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This article deals with the exhaust emissions from aircraft turbine engines, which is related to the rapidly growing market for this type of aircraft and its contribution to toxic emissions. The test carried out was done on a business jet turbine engine exhaust pollutants. The test object was the DGEN 380 engine. In order to determine the toxic composition of the exhaust gas as a function of the engine's operating range, an experiment related to the actual engine was conducted in the first stage. The test performed on the static thrust stand of the DGEN 380 turbine engine provided the necessary data on the parameters of the working medium for further research. The actual rotational characteristics of the engine were obtained. It was also determined numerically using GasTurb software. A high correspondence between experimental and calculated parameters was obtained, which gave the possibility of using them in further analyses of the exhaust gas pollutants of the studied engine. The correspondence of the results showed the correctness of the computational model built, thus predestining it for use in further analysis. This paper presents a model of the reverse-flow combustor made for numerical thermal-fluid studies. The thermal-fluid analysis of the model was performed in the ANSYS Fluent environment. The calculations were performed for three shaft speed. The numerical analysis provided information on changes in pollutant components of the exhaust gas of the DGEN 380 aircraft turbine engine as a function of changes in the shaft speed range. The results showed that the levels of nitrogen oxides depend greatly on shaft speed. The model built and the numerical analyses conducted also provided information about the zones inside of liner casing that affect significantly the amount of pollutant compounds obtained, which can then be used in the work on improving the design in terms of reducing the engine exhaust pollutants.

Bioinformatics is a large group of methods used in biology, mostly for analysis of gene sequences. The algorithms developed for this task have recently found a new application in network threat detection. This paper is an introduction to this area of research, presenting a survey of bioinformatics methods applied to this task, outlining the individual tasks and methods used to solve them. It is argued that the early conclusion that such methods are ineffective against polymorphic attacks is in fact too pessimistic.

Currently, strict requirements are set for aircraft turbine engine performance, which requires introducing larger, more complex, and more loaded compressors. In sub-assemblies designed in this manner, a vital challenge is to maintain stable compressor operation across wide range of operating conditions. This article presents the results of analysis and estimation of the range of unstable operation of an example axial compressor for a turbofan jet engine with high mass flow ratio. The analyses and numerical simulations performed made it possible to estimate the limit performance for compressor operation for two particularly important phases of flight.

The following paper evaluates the strength properties of the critical area of the turbine rotor stage of a jet engine. This is where the blade is attached to the rotor disk. Important aspects of this issue are characteristic geometrical dimensions and operating factors, e.g., changes in rotor speed. In the article, the strength properties of the rotor stage with a trapezoidal blade–disk connection were analyzed using parametric analysis considering fluid–structure interaction (FSI). Virtual models of the compressor rotor stages were developed, including parametric blade–disk connections and discrete models for FEM (finite element method) and CFD (computational fluid dynamics) analyses. The parametric analysis was aimed at assessing selected geometric parameters in terms of their impact on the maximum stresses in the blade root. The analysis performed shows that by changing the blade’s width and thickness angles at the root, we can influence the value of the maximum stresses in the rotor stage. It was noticed that some combinations of these two parameters may negatively affect the value of the stresses in the rim.

The high demands placed on aircraft turbine engines necessitate the use of the latest engine compressors which must be increasingly efficient and more robust due to the increased loads. The key safety issue in this context is to ensure compressor stability over all engine speed ranges and aircraft flight regimes. This paper presents selected areas of research into surge and stall of axial compressors used in aircraft turbine engines based on scientific publications in recent years. On the basis of the analysed literature the authors defined the main research areas into compressor surge, namely: air intake research, compressor research and combined air intake and compressor system research. On the background of the conducted analysis the authors has presented their own areas of research. The aim of this work is to search for an intake-compressor design more passively resistant to stall or surge phenomena without necessity of implementation of complex control systems to prevent compressor stall.

This paper presents an analysis of the causes of damage and fragmentation to the high-pressure turbine (HTP) disc of the RD-33 engine mounted in the MIG-29 aircraft. The authors have carried out an analysis of the changes to the structure of the disc material, both in the areas containing cracks and in the undamaged areas. The impact of structural changes on the alterations in the analysed strength properties along the disc radius was assessed. Material tests were correlated with the analysis of the recorded engine parameters, indicating potential causes of the HPT disc fragmentation.

The paper presents the results of a series of numerical research on the possibility of applying Artificial Neural Networks (ANNs) for ultimate strength calculations of selected parts of rotating machines. The layout and the principle of the algorithm operation were described, beginning from the general assumptions and then moving to the detailed description of the subsequent modules. The effects of applying the algorithm were presented on the example of the analysis of the compressor disc. The significant benefits of using it were the reduction of optimization time by about 40% and the disc weight reduction by 0.5 kg. Accuracy of ANNs was different in each iteration of a presented algorithm. Finally, high accuracy of neural networks was achieved with the following mean values of relevant indices reached in the last iteration: RMSE=0.5983, MAPA=0.0733 and R^2=0.99895. The further perspectives of undertaken research were defined at the end.

In this paper, an assessment of strength properties of the existing blade-disc dovetail joint is presented, taking the parametric optimization of its geometry. A sensitivity of the analysis was carried out to determine the relationship between selected geometric parameters and strength properties of the structure questioned. Results from experiments and computer simulations were compared. In addition, the fatigue life of the structure was analyzed for different materials and using the change of speed ranges and parameterization of geometry.

This article presents a genetic algorithm modification inspired by events related to great extinctions. The main objective of the modification was to minimize the number of objective function solutions until the minimum for the function was established. It was assumed that, within each step, a population should be smaller than that recommended in the applicable literature, the number of iterations should be limited, the solution area should be variable, and a great extinction event should take place following several iterations. Calculations were performed for 10 individuals within a population, 10 iterations, two generations each, with a great extinction event happening once every three iterations. The developed algorithm was presented, capable of indicating the minimum number of Eggholder and Rastrigin functions, with a higher probability than the master algorithm (default “ga” in MATLAB) at the same number of objective function solutions. An algorithm was proposed focusing on minimizing the randomization of the objective function, which may be an alternative to the surrogate model. Typically, the emphasis is on achieving as much accuracy as possible. This article presents a method for minimizing the randomization of the objective function and obtaining the highest possible accuracy. A method is presented which minimizes the disadvantages of the largest computation time and the need to generate many samples for typical genetic algorithms (GAs). Optimization results for the classic GA, GEGA, WOA, SMA, and SSA algorithms for the Eggholder and Rastrigin functions were compared. A modification of the genetic algorithm was made to obtain a global extreme with satisfactory accuracy and a sufficiently high probability, while minimizing the number of samples calculated on the basis of the objective function. The developed methodology was used to fulfill the target function for the turbine disc.

This paper presents selected issues regarding the design of a complex object of a turbine jet engine inlet duct model for the purposes of numerical analysis of the phenomenon of inlet vortex formation. The authors described the process of discretisation in the matter in question and presented certain guidelines for preparing and conducting discretisation of the computational area. The authors presented an example test findings analysis to verify the accuracy of the object's shape, computation grid and the selection of the boundary conditions and solution algorithm. The main part of the paper regards analysis of changes in the location of the vortex (point of stagnation) based on an examination of the impact of changes in the velocity and inlet and gust angles. The authors seek to determine areas and regularity of points of stagnation

This paper presents a numerical analysis of the stability of the flow parameters along the intake duct of an aircraft jet turbine engine. This problem has been investigated by many research teams and was included in the literature analysis. The unstable operation of a turbojet intake system can be the consequence of many adverse factors, including an intake vortex. The investigated intake system, due to its low location to the plane of the airport, is highly susceptible to the formation of an intake vortex. The phenomenon of an intake vortex can, in the worst-case scenario, result in the surging of the turbojet, and even engine stalling. This paper presents a developed model of the forward section of an aircraft, complete with its intake duct, and the method of its discretization. The intake-system model and numerical analysis were performed in Ansys Fluent. The flow parameters adopted for numerical simulations, under specific boundary conditions, corresponded to the operating conditions of the engine cooperating with the investigated intake system. The numerical calculations were performed assuming an air-pressure rise in the end section of the engine-intake system, reflecting the reduction in the pitch angle of the inlet stator blades of the fan. As a result, the pressure distributions in a significant cross section in the intake system were obtained. The results were analyzed with the quantitative distribution of the pressure fields by applying a dimensionless potential-pressure ratio. The pressure ratio enabled a comparative analysis of the nonuniformity of the total-pressure distribution in selected cross sections of the intake system. The results were revealing in terms of growing unstable flows in the flow duct. A major conclusion drawn from the results, by testing the dimensionless potential-pressure ratio, was that, within certain limits, it was possible to improve the flow uniformity by increasing the throttling pressure.

The article presents the process of selecting and optimising artificial neural networks based on the example of determining the stress distribution in a disk-drum structure compressor stage of an aircraft turbine engine. The presented algorithm allows the determination of von Mises stress values which can be part of the penalty function for further mass optimization of the structure. A method of a parametric model description of a compressor stage is presented in order to prepare a reduced stress distribution for training artificial neural networks. A comparative analysis of selected neural network training algorithms combined with the optimisation of their structure is presented. A genetic algorithm was used to determine the optimal number of hidden layers and neurons in a layer. The objective function was to minimise the absolute value of the relative error and standard deviation of stresses determined by FEM and artificial neural networks. The results are presented in the form of the Pareto front due to the stochastic optimisation process.

The article is devoted to the preliminary concept of the Future Planetary Defense System (FPDS) emphasizing astroballistics. This paper is intended to support international efforts to improve the planetary security of Earth. The work covers three areas of knowledge: astronautics, astrodynamics, and astroballistics. The most important part of the presented article is dynamic, contact combat modeling against small, deformable celestial bodies. For these purposes, the original, proprietary hydrocode of the free particle method (HEFPM-G) with gravity was used. The main aim of combat is to redirect potentially hazardous objects (PHOs) to orbits safe for Earth or destroy them. This concept’s first task is to find, prepare, and use dynamic three-dimensional models of the motion of celestial bodies and spacecraft or human-crewed spaceships in the solar system’s relativistic frame. The second task is to prepare the FPDS’ architecture and computer simulation space missions’ initial concepts in the internal part of the solar system. The third and main task covers simulating, using hydrocodes, and selected methods of fighting 100 m diameter rock material asteroids.

This paper presents a selection of issues related to the methods of evaluation and selection of advanced weapon systems for armed forces. The paper’s focus is ranking in the form of typical Multidimensional Comparative Analysis Methods, and the AHP method which represents a large group of Multi-Criteria Decision Analysis methods. Both methods were illustrated with a practical computational example related to combat aircraft. The example can help determine the defensive capabilities of friendly forces; it can also support the decision-making process in the acquisition of novel armament, including aircraft, ships, surface-to-air missile defense systems, etc. Keywords: armament, military aviation, decision making support, multi-criteria analysis, AHP method, ranking.

The aim of the study is to explore the intellectual structure of the field and fronts in research on energy efficiency in the context of cloud computing and thus to contribute to science mapping of the research field. The research process was driven by the following study questions: (1) what are the most influential publications in the research field? and (2) what are the research fronts in the research field? The method of direct citation analysis was employed in the research process. Data for analysis were obtained from the Scopus database and analyzed with the use of VOSviewer science mapping software. In response to the first question, we identified the most influential publications in the research field and analyzed their types (i.e., whether they are original research papers or rather the “context” papers e.g., survey or review papers, framework papers, challenges papers, and study papers). Moreover, a comparison analysis between the types of papers among the most cited “classical” publications and “emerging stars” was conducted. In response to the second research question, we identified five research fronts concentrated around the issues of: virtual machine management (“VM”); task-focus, concerning data replication, task consolidation, and task scheduling (“task”); energy efficiency (“energy”); modelling and optimization (“model”); and energy efficiency in the networking context (“network”).

The structural and strength analysis of the materials used to construct an important engine element such as the turbine is of great significance, at both the design stage and during tests and training relating to emergency situations. This paper presents the results of a study on the chemical composition, morphology, and phased structure of the metallic construction material used to produce the blades of the high- and low-pressure turbines of the RD-33 jet engine, which is the propulsion unit of the MiG-29 aircraft. On the basis of an analysis of the chemical composition and phased structure, the data obtained from tests of the blade material allowed the grade of the alloy used to construct the tested elements of the jet engine turbine to be determined. The structural stability of the material was found to be lower in comparison with the engine operating conditions, which was shown by a clear decrease in the resistance properties of the blade material. The results obtained may be used as a basis for analyzing the life span of an object or a selection of material replacements, which may enable the production of the analyzed engine element.

The dynamic growth in the use of cloud computing systems results in increasing energy consumption. Consequently, more and more attention is given to energy efficiency issues both in research and theory development as well as the business practice of cloud computing systems. In spite of the rapid development of research, the field has not been mapped from the bibliometric perspective yet. This study aims at publication profiling and mapping the thematic structure of the cloud computing energy efficiency research field. Detailed research objectives include: (1) profiling scientific publications in the field, (2) identifying and exploring thematic research areas, (3) identifying emerging topics and discussing their potential as future research lines. The aforementioned objectives are translated into the following study questions: (1) What are the most productive nations, institutions, source titles, and scholars contributing to research on energy efficiency in cloud computing? (2) What does the thematic structure of the research field look like? (3) What are the “hot” research topics attracting scholars’ attention? The research methodology toolbox includes a combination of bibliometric descriptive studies (research profiling), science mapping (keyword co-occurrence analysis), and literature reviews (systematic literature review). Bibliometric data for analysis were elicited from the Scopus database. The VOSviewer software supported bibliometric analysis and data visualization.

Klienckie honeypoty to podstawowe narzędzie do wykrywania zagrożeń dla aplikacji klienckich. Artykuł prezentuje wprowadzenie do tematyki, koncentrując się na wysoko interaktywnych klienckich honeypotach, wykorzystujących kompletne systemy w roli pułapek. Przedstawiony został problem występowania fałszywych alarmów i jego konsekwencje dla użytkowników honeypotów. Artykuł omawia oryginalne podejście do eliminacji tego problemu, oparte na metodach sztucznej inteligencji, przedstawiając zarys sposobu działania i wyniki najważniejszych testów.

The paper discusses the threats to networks of resource-limited things such as wireless sensors and the different mechanisms used to deal with them. A novel approach to threat detection is proposed. MOTHON is a movementassisted threat detection system using mobility to enhance a global threat assessment and provide a separate physical secure channel to deliver collected information.

The paper presents the design and the rationale behind a simple verification protocol for autonomous verification modules, and the architecture enabling use of such modules. The architecture assumes strict separation of all personal metadata and the actual verification data. The paper also describes a prototype implementation of the protocol and its extension enabling the state of the module to be monitored from the main system. The proposed design solves the problem of using advanced verification methods, especially biometric ones, in systems where direct implementation is not possible due to hardware incompatibilities, insufficient resources or other limitations.

The paper presents an application of an RT-family trust management language as a basis for an access control model. The discussion concerns a secure workstation running multiple virtual machines used to process sensitive information from multiple security domains, providing strict separation of the domains. The users may act in several different roles, with different access rights. The inference mechanisms of the language are used to translate credentials allowing users to access different functional domains, and assigning virtual machines to these domains into clear rules, regulating the rights of a particular user to a particular machine, taking into account different periods of validity of different credentials. The paper also describes a prototype implementation of the model.

Most of the traditional access control models, like mandatory, discretionary and role based access control make authorization decisions based on the identity, or the role of the requester, who must be known to the resource owner. Thus, they may be suitable for centralized systems but not for decentralized environments, where the requester and service provider or resource owner are often unknown to each other. To overcome the shortcomings of traditional access control models, trust management models have been presented. The topic of this paper is three different semantics (set-theoretic, operational, and logic- programming) of RTT , language from the family of role-based trust management languages (RT). RT is used for representing security policies and credentials in decentralized, distributed access control systems. A credential provides information about the privileges of users and the security policies issued by one or more trusted authorities. The set-theoretic semantics maps roles to a set of sets of entity names. Members of such a set must cooperate in order to satisfy the role. In the case of logic-programming semantics, the credentials are translated into a logic program. In the operational semantics the credentials can be established using a simple set of inference rules. It turns out to be fundamental mainly in large- scale distributed systems, where users have only partial view of their execution context. The core part of this paper is the introduction of time validity constraints to show how that can make RTT language more realistic. The new language, named RTT+ takes time validity constraints into account. The semantics for RTT+ language will also be shown. Inference system will be introduced not just for specific moment but also for time intervals. It will evaluate maximal time validity, when it is possible to derive the credential from the set of available credentials. The soundness and completeness of the inference systems with the time validity constraints with respect to the set-theoretic semantics of RTT+ will be proven.

The optimization flow control algorithm for traffic control in computer networks, introduced by Steven H. Low, works only for concave utility functions. This assumption is rather optimistic and leads to several problems, especially with streaming applications. In an earlier paper we introduced a modification of the algorithm based on the idea of proximal convexification. In this paper we extend this approach, replacing the proximal method with the ρ-proximal method. The new method mixes the quadratic proximal term with higher-order terms, achieving better results. The algorithms are compared in a simple numerical experiment.