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The purpose of this paper is to introduce two new automatic methods for evaluating the performance of search engines. The reported study uses the methods to experimentally investigate which search engine among three popular search engines (Ask.com, Bing and Google) gives the best performance.

The study assesses the performance of three search engines. For each one the weighted average of similarity degrees between its ranked result list and those of its metasearch engines is measured. Next these measures are compared to establish which search engine gives the best performance. To compute the similarity degree between the lists two measures called the “tendency degree” and “coverage degree” are introduced; the former assesses a search engine in terms of results presentation and the latter evaluates it in terms of retrieval effectiveness. The performance of the search engines is experimentally assessed based on the 50 topics of the 2002 TREC web track. The effectiveness of the methods is also compared with human‐based ones.

Google outperformed the others, followed by Bing and Ask.com. Moreover significant degrees of consistency – 92.87 percent and 91.93 percent – were found between automatic and human‐based approaches.

The findings of this work could help users to select a truly effective search engine. The results also provide motivation for the vendors of web search engines to improve their technology.

The paper focuses on two novel automatic methods to evaluate the performance of search engines and provides valuable experimental results on three popular ones.

The propulsion system integration of a turboprop aircraft, which has been developed for the basic trainer, was performed. The proper turboprop engine was selected among worldwide existing engines by the specific developed engine selection technique and trade‐off studies such as customer’s request for operational capability (ROC), propulsion system parameters, performance analysis with engine installed effects, future growth potential, integrated logistic support (ILS), maintainability, interfaces with the airframe, etc. The chin type air inlet with the plenum chamber was designed in consideration of the inclined configuration to minimize the propeller swirl effect, the inertial separation bypass device to reduce FOD, and the super‐ellipse and NACA‐1 profile lip to maximize the ram recovery. The air inlet was analyzed by a higher‐order source panel method considering propeller wake. The exhaust duct was designed through internal cross‐section area determination to maximize the cruising power as well as external configuration to maximize the effective power, to minimize the aerodynamic drag and to minimize the cockpit contamination by the exhaust gas. The proper oil cooler for the selected turboprop engine was determined with cooling requirements and the oil cooling inlet duct with NACA configuration was designed. The test of the propulsion system including the installation performance test with the effects of the air inlet, the exhaust duct, the propeller and the nose fuselage configuration was performed in the test cell.

Climate change significantly impacts global temperatures, posing challenges to various sectors, including aviation. The purpose of this study is to assess the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences.

This study examines the effects of rising temperatures on aircraft engine performance using real-time data from a Boeing 787-8 equipped with GEnx-1B engines, which are collected via Flight Data Recorder of the engines and were analyzed for the take-off and cruise phases on the ground. Exhaust gas temperature (EGT), fuel flow and take-off weights were evaluated.

The analysis revealed a significant increase in EGT at the cruising altitude of 38,000 ft during the summer months compared to expected standard atmospheric values. This increase, averaging over 200 °C, is attributed to global warming. Such elevated temperatures are likely to accelerate the degradation of turbine components, resulting in increased fuel consumption: higher EGT signifies inefficient engine operation, resulting in more fuel burned per unit thrust; early engine aging: elevated temperatures accelerate wear and tear on turbine components, potentially reducing engine lifespan and increasing maintenance costs and enhanced atmospheric pollution: incomplete combustion at high EGTs generates additional emissions, contributing to local air quality concerns.

The research findings have practical implications for understanding the potential operational challenges and environmental impacts of climate change on aircraft engine performance. This lets us explore mitigation strategies and adapt operational procedures to ensure sustainable regional aviation practices.

This research enhances environmental consequences by assessing the impact of climate change on aircraft performance.

This study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated features engineering (AFE).

The main concept of engine health status prediction was based on three case studies and a validation process. The first two were performed on the engine health status parameters, namely, performance margin and specific fuel consumption margin. The third one was generated and created for the engine performance and safety data, specifically created for the final test. The final validation of the neural network pattern recognition was the validation of the proposed neural network architecture in comparison to the machine learning classification algorithms. All studies were conducted for ANN, which was a two-layer feedforward network architecture with pattern recognition. All case studies and tests were performed for both simple pattern recognition network and network augmented with automated feature engineering (AFE).

The greatest achievement of this elaboration is the presentation of how on the basis of the real-life engine operational data, the entire process of engine status prediction might be conducted with the application of the neural network pattern recognition process augmented with AFE.

This research could be implemented into the engine maintenance strategy and planning. Engine health status prediction based on ANN augmented with AFE is an extremely strong tool in aircraft accident and incident prevention.

Although turbofan engine health status prediction with ANN is not a novel approach, what is absolutely worth emphasizing is the fact that contrary to other publications this research was based on genuine, real engine performance operational data as well as AFE methodology, which makes the entire research very reliable. This is also the reason the prediction results reflect the effect of the real engine wear and deterioration process.

Purpose — To develop methodologies to evaluate search engines according to an individual's preference in an easy and reliable manner, and to formulate user-oriented metrics to compare freshness and duplication in search results.

Design/methodology/approach — A personalised evaluation model for comparing search engines is designed as a hierarchy of weighted parameters. These commonly found search engine features and performance measures are given quantitative and qualitative ratings by an individual user. Furthermore, three performance measurement metrics are formulated and presented as histograms for visual inspection. A methodology is introduced to quantitatively compare and recognise the different histogram patterns within the context of search engine performance.

Findings — Precision and recall are the fundamental measures used in many search engine evaluations due to their simplicity, fairness and reliability. Most recent evaluation models are user oriented and focus on relevance issues. Identifiable statistical patterns are found in performance measures of search engines.

Research limitations/implications — The specific parameters used in the evaluation model could be further refined. A larger scale user study would confirm the validity and usefulness of the model. The three performance measures presented give a reasonably informative overview of the characteristics of a search engine. However, additional performance parameters and their resulting statistical patterns would make the methodology more valuable to the users.

Practical implications — The easy-to-use personalised search engine evaluation model can be tailored to an individual's preference and needs simply by changing the weights and modifying the features considered. A user is able to get an idea of the characteristics of a search engine quickly using the quantitative measure of histogram patterns that represent the search performance metrics introduced.

Originality/value — The presented work is considered original as one of the first search engine evaluation models that can be personalised. This enables a Web searcher to choose an appropriate search engine for his/her needs and hence finding the right information in the shortest time with the least effort.

In this study, the performance analysis of the split flow turbofan engine with afterburners has been examined using the parametric cycle analysis method. The purpose of this study is to examine how engine performance is impacted by design parameters and flight ambient values and to develop a software in this context.

Software has been developed using the open-source PYTHON programming language to perform performance analysis. Mach number, compressor/fan pressure ratio, bypass ratio and density were used as parameters. The effects of these variables on engine performance parameters were investigated.

Parametric cycle analysis has been calculated for different flight conditions in the range of 0–2 M and 0–15,000 m altitude for turbofan engines. With this study, basic data were obtained to optimize according to targeted flight conditions.

As a result of the performance analysis, the association between the flight conditions and design parameters of engine were determined. A software has been developed that can be used in the design of supersonic gas turbine engines for fast and easy simulation of the design parameters.

The variables used in the literature have been analyzed, and the results of the studies have been incorporated into the developed software, which can be used in innovative engine design. Software is capable to be developed further with the integration of new algorithms and models.

This paper aims to investigate the cycle performance of a small size turbojet engine used in unmanned aerial vehicles at 0–5,000 m altitude and 0–0.8 Mach flight speeds with real component maps.

The engine performance calculations were performed for both on-design and off-design conditions through an in-house code generated for simulating the performance of turbojet engines at different flight regimes. These calculations rely on input parameters in which fuel composition are obtained through laboratory elemental analysis.

Exemplarily, according to comparative results between in-house developed performance code and commercially available software, there is 0.25% of the difference in thrust value at on-design conditions.

Once the on-design performance parameters and fluid properties were determined, the off-design operation calculations were performed based on the compressor and turbine maps and scaling methodology. This method enables predicting component maps and fitting them to real conditions.

A method to be used easily by researchers on turbojet engine performance calculations which best fits to real conditions.

This paper aims to determine the usage time of the test lubricant N0, prepared from base oils of Aliaga Plant, Izmir, in gasoline and diesel‐engines, and the investigations of high‐temperature oxidation, engine‐protective properties, and property changes of the lubricant in performance time.

Physical and chemical properties of the lubricating oil were initially established, and the oil was then subjected to Petter W‐1 gasoline and Petter AV‐1 diesel test engines. Dismantling of the engine parts was followed by the examination of pistons, piston rings and bearings, and analysis of the lubricant was also undertaken. The engine performance test results and the quality control of the lubricating oil assessments were evaluated according to the International Engine Lubricant Specifications.

The lubricating oil, under sluggish experimental conditions, appears to meet a 40‐hour test in gasoline engines and a 120‐hour test in diesel engines with the specifications. This means that under usual working conditions the lubricants keep the engine protective properties in 7,000 km distance for gasoline run‐vehicles, and in 5,000 km distance for diesel run‐vehicles, after which change of the oil is required.

The paper provides information of value to those involved with lubrication and engine performance.

IN all cases, the estimation of airscrew‐engine performance must start with a clear specification of the primary condition for which the airscrew is to be designed. In the majority of cases up to date this primary design condition has been that the airscrew is to absorb the maximum b.h.p. of the engine at maximum permissible r.p.m. at maximum boost height and maximum aircraft speed. (The aircraft speed is obviously an estimate only, but we may assume for the time being that it is reliable.) Under these conditions the airscrew efficiency is required to be the maximum possible.

This paper aims to present the results of a design optimization study for the impeller of a small mixed‐flow compressor. The objective of the optimization is to obtain an impeller geometry that could minimize a cost function based on the specific thrust and the thrust specific fuel consumption of a small turbojet engine.

The design methodology is based on an optimization process that uses a configurational database for various compressor geometries. The database is constructed using design of experiments and the compressor configurations are generated using one‐dimensional in‐house design codes, as well as various tools and programs of the Agile Engineering Design System^®, which is a commercially available turbomachinery design system developed at Concepts NREC. The cost function variations within the design space are represented through a neural network. The optimum configuration that minimizes the cost function is obtained using a direct search optimization procedure.

The optimization study generated a small 86 mm diameter mixed‐flow impeller with a 50° meridional exit angle. The optimized compressor, as well as the engine that it is designed for, were shown to have improved performance characteristics.

Preliminary performance and flow analysis of the optimized impeller show shock structures and possible shock‐boundary layer interactions within the blade passages indicating further geometrical fine tuning may be required based on more detailed computational studies or experimental tests.

A further study including the effect of diffuser is required to carry the results to a more practical level.

The originality and the value of the paper comes mainly from two different aspects: combining various in‐house and commercial turbomachinery design codes in one robust methodology to obtain an optimum mixed‐flow compressor impeller that will maximize the performance requirements of a small unmanned air vehicle (UAV) turbojet engine under restricted size and power conditions; and investigation of the design optimization and analysis of a mixed‐flow compressor that could have potential applications in small jet engines to be used in high‐performance UAV applications. Design optimization studies on this type of compressor are very limited in the open literature. For many years, these compressors have been disregarded because of their bulky design in large‐scale engines. However, as mentioned above, they present a great potential for small‐scale jet engines by supplying enough pressure rise, as well as high mass flow rate compared to their centrifugal counterparts.