This chapter discusses the direction of development of promising multimode aviation gas turbine engines (GTE). It is shown that the development of GTE is on the way to increase the parameters engine workflow: gas temperatures in front of the turbine (T*G) and the degree of pressure increase in the compressor (P*C). It is predicted that the next generation engines will operate with high parameters of the working process, T*G = 2000–2200 K, π*C = 60–80. At this temperature of gases in front of the turbine, the working mixture in the combustion chamber (CC) is stoichiometric, which sharply narrows the range of stable operation of the CC and its efficiency drops sharply in off-design gas turbine engine operation modes. To expand the range of effective and stable work, it is proposed to use an advanced aviation GTE: Adaptive Type Combustion Chamber (ATCC). A scheme of the ATCC and the principles of its regulation in the system of a multi-mode gas turbine engine are presented. The concept of an adaptive approach is given in this article. There are two main directions for improving the characteristics of a promising aviation gas turbine engine. One is a complication of the concepts of aircraft engines and the other one is an increase in the parameters of the working process, the temperature of the gases in front of the turbine (T*G) and the degree of increasing pressure behind the compressor (π*C). It is shown how the principles of adaptation are used in these areas. The application of the adaptation principle in resolving the contradiction of the possibility of obtaining optimal characteristics of a high-temperature combustion chamber (CC) of a gas turbine engine under design (optimal) operating conditions and the impossibility of their implementation when these conditions change in the range of acceptable (non-design) gas turbine operation modes is considered in detail. The use of an adaptive approach in the development of promising gas turbine engines will significantly improve their characteristics and take into account unknown challenges.

The adaptive control of metal cutting processes is a logical extension of the CNC systems. In CNC systems of metal-cutting processes the machining variables (e.g., the cutting speed and feedrate) are prescribed by the part programmer. The determination of these variables depends on experience and knowledge regarding the workpiece and tool materials, coolant conditions, and other factors.The determination of these operating parameters depends on experience and knowledgeregarding the workpiece and tool materials, coolant conditions, and other factors. By contrast,the main idea in adaptive control is the improvement of the production rate, or the reductionof machining costs, by calculation and setting of the optimal operating parameters duringmachining itself. This calculation is based upon measurements of process variables in real time and is followed by a subsequent on-line adjustment of the machining variables subject to constraints with the objective to optimize the performance of the overall system.The adaptive control is basically a feedback system, in which the operatingparameters automatically adapt themselves to actual condition of the process. AC system formachine tools can be classified into two categories:1.Adaptive control with optimization(ACO);2.Adaptive control with constraints(ACC);ACO refers to systems in which a given performance index (usually an economicfunction) is extremized subject to process and system constraints. With ACC, the machiningparameters are maximized within a prescribed region bounded by process and systemconstraints, such as maximum torque or power. ACC systems, however, do not use aperformance index. In both systems an adaptation strategy is used to vary the operatingparameters in real time cutting progresses. Although there has been considerable research onthe development of ACO systems, few, if any, of these systems are used in practice. The major problems with such systems have been difficulties in defining realistic indexes of performance and the lack of suitable sensors which can reliably measure on-line thenecessary parameters in a production environment. The objective of most AC systems isimprovement in productivity, which is achieved by increasing the metal removal rate (MRR)during rough cutting operations. The increases in productivity range from approximately 20 to 80 percent and clearly depend on the material being machined and the complexity of the part tobe produced.

Promocijas darbā izstrādāta apvirpotas virsmas raupjuma noteikšanas metode grūti apstrādājamām materiālam palielinātos apstrādes režīmos virpošanās procesā bez dzesēšanas emulsijas lietošanas, izmantojot jaunus griezējinstrumentus, kā arī ir izpētīts griešanas process, pētot skaidu veidošanos un griezējinstrumenta nodiluma rezultātu, lietojot analoģiskus instrumentus. Veikts literatūras apskats, un definēti pētījumu virzieni. Apskatītas divu nerūsējošo tēraudu struktūru grupu materiālu apvirpošanas rezultāti, izstrādāti vairāki apvirpošanas procesa matemātiskie modeļi virsmas raupjuma prognozēšanai, lietojot regresijas analīzi. Pētīta materiālu leģējošo elementu ietekme uz skaidu veidošanās procesu, izvērtēta regresijas prognozēšanas modeļu precizitāte, kā arī veikta eksperimentālā modeļa atbilstības pārbaude un apvirpošanas procesa galīgo elementu metodes modelēšana, iegūstot datus, ko nebija iespējams noskaidrot ar praktiskā eksperimenta palīdzību.

In the PhD Thesis a method for determining the roughness of a turned surface for hard-to-machine materials has been developed using increased processing parameters, the application of a turning process without cooling emulsion, using new cutting tools, and the cutting process has been investigated. The Thesis presents the study on the chip formation process and the result of cutting tool wear using the tools produced by different manufacturers. A literature review is presented and research directions are defined. The results of material turning of two groups of stainless steel structures are reviewed. Several mathematical models of the turning process have been developed for predicting surface roughness using regression analysis. The influence of material alloying elements on the chip formation process has been studied. The accuracy of the regression prediction models has been evaluated and an experimental model has been tested. Finite element method modelling of the turning process has been represented and the obtained data, which could not be obtained before, with the help of a practical experiment have been obtained.

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