油发动机混合比调整技术研究

The LM-5B carrier rocket’s first stage is equipped with eight 120 t.thrust high-pressure staged combustion LOX/kerosene engines(YF-100).The YF-100 engine features a throttle valve in the main fuel path,which allows the adjustment of the throttle area,thereby controlling the engine’s mixture ratio.Engine parameters for the throttle valve were determined based on design conditions(mixture ratio of 2.6),and the engine was then tested for ignition.After testing,if the mixture ratio was found not to meet the overall requirements of the rocket,the throttle area could be adjusted prior to subsequent ignition or installation in the whole system,enabling a secondary adjustment of the mixture ratio.This paper outlines the methodology for static parameter calculations of the engine and the analysis of internal and external interference factors,and presents a scheme for the secondary adjustment of the engine’s mixture ratio and examines the precision of this secondary adjustment.The mixture ratio adjustment technology can notably reduce the dispersion range of mixture ratios for YF-100 engines.Moreover,the influence of mixture ratio adjustment on engine performance parameters was obtained.The approach of mixture ratio adjustment proposed in this paper lays the technical foundation for the precise adjustment of mixture ratio for future heavy-lift rocket engines.

Fluid characteristic of multiphase fluid in annular space between pump barrel and plunger

The pump performance parameters,such as pump pressure,plunger friction and pump valve resistance,are fundamental parameters of optimal design of pump efficiency and sucker rod pumping system (SRPS).In this paper,considering the characteristic of geometrical nonlinear and rheology property of multiphase fluid,the pump performance parameters are studied.Firstly,a dynamics model of annular fluid flow is built.In the detail,a partial differential equation of annular fluid is established and a computing model of fluid pressure gradient is built.Secondly,the simulation models of plunger friction and hydraulic resistance of pump valve are built.Finally,a novel simulation method of fluid pressure in annular space is proposed with software ANSYS.In order to check up the correction of models proposed in this paper,the comparison curves of experiment and simulation results are given.Based on above model,the whole simulation model of plunger pump is simulated with Visual Basic 6.0.The results show that the fluid friction of pump plunger and instantaneous resistance of pump valve are nonlinear.The impact factors of pump performance parameters are analyzed,and their characteristic curves are given,which can help to optimize the pump motion parameters and pump structural.

Quantitative design of yield components to simulate yield formation for maize in China

Maize(Zea mays L.) stands prominently as one of the major cereal crops in China as well as in the rest of the world.Therefore,predicting the growth and yield of maize for large areas through yield components under high-yielding environments will help in understanding the process of yield formation and yield potential under different environmental conditions.This accurate early assessment of yield requires accuracy in the formation process of yield components as well.In order to formulate the quantitative design for high yields of maize in China,yield performance parameters of quantitative design for high grain yields were evaluated in this study,by utilizing the yield performance equation with normalization of planting density.Planting density was evaluated by parameters including the maximum leaf area index and the maximum leaf area per plant.Results showed that the variation of the maximum leaf area per plant with varying plant density conformed to the Reciprocal Model,which proved to have excellent prediction with root mean square error(RMSE) value of 5.95%.Yield model estimation depicted that the best optimal maximum leaf area per plant was 0.63 times the potential maximum leaf area per plant of hybrids.Yield performance parameters for different yield levels were quantitatively designed based on the yield performance equation.Through validation of the yield performance model by simulating high yields of spring maize in the Inner Mongolia Autonomous Region and Jilin Province,China,and summer maize in Shandong Province,the yield performance equation showed excellent prediction with the satisfactory mean RMSE value(7.72%) of all the parameters.The present study provides theoretical support for the formulation of quantitative design for sustainable high yield of maize in China,through consideration of planting density normalization in the yield prediction process,providing there is no water and nutrient limitation.

Development of Efficient Classification Systems for the Diagnosis of Melanoma

Skin cancer is usually classified as melanoma and non-melanoma.Melanoma now represents 75%of humans passing away worldwide and is one of the most brutal types of cancer.Previously,studies were not mainly focused on feature extraction of Melanoma,which caused the classification accuracy.However,in this work,Histograms of orientation gradients and local binary pat-terns feature extraction procedures are used to extract the important features such as asymmetry,symmetry,boundary irregularity,color,diameter,etc.,and are removed from both melanoma and non-melanoma images.This proposed Effi-cient Classification Systems for the Diagnosis of Melanoma(ECSDM)framework consists of different schemes such as preprocessing,segmentation,feature extrac-tion,and classification.We used Machine Learning(ML)and Deep Learning(DL)classifiers in the classification framework.The ML classifier is Naïve Bayes(NB)and Support Vector Machines(SVM).And also,DL classification frame-work of the Convolution Neural Network(CNN)is used to classify the melanoma and benign images.The results show that the Neural Network(NNET)classifier’achieves 97.17%of accuracy when contrasting with ML classifiers.

Effect of thermal load on performance parameters of solar concentrating photovoltaic:High-efficiency solar cells

The triple-junction solar cell is designed to exploit a wide range of the solar spectrum photons.These triple-layers consisting of GaInP/GaInAs/Ge,it is monolithically stacked,leading to high conversion efficiency.To describe and understand it’s operating behaviour,this paper presents a performance analysis of a triple-junction solar cell,based on estimation modelling.A model was developed to determine the performance characteristic of the solar cell.Hence,the J-V curve is characterising the performance of solar cells,which used to optimise and improve the design of the cells.It has been discussed the effects of thermal load related to cell temperature increases on the cell’s operating performance parameters.Cell temperature increases from 25 to 125℃ have resulted variances,which causes a significant decrease in efficiency to approximately−17%,open circuit voltage by−15%and fill factor by−4.5%.On the other hand,the current density slightly increased by+5.5%.Finally,ought to consider the thermal management while designing and developing solar CPV technology;therefore,it’s significant to improve cell efficiency and to maintain cell integrity from thermal damage.

Energy and Life Cycle Assessment of Zinc/Water Nanofluid Based Photovoltaic Thermal System

Cooling the PV surface in a Photovoltaic Thermal system is a pivotal operational aspect to be taken into account to achieve optimized values of performance parameters in a Photovoltaic Thermal System.The experimental design used in this study facilitates the flow of varying concentrations of Zn-water nanofluid in serpentine copper tubing installed at the rear of the PV panel thereby preventing the PV surface temperature from increasing beyond the threshold value at which a decrease in electrical efficiency starts to occur.This fusion of solar thermal with PV devices leads to better electrical and thermal efficiency values resulting in decreased cell degradation over time and maximization of the lifespan of the PV module and the energy output from the PV system.Due to the superior thermal heat properties of nanofluids,their usage in such systems has become increasingly widespread.Life cycle metrics which include Energy Payback period,Energy Production Factor and life cycle conversion efficiency were evaluated for the PVT system by exhaustively chalking fundamental parameters such as embodied energy of the PVT setup and the total energy output from the PVT system.This research aims to be a major milestone in the evolutionary journey of Photovoltaic Thermal modules by guiding the engineers working on the theory,design and implementation of PVT systems towards its economic feasibility,environmental impact and energy sustainability.

Influence of the layer parameters on the performance of the CdTe solar cells

Influence of the layer parameters on the performances of the CdTe solar cells is analyzed by SCAPS-1 D. The Zn O: Al film shows a high efficiency than SnO_2:F. Moreover, the thinner window layer and lower defect density of Cd S films are the factor in the enhancement of the short-circuit current density. As well, to increase the open-circuit voltage, the responsible factors are low defect density of the absorbing layer CdTe and high metal work function. For the low cost of cell production, ultrathin film CdTe cells are used with a back surface field(BSF) between CdTe and back contact, such as PbTe. Further, the simulation results show that the conversion efficiency of 19.28% can be obtained for the cell with 1-μm-thick CdTe, 0.1-μm-thick PbTe and 30-nm-thick CdS.

Effect of flue gas outlet temperature in evaporator on thermal economic performance of organic Rankine cycle system for sinter waste heat recovery

In order to improve the recovery and utilization rates of sinter waste heat effectively,the organic Rankine cycle(ORC)system with subcritical cycle was designed to recover the low-temperature sinter cooling flue gas waste heat in an annular cooler for power generation.The thermodynamic,economic and multi-objective optimization models of ORC system were established,and R600a was selected as the ORC working medium.Subsequently,the variations in system thermodynamic performance and economic performance with the ORC thermal parameters were discussed in detail,and the optimal ORC thermal parameters were determined.The results show that the system net output power increases with increasing the evaporation temperature and decreasing the condensation temperature and increases first and then,decreases with the increase in superheat degree for a given flue gas outlet temperature in the evaporator,while the heat transfer area per unit net output power appears different variation trends in various ranges of flue gas outlet temperature.Taking the sinter cooling flue gas waste heat of 160℃as the ORC heat source,the optimal thermal parameters of ORC system were the flue gas outlet temperature of 90℃,the evaporation temperature of 95℃,the superheat degree of 10℃,and the condensation temperature of 28℃.

Optimization and comparative performance analysis of conventional and desiccant air conditioning systems regenerated by two different modes for hot and humid climates:Experimental investigation

A desiccant air conditioning system is considered a capable alternative to a conventional air conditioning system because of its independent control of temperature,humidity and being eco-friendly.Also,to resolve the problem of more energy consumption for the restoration of a desiccant,structures comprising of desiccant can utilize thermal energy or complete waste heat to revive desiccant material.Therefore,this research work executes an experimental,optimization and comparative examination for conventional and desiccant air conditioning sys-tems regenerated by two different modes,i.e.firstly using(Mode-I)complete waste heat from condenser and secondly using(Mode-II)rod(electric heater)heat for regeneration at different process air inlet temperatures,i.e.(28,29.5,31,32.5,34,35.5 and 37°C),at different process air inlet velocities,i.e.(1.5,2.5,3.5 and 4.5 m/s)and a fix(2.5 m/s)regeneration air inlet velocity.Thus,optimization of performance parameters,i.e.VCOP,ECOP,dehumidification effectiveness,moisture removal capacity(kg/hr),DCOP,regeneration effectiveness and regeneration rate(kg/hr),is identified for achieving maximum efficiency of conventional and desiccant air con-ditioning systems under the above operating conditions.

In-cylinder in-depth combustion investigation for a heavy-duty diesel engine

t This present study is part of the design improvement process of a specified high torque low-speed engine.This work aims at carrying out an in-depth analysis of in-cylinder combustion,mesh sensitivity,and engine performance at supercharge conditions to provide a foundation for the design improvement process of the given engine.The computational fluid dynamic(CFD)simulations are carried out on a 3D sector from-130°to 130°crank angle(CA)by employing appropriate models to represent the different physical and chemical processes and using the finite volume method for solving the governing differential equations.An extensive investigation has been carried out for the choice of base mesh size and the number of local and temporal refinements to capture the phenomena happening in the combustion chamber at diverse temporal and local scales.The present results have been validated against available literature experimental and simulation results.Primary field variables and the wellknown four phases of combustion have been studied for gaining in-depth insight into these phenomena.Cylinder average pressure,mean temperature,heat release rate(HRR),integrated heat release rate(IHRR),and emissions of CO2,CO,NOx,HC and soot are presented to assess the quality of combustion.Engine performance analysis has been done in terms of combustion ef-ficiency,gross work,power,torque,and integrated mean effective pressure(IMEP).The base mesh of 1.4 mm may be an appropriate choice during the injection and combustion process spanning throughout around 40CA from the start of injection while in the remaining simulation duration of around 220CA base mesh of 2 mm gives a sufficient resolution.It has been found that maximum heat release takes place in Phase-III,the mixing-controlled phase,of the combustion process.More than 98%combustion efficiency has been achieved in all the simulations.Around 99%of the total heat release and emissions production takes place within 60CA after top dead center(ATDC).

Measuring the spatial quality of bedrooms in nursing homes with visual environmental performance

The elderly's perception of their environment largely depends on acquired visual information.This study provides a quantitative analytical method for designing bedrooms in nursing homes by developing a computational model that uses viewing distance,viewing angle,and viewing field as variables.The model is utilized to measure a range of visual environmental properties,including privacy,accessibility,permeability,and visibility,which reflect the quality of bedrooms in nursing homes.The suitability levels of bedroom planes for the elderly and their main living functions as well as the fitting degree of the functional layout are calculated based on these data.After validating the computational moders feasibility,this study optimizes the typical schemes of single and double rooms in nursing homes.Results reveal certain advantages of the arrangement where bathroom doors are set toward the inside of the bedroom and double rooms have a large width.The computational model can be used in measuring the spatial quality of bedrooms in nursing homes and as a mathematical model for related algorithm design and software programming to assist in the design and optimization of bedrooms for the elderly.