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Exsercises

  1. Write 10 questions to each text from the unit.

  2. Write out of each text the sentences with the verbs in the Passive voice.

  3. Translate any part of the texts (1500 signs) in writing.

  4. Retell text about «Turbojet Engines».

  5. 5. Speak on «Turbofan Engines».

Unit IX. Optimization of engine Optimization of Engine Parameters

Research in the performance improvement of gas-turbine or internal combustion engines commenced immediately after they were created. Until recently, key factors in this field included engine cycle parameters, turbine inlet temperature and total compression ratio. However, further improvement of engine performance can only be achieved by new design solutions, advanced materials, effective and coordinated operation of individual components within an engine’s system, maximum degree of airframe/engine integration, and smart computer-based engine control systems.

However, the increase in the number of techniques employed to improve engine working processes makes engine operational development virtually impossible by conventional methods. Therefore, CAD (computer-aided design66) technology is vitally important to research processes for engine components and their optimization. Most improvements in the efficiency of engines and their components can be achieved in the optimization of designs with multiple parameters, the area where developer’s intuition and experience are not sufficient and, in our opinion, where new technological solutions can be found.

CAD techniques, which fully account for gas-dynamics interaction, heat and mass exchange, strength, reliability, production technology, control and cost issues, are evidently effective for the optimization of aircraft engine’s parameters. Yet the research in and analysis of the best technological solutions using traditional techniques for engine component optimization face many difficulties, including:

– optimization of designs witch multiple parameters (tens and even hundreds of variables);

– topological complexity of goal functions and constraints;

– considerable amount of CPU time required;

– multiple criteria of tasks etc.

Currently, few results are known on the practical optimization of aero engine performance.

In this connection, the techno-Pulsar Research and Engineering Enterprise has developed a new, highly effective optimization technology to increase gas-dynamic efficiency (specific fuel consumption, thrust, specific weight, acceleration time, etc.) and cost efficiency (production, operating and modernization costs) for various engine designs. Our technology is based on unique numerical optimization methods which feature the following advantages compared to existing techniques:

– comparatively small number of direct calls to the mathematical simulator of object under research to achieve the result;

– sufficiently high probability of determining global extreme in multi-extreme tasks;

– capability to solve single-criterion and multi-criteria deterministic and stochastic tasks with multiple variables and constraints;

– simple use of all mathematical simulators.

Our technology, designed to form various alternative optimal solutions and provide new methods for improving engine efficiency, fulfills the following tasks:

– optimal design (new engine’s development or existing engine’s modernization);

– search for optimal control laws for controllable engine elements, including the substantiation of their rational quantity and composition;

– optimal design of controllable objects (a combination of optimized design and optimized control tasks).

For example, our technology used to modernize an engine compressor by only reshaping all blade rims and air flow section (140 design parameters were optimized) produced a 3,5-percent increase of compressor efficiency in a wide range of engine ratings.

Our experience indicates that under this technology the volume of computations and the time of overall effort to solve multivariable tasks can be reduced by two to three orders of magnitude. In addition, if a mathematical simulator can not be developed, our methods can be used for optimizing a full-scale object on a test stand.

For example, for the experimental adjustment of microprocessor-based internal combustion engine control systems, fast-running optimization procedures are required to find the requisite solution within a limited number of experiments. The efficiency of our technology was assessed when it was put to the task of fast search for the optimal adjustment of an experimental VAZ car’s engine control system. The task involved the search for optimal gas mixture control, ignition advance angle and exhaust gas recycling. It was necessary to find optimal parameters for each power and speed engine rating which would ensure minimum fuel consumption at specified exhaust gas toxicity levels. Each optimization task (for a given engine rating) was characterized by three variables and three limitations and was solved by 14 experiments, while the traditional method would have required at least 100 experiments.

The resultant analysis demonstrated that our optimization technology can be effectively used for fast experimental adjustment of microprocessor-based engine control systems. It also provides for the stable solution of tasks involving optimal adjustment of these systems, requires a small number of calls for an object under research to determine optimal parameters, and can be used to find a solution in case of errors in the course of experimental adjustment.

Modern CAD technology application in engine-building requires the integration of theoretical/computational research with industrial production.

This research for the most part uses the so-called deterministic approach which assumes that its results will be most precisely implemented in production which, however, cannot be provided by the most advanced production technology. At the R@D phases, a required production technology level is only considered in the mathematical model of an object under research, at best. At the same time, during the search for the optimum solution, a real range of design parameters is not considered. As a result, the probability of accurate project implementation at the production phase is low. Therefore, search for the most effective technical solutions without full consideration of the production technology level will not assure parameters specified at the engine development phase. This design solution does not fully correspond to the optimal one, as it does not consider the probability of the project’s implementation. The problem can be successfully solved via the stochastic optimization of the gas-turbine engine and its components, making it possible to achieve a probability of the project’s implementation of almost 1.0, with only an insignificant decrease in efficiency compared to the deterministic solution.

The Techno-Pulsar’s optimization technology can be used to:

– develop engines accounting or a concrete production technology level;

– determine the probability of achieving specified parameters in case of a technology level decrease at some production lines;

– substantiate the requisite production technology level and product production technology requirements for a new product at the R&D phase;

– search for «choke67 points» affecting engine parameter assurance both at the R&D and production phases;

– introduce certain engine operating features at the R&D phase (for example, only a slight decrease in compressor’s operational performance in the course of its service life in dusty areas by corresponding changes in the geometry of compressor blade).

The list of advantages provided by our technology can be continued. It is noteworthy that the deterministic optimization approach traditionally uses in engine design is only a specific case of stochastic object optimization.

Our technology was used to solve over 500 practical tasks to optimize aircraft gas turbine engines and their components with about 200 articles sent for production development and the update of existing type (a prototype improvement task). The results were implemented at the Lulka-Suturn JSC, Samara-based Kuznetsov Research and Engineering Complex, Snecma, etc. our main task was to increase the efficiency of engine components and reduce fuel consumption. Over 80 percent of results led to efficiency increases of more that one percent. These results were received for the same design configurations and the same number of limitations as those for the prototypes. In fact, our technology provides an opportunity to discover and use to the maximum extent potentialities of existing gas turbine engines which cannot be revealed by the conventional methods.

Our technology was widely proven and recognized by leading Russian and foreign specialists in the aviation engine industry. In part, the technology was demonstrated at the INFO’89, Engines’92, Engines’96 and MAKS’97 international exhibitions.

The technology and its results were discussed at the ISAIF- 1, ISALF-3 and ASME TURBO-EXPO’92, ’93, ’94, ’97, ’98, symposia which led over 20 research reports that were published in the USA, Great Britain, France and China.

We believe that our optimization technology will help develop a new concept for the increase of engine efficiency. It will considerably reduce engine efficiency, enhance the general proficiency level of experts and help cope with difficult and multifaceted problems which will challenge the aviation industry in the future.