Primary Production and the Hydrochemical Parameters of the Salt Lakes in the North-Western Part of the Crimea(Russia)

1 Introduction It is known that more than 300 lakes and lagoons are present in the Crimean Peninsula,which are divided depending on position to 7 groups:Perekop,Tarkhankut,Evpatoriyskaya,Khersonesskaya,lake on the mountainpastures,Kerch and Genicheskaya.Almost the all lakes,with the exception of the small freshwater lakes,which situated on mountain pastures of the Main ridge of

Beam Parameter Product Optimization for High Power SWIR Laser Diode Stack Fiber Coupling

An optimized setup for fiber optic injection of a kilowatt peak power laser diode stack emitting in the SWIR spectral range is proposed. Starting from a fast axis collimated (FAC) and slow axis collimated (SAC) 15 bars, 19 emitters off the shelf laser diode stack, the beam is transformed using spatial beam combining and polarization coupling. Both techniques integrated in a compact design enable to couple the kilowatt level beam into a standard 600 μm core, 0.22 numerical aperture (NA) multimode optical fiber. An application in the field of long range SWIR laser illuminator for gated viewing is presented. A comparison between two illuminators is realized both based on the same laser diode stack but one using beam parameter product (BPP) reduction and one without. It could be demonstrated that BPP reduction is the best way for efficient, narrow divergence and compact semi-conductor based laser illuminators design and realization. The global laser illuminator efficiency could be improved by 75% for the narrowest divergences thanks to this approach.

Prediction of rock brittleness using nondestructive methods for hard rock tunneling

Sand production is an undesired phenomenon occurring in unconsolidated formations due to shear failure and hydrodynamic forces. There have been many approaches developed to predict sand production and prevent it by changing drilling or production strategies. However, assumptions involved in these approaches have limited their applications to very specific scenarios. In this paper, an elliptical model based on the borehole shape is presented to predict the volume of sand produced during the drilling and depletion stages of oil and gas reservoirs. A shape factor parameter is introduced to estimate the changes in the geometry of the borehole as a result of shear failure. A carbonate reservoir from the south of Iran with a solid production history is used to show the application of the developed methodology. Deriving mathematical equations for determination of the shape factor based on different failure criteria indicate that the effect of the intermediate principal stress should be taken into account to achieve an accurate result. However, it should be noticed that the methodology presented can only be used when geomechanical parameters are accurately estimated prior to the production stage when using wells and field data.

HOSVD-based LPV modeling and mixed robust H_2/H_∞ control design for air-breathing hypersonic vehicle

This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.

A quasi-isentropic model of a cylinder driven by aluminized explosives based on characteristic line analysis

A quasi-isentropic study on the process of driving a cylinder with aluminized explosives was carried out to examine the influence of the aluminum(Al) reaction rate on cylinder expansion and the physical parameters of the detonation products. Based on the proposed quasi-isentropic hypothesis and relevant isentropic theories, the characteristic lines of aluminized explosives driving a cylinder were analyzed,and a quasi-isentropic model was established. This model includes the variation of the cylinder wall velocity and the physical parameters of the detonation products with the Al reaction degree. Using previously reported experimental results, the quasi-isentropic model was verified to be applicative and accurate. This model was used to calculate the physical parameters for cylinder experiments with aluminized cyclotrimethylenetrinitramine explosives with 15.0 % and 30.0 % Al content. The results show that this quasi-isentropic model can be used not only to calculate the cylinder expansion rule or Al reaction degree, but also to calculate the physical parameters of the detonation products in the process of cylinder expansion. For explosives with 15.0 % and 30.0 % Al, 24.3 % and 18.5 % of the Al was found to have reacted at 33.9 μs and 34.0 μs, respectively. The difference in Al content results in different reaction intensity, occurrence time, and duration of two forms of reaction(diffusion and kinetic) between the Al powder and the detonation products;the post-detonation burning reaction between the Al powder and the detonation products prolongs the positive pressure action time, resulting in a continuous rise in temperature after detonation.

An energy consumption prediction approach of die casting machines driven by product parameters

Die casting machines,which are the core equipment of the machinery manufacturing industry,consume great amounts of energy.The energy consumption prediction of die casting machines can support energy consumption quota,process parameter energy-saving optimization,energy-saving design,and energy efficiency evaluation;thus,it is of great significance for Industry 4.0 and green manufacturing.Nevertheless,due to the uncertainty and complexity of the energy consumption in die casting machines,there is still a lack of an approach for energy consumption prediction that can provide support for process parameter optimization and product design taking energy efficiency into consideration.To fill this gap,this paper proposes an energy consumption prediction approach for die casting machines driven by product parameters.Firstly,the system boundary of energy consumption prediction is defined,and subsequently,based on the energy consumption characteristics analysis,a theoretical energy consumption model is established.Consequently,a systematic energy consumption prediction approach for die casting machines,involving product,die,equipment,and process parameters,is proposed.Finally,the feasibility and reliability of the proposed energy consumption prediction approach are verified with the help of three die casting machines and six types of products.The results show that the prediction accuracy of production time and energy consumption reached 91.64%and 85.55%,respectively.Overall,the proposed approach can be used for the energy consumption prediction of different die casting machines with different products.