48 research outputs found
An analysis of Feature extraction and Classification Algorithms for Dangerous Object Detection
One of the important practical applications of object detection and image classification can be for security enhancement. If dangerous objects e.g. knives can be identified automatically, then a lot of violence can be prevented. For this purpose, various different algorithms and methods are out there that can be used. In this paper, four of them have been investigated to find out which can identify knives from a dataset of images more accurately. Among Bag of Words, HOG-SVM, CNN and pre-trained Alexnet CNN, the deep learning CNN methods are found to give best results, though they consume significantly more resources
ΠΠ½Π°Π»ΠΈΠ·Π°, ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠ°ΡΠ΅ ΠΈ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΠ° Π±Π΅ΡΠΏΠΈΠ»ΠΎΡΠ½Π΅ Π»Π΅ΡΠ΅Π»ΠΈΡΠ΅ Π·Π° Π²Π΅Π»ΠΈΠΊΠ΅ Π²ΠΈΡΠΈΠ½Π΅ Π½Π° ΡΠΎΠ»Π°ΡΠ½ΠΈ ΠΏΠΎΠ³ΠΎΠ½
High-altitude long-endurance (HALE) or High-altitude platform station (HAPS) are
aircraft that can fly in the stratosphere continuously for several months and provide support to military
and civilian needs. In addition, HAPS can be used as a satellite at a fraction of the cost and provide
instant, persistent, and improved situational awareness. Solar energy is the primary source of energy
for these types of unmanned aerial vehicles (UAVs). Solar panels mounted on the wing and
empennage capture solar energy during the day for immediate consumption and conserve the
remainder for use at night. The main challenges to the successful design of HAPS are finding an
appropriate model to calculate airframe weight, materials for structural analysis, designing a wing
and propulsion system so that they can be integrated successfully into a unique aircraft configuration
and these problems need to be solved. Therefore, this thesis investigates /focuses on the concept of
HAPS, optimization of the airfoil, wing design and aerodynamic analysis, experimental analysis of
different materials used in the wing structure, structural analysis of the wing and design of novel
optimized propeller. The topics covered in the chapters are mentioned below.
The first three chapters of this thesis deal with the introduction, review of available literature and
previous relevant research, and background of existing high-altitude aircraft and their configurations.
Then, in Chapter 4, the initial mission requirements, mission profile, basic characteristics of solar
panels, rechargeable batteries, assessment of daily power consumption and battery mass as well as
methodologies for the initial estimation of aircraft structural mass and wing loads are discussed.
Chapter 5 is dedicated to selecting and defining the appropriate airfoil by using potential flow model
and the multi-criteria optimization process. The aerodynamic analysis of wings performed by
computational fluid dynamics is shown in Chapter 6. Calculations of aerodynamic coefficients of the
wing and the flow field around the wing are presented in this chapter.
Chapter 7 is dedicated to the structural design of high-performance slender wings. Tensile tests of a
variety of 3D printed polymers and composite materials as well as the effect of ageing and heat
treatment on the tensile properties of PLA are presented to investigate their mechanical
characteristics. Structural analysis of the wing is presented in Chapter 8. Two different possible
solutions of the aircraft's wing structure for high altitudes are presented and their performance is
compared through static and modal analyses.
Chapter 9 deals entirely with the methodology for designing the optimal propeller intended for highaltitude
unmanned aerial vehicles. Coupled aero-structural optimization was performed using a
genetic algorithm where input and output parameters and constraints were defined from a set of
geometric, aerodynamic, and structural characteristics of the propeller. Finally, main conclusions are
presented in chapter 10.ΠΠ΅ΡΠΏΠΈΠ»ΠΎΡΠ½Π΅ Π»Π΅ΡΠ΅Π»ΠΈΡΠ΅ Π·Π° Π²Π΅Π»ΠΈΠΊΠ΅ Π²ΠΈΡΠΈΠ½Π΅ (Π₯ΠΠΠ, Π₯ΠΠΠ‘) ΡΡ Π°Π²ΠΈΠΎΠ½ΠΈ ΠΊΠΎΡΠΈ ΠΌΠΎΠ³Ρ Π΄Π° Π»Π΅ΡΠ΅ Ρ
ΡΡΡΠ°ΡΠΎΡΡΠ΅ΡΠΈ Π½Π΅ΠΏΡΠ΅ΠΊΠΈΠ΄Π½ΠΎ Π½Π΅ΠΊΠΎΠ»ΠΈΠΊΠΎ ΠΌΠ΅ΡΠ΅ΡΠΈ ΠΈ ΠΏΡΡΠΆΠ°ΡΡ ΠΏΠΎΠ΄ΡΡΠΊΡ Π²ΠΎΡΠ½ΠΈΠΌ ΠΈ ΡΠΈΠ²ΠΈΠ»Π½ΠΈΠΌ ΠΏΠΎΡΡΠ΅Π±Π°ΠΌΠ°.
ΠΠΎΡΠ΅Π΄ ΡΠΎΠ³Π°, ΠΎΠ²Π΅ Π»Π΅ΡΠ΅Π»ΠΈΡΠ΅ ΡΠ΅ ΠΌΠΎΠ³Ρ ΠΊΠΎΡΠΈΡΡΠΈΡΠΈ ΠΈ ΠΊΠ°ΠΎ Π΅ΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ½ΠΈ ΡΠ°ΡΠ΅Π»ΠΈΡΠΈ ΠΈ ΠΎΠ±Π΅Π·Π±Π΅ΡΠΈΠ²Π°ΡΠΈ
ΡΡΠ΅Π½ΡΡΠ½ΠΈ, ΡΡΠ°Π»Π½ΠΈ ΠΈ ΠΏΠΎΠ±ΠΎΡΡΠ°Π½ΠΈ ΡΠ²ΠΈΠ΄ Ρ Π΄Π΅ΡΠ°Π²Π°ΡΠ° Π½Π° ΠΠ΅ΠΌΡΠΈ. Π‘ΡΠ½ΡΠ΅Π²Π° Π΅Π½Π΅ΡΠ³ΠΈΡΠ° ΡΠ΅ Π³Π»Π°Π²Π½ΠΈ ΠΈΠ·Π²ΠΎΡ
Π΅Π½Π΅ΡΠ³ΠΈΡΠ΅ ΠΎΠ²ΠΎΠ³ ΡΠΈΠΏΠ° Π±Π΅ΡΠΏΠΈΠ»ΠΎΡΠ½ΠΈΡ
Π»Π΅ΡΠ΅Π»ΠΈΡΠ°. Π‘ΠΎΠ»Π°ΡΠ½ΠΈ ΠΏΠ°Π½Π΅Π»ΠΈ ΡΠ°ΡΠΏΠΎΡΠ΅ΡΠ΅Π½ΠΈ ΠΏΠΎ ΠΊΡΠΈΠ»Ρ ΠΈ
Ρ
ΠΎΡΠΈΠ·ΠΎΠ½ΡΠ°Π»Π½ΠΈΠΌ ΡΡΠ°Π±ΠΈΠ»ΠΈΠ·Π°ΡΠΎΡΠΈΠΌΠ° ΡΠΏΠΈΡΠ°ΡΡ ΡΡΠ½ΡΠ΅Π²Ρ Π΅Π½Π΅ΡΠ³ΠΈΡΡ ΡΠΎΠΊΠΎΠΌ Π΄Π°Π½Π° Π·Π° ΡΡΠ΅Π½ΡΡΠ½Ρ ΠΏΠΎΡΡΠΎΡΡΡ
Π΄ΠΎΠΊ ΡΠ΅ ΠΎΡΡΠ°ΡΠ°ΠΊ ΡΡΠ²Π° Π·Π° Π»Π΅Ρ ΡΠΎΠΊΠΎΠΌ Π½ΠΎΡΠΈ. ΠΡΠ½ΠΎΠ²Π½ΠΈ ΠΈΠ·Π°Π·ΠΎΠ²ΠΈ ΡΡΠΏΠ΅ΡΠ½ΠΎΠΌ ΠΏΡΠΎΡΠ΅ΠΊΡΠΎΠ²Π°ΡΡ Π₯ΠΠΠ‘
Π»Π΅ΡΠ΅Π»ΠΈΡΠ° ΡΡ ΠΈΠ·Π½Π°Π»Π°ΠΆΠ΅ΡΠ΅ ΠΎΠ΄Π³ΠΎΠ²Π°ΡΠ°ΡΡΡΠ΅Π³ ΠΌΠΎΠ΄Π΅Π»Π° Π·Π° ΠΏΡΠΎΡΠ΅Π½Ρ ΡΠ΅ΠΆΠΈΠ½Π΅ Π»Π΅ΡΠ΅Π»ΠΈΡΠ΅, ΠΌΠ°ΡΠ΅ΡΠΈΡΠ°Π»Π° Π·Π°
ΡΡΡΡΠΊΡΡΡΠ°Π»Π½Ρ Π°Π½Π°Π»ΠΈΠ·Ρ, ΠΏΡΠΎΡΠ΅ΠΊΡΠΎΠ²Π°ΡΠ΅ ΠΊΡΠΈΠ»Π° ΠΈ ΠΏΠΎΠ³ΠΎΠ½ΡΠΊΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ° ΠΊΠΎΡΠΈ ΡΠ΅ ΠΌΠΎΠ³Ρ ΡΡΠΏΠ΅ΡΠ½ΠΎ
ΠΈΠ½ΡΠ΅Π³ΡΠΈΡΠ°ΡΠΈ Ρ ΡΠ΅Π΄ΠΈΠ½ΡΡΠ²Π΅Π½Ρ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΡ Π»Π΅ΡΠ΅Π»ΠΈΡΠ΅ ΠΈ ΠΎΠ²ΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ ΠΌΠΎΡΠ°ΡΡ Π±ΠΈΡΠΈ ΡΠ΅ΡΠ΅Π½ΠΈ.
Π‘ΡΠΎΠ³Π°, ΠΎΠ²Π° ΡΠ΅Π·Π° ΠΈΡΡΡΠ°ΠΆΡΡΠ΅/ΡΠ΅ ΡΠΎΠΊΡΡΠΈΡΠ°Π½Π° Π½Π° ΠΊΠΎΠ½ΡΠ΅ΠΏΡ Π₯ΠΠΠ‘-Π°, ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΡ Π°Π΅ΡΠΎΠΏΡΠΎΡΠΈΠ»Π°,
Π΄ΠΈΠ·Π°ΡΠ½ ΠΈ Π°Π΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΡ Π°Π½Π°Π»ΠΈΠ·Ρ ΠΊΡΠΈΠ»Π°, Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»Π½Ρ Π°Π½Π°Π»ΠΈΠ·Ρ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
ΠΌΠ°ΡΠ΅ΡΠΈΡΠ°Π»Π°
ΠΊΠΎΡΠΈΡΡΠ΅Π½ΠΈΡ
Ρ ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΡΠΈΠ»Π°, ΡΡΡΡΠΊΡΡΡΠ°Π»Π½Ρ Π°Π½Π°Π»ΠΈΠ·Ρ ΠΊΡΠΈΠ»Π° ΠΈ Π΄ΠΈΠ·Π°ΡΠ½ Π½ΠΎΠ²Π΅ ΠΎΠΏΡΠΈΠΌΠΈΠ·ΠΎΠ²Π°Π½Π΅
Π΅Π»ΠΈΡΠ΅. Π’Π΅ΠΌΠ΅ ΠΎΠ±ΡΠ°ΡΠ΅Π½Π΅ ΠΏΠΎ ΠΏΠΎΠ³Π»Π°Π²ΡΠΈΠΌΠ° Π½Π°Π²Π΅Π΄Π΅Π½Π΅ ΡΡ Ρ Π½Π°ΡΡΠ°Π²ΠΊΡ.
ΠΡΠ²Π΅ ΡΡΠΈ Π³Π»Π°Π²Π΅ ΠΎΠ²Π΅ ΡΠ΅Π·Π΅ Π±Π°Π²Π΅ ΡΠ΅ ΡΠ²ΠΎΠ΄ΠΎΠΌ, ΠΏΡΠ΅Π³Π»Π΅Π΄ΠΎΠΌ Π΄ΠΎΡΡΡΠΏΠ½Π΅ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ ΠΈ ΠΏΡΠ΅ΡΡ
ΠΎΠ΄Π½ΠΈΡ
ΡΠ΅Π»Π΅Π²Π°Π½ΡΠ½ΠΈΡ
ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ°, ΠΊΠ°ΠΎ ΠΈ ΠΏΡΠ΅Π³Π»Π΅Π΄ΠΎΠΌ ΠΏΠΎΡΡΠΎΡΠ΅ΡΠΈΡ
Π₯ΠΠΠ‘ Π»Π΅ΡΠ΅Π»ΠΈΡΠ° ΠΈ ΡΠΈΡ
ΠΎΠ²ΠΈΡ
ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΠ°. ΠΠ°ΡΠΈΠΌ, Ρ Π³Π»Π°Π²ΠΈ 4, ΡΠ°Π·ΠΌΠ°ΡΡΠ°Π½ΠΈ ΡΡ ΠΏΠΎΠ»Π°Π·Π½ΠΈ Π·Π°Ρ
ΡΠ΅Π²ΠΈ ΠΈ ΠΌΠΈΡΠΈΡΠ°, ΠΎΡΠ½ΠΎΠ²Π½Π΅
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅ ΡΠΎΠ»Π°ΡΠ½ΠΈΡ
ΠΏΠ°Π½Π΅Π»Π° ΠΈ ΠΏΡΡΠΈΠ²ΠΈΡ
Π±Π°ΡΠ΅ΡΠΈΡΠ°, ΠΏΡΠΎΡΠ΅Π½Π° Π΄Π½Π΅Π²Π½Π΅ ΠΏΠΎΡΡΠΎΡΡΠ΅ Π΅Π½Π΅ΡΠ³ΠΈΡΠ΅ ΠΈ
ΠΏΠΎΡΡΠ΅Π±Π½Π΅ ΠΌΠ°ΡΠ΅ Π±Π°ΡΠ΅ΡΠΈΡΠ°, ΠΊΠ°ΠΎ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ Π·Π° ΠΏΠΎΡΠ΅ΡΠ½Ρ ΠΏΡΠΎΡΠ΅Π½Ρ ΠΌΠ°ΡΠ΅ ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅ Π°Π²ΠΈΠΎΠ½Π° ΠΈ
ΠΎΠΏΡΠ΅ΡΠ΅ΡΠ΅ΡΠ° ΠΊΡΠΈΠ»Π°.
ΠΠ»Π°Π²Π° 5 ΠΏΠΎΡΠ²Π΅ΡΠ΅Π½Π° ΡΠ΅ ΠΎΠ΄Π°Π±ΠΈΡΡ ΠΈ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°ΡΡ ΠΎΠ΄Π³ΠΎΠ²Π°ΡΠ°ΡΡΡΠ΅Π³ Π°Π΅ΡΠΎΠΏΡΠΎΡΠΈΠ»Π° ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ΠΌ ΠΌΠΎΠ΄Π΅Π»Π°
ΠΏΠΎΡΠ΅Π½ΡΠΈΡΠ°Π»Π½ΠΎΠ³ ΡΡΡΡΡΠ°ΡΠ° ΠΈ Π²ΠΈΡΠ΅ΠΊΡΠΈΡΠ΅ΡΠΈΡΡΠΌΡΠΊΠΎΠ³ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΎΠ½ΠΎΠ³ ΠΏΠΎΡΡΡΠΏΠΊΠ°. ΠΠ΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠ°
Π°Π½Π°Π»ΠΈΠ·Π° ΠΊΡΠΈΠ»Π° ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΏΡΠΎΡΠ°ΡΡΠ½ΡΠΊΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠΊΠ΅ ΡΠ»ΡΠΈΠ΄Π° ΠΏΡΠΈΠΊΠ°Π·Π°Π½Π° ΡΠ΅ Ρ Π³Π»Π°Π²ΠΈ 6. ΠΠ²Π΄Π΅
ΡΡ ΡΠ°ΠΊΠΎΡΠ΅ ΠΏΡΠΈΠΊΠ°Π·Π°Π½ΠΈ ΠΈ ΠΏΡΠΎΡΠ°ΡΡΠ½Π°ΡΠΈ Π°Π΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈ ΠΊΠΎΠ΅ΡΠΈΡΠΈΡΠ΅Π½ΡΠΈ ΠΊΡΠΈΠ»Π° ΠΊΠ°ΠΎ ΠΈ ΡΡΡΡΡΠ½ΠΎ ΠΏΠΎΡΠ΅
ΠΎΠΊΠΎ ΠΊΡΠΈΠ»Π°.
ΠΠ»Π°Π²Π° 7 ΠΏΠΎΡΠ²Π΅ΡΠ΅Π½Π° ΡΠ΅ ΡΠ½ΡΡΡΠ°ΡΡΠΎΡ ΡΡΡΡΠΊΡΡΡΠΈ Π²ΠΈΡΠΎΠΊΠΎΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ½ΠΈΡ
Π²ΠΈΡΠΊΠΈΡ
ΠΊΡΠΈΠ»Π°. ΠΠΏΠΈΡΠ°Π½Π° ΡΡ
ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΠΌΠ΅ΡΠ΅ΡΠ° Π·Π°ΡΠ΅Π·Π½ΠΈΡ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
3Π ΡΡΠ°ΠΌΠΏΠ°Π½ΠΈΡ
ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠ° ΠΈ
ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΠ½ΠΈΡ
ΠΌΠ°ΡΠ΅ΡΠΈΡΠ°Π»Π°, ΠΊΠ°ΠΎ ΠΈ Π΅ΡΠ΅ΠΊΡΠΈ ΡΡΠ°ΡΠ΅ΡΠ° ΠΈ ΡΠ΅ΡΠΌΠΈΡΠΊΠ΅ ΠΎΠ±ΡΠ°Π΄Π΅ Π½Π° ΠΌΠ΅Ρ
Π°Π½ΠΈΡΠΊΠ΅
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ΅ 3Π ΡΡΠ°ΠΌΠΏΠ°Π½ΠΈΡ
Π΅ΠΏΡΡΠ²Π΅ΡΠ°. Π‘ΡΡΡΠΊΡΡΡΠ°Π»Π½Π° Π°Π½Π°Π»ΠΈΠ·Π° ΠΊΡΠΈΠ»Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΡΠ΅ Ρ Π³Π»Π°Π²ΠΈ
8. ΠΡΠΈΠΊΠ°Π·Π°Π½Π° ΡΡ Π΄Π²Π° ΡΠ°Π·Π»ΠΈΡΠΈΡΠ° ΠΌΠΎΠ³ΡΡΠ° ΡΠ΅ΡΠ΅ΡΠ° ΡΡΡΡΠΊΡΡΡΠ΅ ΠΊΡΠΈΠ»Π° Π°Π²ΠΈΠΎΠ½Π° Π·Π° Π²Π΅Π»ΠΈΠΊΠ΅ Π²ΠΈΡΠΈΠ½Π΅ ΠΈ
ΡΠΏΠΎΡΠ΅ΡΠ΅Π½Π΅ ΡΡ ΡΠΈΡ
ΠΎΠ²Π΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠ΅ ΠΊΡΠΎΠ· ΡΡΠ°ΡΠΈΡΠΊΡ ΠΈ ΠΌΠΎΠ΄Π°Π»Π½Ρ Π°Π½Π°Π»ΠΈΠ·Ρ.
ΠΠ»Π°Π²Π° 9 ΡΠ΅ Ρ ΡΠ΅Π»ΠΎΡΡΠΈ Π±Π°Π²ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠΎΠΌ ΠΏΡΠΎΡΠ΅ΠΊΡΠΎΠ²Π°ΡΠ° ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ Π΅Π»ΠΈΡΠ΅ Π½Π°ΠΌΠ΅ΡΠ΅Π½Π΅
Π±Π΅ΡΠΏΠΈΠ»ΠΎΡΠ½ΠΎΡ Π»Π΅ΡΠ΅Π»ΠΈΡΠΈ Π·Π° Π²Π΅Π»ΠΈΠΊΠ΅ Π²ΠΈΡΠΈΠ½Π΅. ΠΠ²Π΄Π΅ ΡΠ΅ ΡΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΡΠΏΡΠ΅Π³Π½ΡΡΠ° Π°Π΅ΡΠΎ-ΡΡΡΡΠΊΡΡΡΠ°Π»Π½Π°
ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡΠ° ΠΏΠΎΠΌΠΎΡΡ Π³Π΅Π½Π΅ΡΡΠΊΠΎΠ³ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π³Π΄Π΅ ΡΡ ΡΠ»Π°Π·Π½ΠΈ ΠΈ ΠΈΠ·Π»Π°Π·Π½ΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈ ΠΈ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ°ΡΠ°
Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΈ ΠΈΠ· ΡΠΊΡΠΏΠ° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΡΠΊΠΈΡ
, Π°Π΅ΡΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈΡ
ΠΈ ΡΡΡΡΠΊΡΡΡΠ°Π»Π½ΠΈΡ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° Π΅Π»ΠΈΡΠ΅.
ΠΠΎΠ½Π°ΡΠ½ΠΎ, ΠΎΡΠ½ΠΎΠ²Π½ΠΈ Π·Π°ΠΊΡΡΡΡΠΈ Π΄Π°ΡΠΈ ΡΡ Ρ Π³Π»Π°Π²ΠΈ 10
Conceptual design of solar-powered high-altitude long endurance aircraft
The design of high-altitude unmanned aerial vehicles is one of the most current research
topics today in the field of aviation. The possible purposes of such flying platforms are
numerous, from communication hubs, terrain observations, performing various measurements
in the upper layers of the atmosphere, to various military uses. However, these are complex
systems that involve many unresolved scientific and research challenges such as: the necessity
of extremely low airframe weight, low air pressure and density cruising at high altitudes where
air pressure and density are much lower than in the Earthβs vicinity, sub-zero temperatures,
exposure to increased radiation, low Re implying accentuated viscosity effects and decreased
aerodynamic characteristics, assuring complete flight autonomy, need to generate the required
energy for flight solely from solar energy, adequate sizing and control of rechargeable batteries,
etc.
At the beginning, the initial mission requirements, mission profile, assessment of daily
power consumption and battery mass as well as methodologies for the initial estimation of
aircraft structural mass and wing loads are discussed. Then a novel high-lift airfoil specially
designed for low-Re high-altitude flight through multi- objective optimization was designed
by using genetic algorithm. Subsequently, aerodynamic analysis of the wing carried out by the
methods of computational fluid mechanics, specifically by solving Navier-Stokes equations
averaged by Reynolds statistics and closed by a 4-equation turbulent model is shown. Finally,
static analyses of the behavior of wing structures under the combined action of calculated
aerodynamic and gravitational loads were performed, as well as dynamic, modal analyses
(important for knowing the response of the structure in non-stationary operating conditions)
using the finite element method
Towards viable flow simulations of small-scale rotors and blade segments
The paper focuses on the possibilities of adequately simulating complex flow fields that appear around small-scale propellers of multicopter aircraft. Such unmanned air vehicles (UAVs) are steadily gaining popularity for their diverse applications (surveillance, communication, deliveries, etc.) and the need for a viable (i.e. usable, satisfactory, practical) computational tool is also surging. From an engineering standpoint, it is important to obtain sufficiently accurate predictions of flow field variables in a reasonable amount of time so that the design process can be fast and efficient, in particular the subsequent structural and flight mechanics analyses. That is why more or less standard fluid flow models, e.g. Reynolds-averaged NavierβStokes (RANS) equations solved by the finite volume method (FVM), are constantly being employed and validated. On the other hand, special attention must be given to various flow peculiarities occurring around the blade segments shaped like airfoils since these flows are characterized by small chords (length-scales), low speeds and, therefore, low Reynolds numbers (Re) and pronounced viscous effects. The investigated low-Re flows include both transitional and turbulent zones, laminar separation bubbles (LSBs), flow separation, as well as rotating wakes, which require somewhat specific approaches to flow modeling (advanced turbulence models, fine spatial and temporal scales, etc). Here, the conducted computations (around stationary blade segments as well as rotating rotors), closed by different turbulence models, are presented and explained. Various qualitative and quantitative results are provided, compared and discussed. The main possibilities and obstacles of each computational approach are mentioned. Where possible, numerical results are validated against experimental data. The correspondence between the two sets of results can be considered satisfactory (relative differences for the thrust coefficient amount to 15%, while they are even lower for the torque coefficient). It can be concluded that the choice of turbulence modeling (and/or resolving) greatly affects the final output, even in design operating conditions (at medium angles-of-attack where laminar, attached flow dominates). Distinctive flow phenomena still exist, and in order to be adequately simulated, a comprehensive modeling approach should be adopted
Optimal Propeller design for future HALE UAV
Osnovne uloge bespilotnih letelica podrazumevaju: osmatranje, nadzor, prenos robe, daljinsko oΔitavanje i razliΔite bezbedonosne zadatke. PoboljΕ‘ana klasa bespilotnih letelica su one koje su posebno projektovane za velike visine leta i duge istrajnosti (uglavnom pri podzvuΔnim brzinama krstarenja). Do sada je probano nekoliko varijanti koje se razlikuju kako po dimenzijama tako i po primenjenim tehniΔkim reΕ‘enjima. UobiΔajeni pristup podrazumeva standarnu konfiguraciju krilotrup-zadnje repne povrΕ‘ine i let pomoΔu elise koja je najefikasnija u tom opsegu brzina. Rad ukratko prikazuje preliminarnu aerodinamiΔku analizu glavnih uzgonskih povrΕ‘ina, ali i detaljniji opis izvedene viΕ‘ekriterijumske optimizacije elise sposobne da obezbedi dovoljni potisak na zadatoj visini i brzini krstarenja. AerodinamiΔke performanse razmatranih elisa procenjene su kombinovanim modelom. Izabrani optimizacioni metod, genetski algoritam, pogodan je za probleme koji ukljuΔuju veliki broj ulaznih promenljivih.The main roles of unmanned air vehicles (UAVs) include: observation, surveillance, transportation, remote sensing and various security tasks. Improved, augmented type of UAVs are high-altitude long-endurance (HALE) aircraft capable and designed, as their name suggests, for lengthy flights at higher altitudes (which also usually implies subsonic cruising velocities). Different variants, in both size and applied technical solutions, have been tried. Common approach incorporates standard wing-fuselage-aft empennage configuration and propelled flight as the most efficient for the required speed range. The paper gives a brief overview of a preliminary aerodynamic analysis of the main lifting surfaces as well as a detailed description of the performed multi-objective optimization of the propeller capable of producing a sufficient amount of thrust at the cruising altitude and speed. Aerodynamic performances of the investigated propellers are estimated by a simple blade element momentum theory (BEMT). The chosen optimizing method, genetic algorithm (GA), is suitable for dealing with a large number of input variables
Effects of Hard Real-Time Constraints in Implementing the Myopic Scheduling Algorithm
Myopic is a hard real-time process scheduling algorithm that selects a suitable process based on a heuristic function from a subset (Window) of all ready processes instead of choosing from all available processes, like original heuristic scheduling algorithm. Performance of the algorithm significantly depends on the chosen heuristic function that assigns weight to different parameters like deadline, earliest starting time, processing time etc. and the size of the Window since it considers only processes from processes (where, knnkβ€). This research evaluates the performance of the Myopic algorithm for different parameters to demonstrate the merits and constraints of the algorithm. A comparative performance of the impact of window size in implementing the Myopic algorithm is presented and discussed through a set of experiments
Optimal Propeller design for future HALE UAV
Osnovne uloge bespilotnih letelica podrazumevaju: osmatranje, nadzor, prenos robe, daljinsko oΔitavanje i razliΔite bezbedonosne zadatke. PoboljΕ‘ana klasa bespilotnih letelica su one koje su posebno projektovane za velike visine leta i duge istrajnosti (uglavnom pri podzvuΔnim brzinama krstarenja). Do sada je probano nekoliko varijanti koje se razlikuju kako po dimenzijama tako i po primenjenim tehniΔkim reΕ‘enjima. UobiΔajeni pristup podrazumeva standarnu konfiguraciju krilotrup-zadnje repne povrΕ‘ine i let pomoΔu elise koja je najefikasnija u tom opsegu brzina. Rad ukratko prikazuje preliminarnu aerodinamiΔku analizu glavnih uzgonskih povrΕ‘ina, ali i detaljniji opis izvedene viΕ‘ekriterijumske optimizacije elise sposobne da obezbedi dovoljni potisak na zadatoj visini i brzini krstarenja. AerodinamiΔke performanse razmatranih elisa procenjene su kombinovanim modelom. Izabrani optimizacioni metod, genetski algoritam, pogodan je za probleme koji ukljuΔuju veliki broj ulaznih promenljivih.The main roles of unmanned air vehicles (UAVs) include: observation, surveillance, transportation, remote sensing and various security tasks. Improved, augmented type of UAVs are high-altitude long-endurance (HALE) aircraft capable and designed, as their name suggests, for lengthy flights at higher altitudes (which also usually implies subsonic cruising velocities). Different variants, in both size and applied technical solutions, have been tried. Common approach incorporates standard wing-fuselage-aft empennage configuration and propelled flight as the most efficient for the required speed range. The paper gives a brief overview of a preliminary aerodynamic analysis of the main lifting surfaces as well as a detailed description of the performed multi-objective optimization of the propeller capable of producing a sufficient amount of thrust at the cruising altitude and speed. Aerodynamic performances of the investigated propellers are estimated by a simple blade element momentum theory (BEMT). The chosen optimizing method, genetic algorithm (GA), is suitable for dealing with a large number of input variables
Towards viable flow simulations of small-scale rotors and blade segments
The paper focuses on the possibilities of adequately simulating complex flow fields that appear around small-scale propellers of multicopter aircraft. Such unmanned air vehicles (UAVs) are steadily gaining popularity for their diverse applications (surveillance, communication, deliveries, etc.) and the need for a viable (i.e. usable, satisfactory, practical) computational tool is also surging. From an engineering standpoint, it is important to obtain sufficiently accurate predictions of flow field variables in a reasonable amount of time so that the design process can be fast and efficient, in particular the subsequent structural and flight mechanics analyses. That is why more or less standard fluid flow models, e.g. Reynolds-averaged NavierβStokes (RANS) equations solved by the finite volume method (FVM), are constantly being employed and validated. On the other hand, special attention must be given to various flow peculiarities occurring around the blade segments shaped like airfoils since these flows are characterized by small chords (length-scales), low speeds and, therefore, low Reynolds numbers (Re) and pronounced viscous effects. The investigated low-Re flows include both transitional and turbulent zones, laminar separation bubbles (LSBs), flow separation, as well as rotating wakes, which require somewhat specific approaches to flow modeling (advanced turbulence models, fine spatial and temporal scales, etc). Here, the conducted computations (around stationary blade segments as well as rotating rotors), closed by different turbulence models, are presented and explained. Various qualitative and quantitative results are provided, compared and discussed. The main possibilities and obstacles of each computational approach are mentioned. Where possible, numerical results are validated against experimental data. The correspondence between the two sets of results can be considered satisfactory (relative differences for the thrust coefficient amount to 15%, while they are even lower for the torque coefficient). It can be concluded that the choice of turbulence modeling (and/or resolving) greatly affects the final output, even in design operating conditions (at medium angles-of-attack where laminar, attached flow dominates). Distinctive flow phenomena still exist, and in order to be adequately simulated, a comprehensive modeling approach should be adopted
Design of optimal flow concentrator for vertical-axis wind turbines using computational fluid dynamics, artificial neural networks and genetic algorithm
Wind energy extraction is one of the fastest developing engineering branches today. Number of installed wind turbines is constantly increasing. Appropriate solutions for urban environments are quiet, structurally simple and affordable small-scale vertical-axis wind turbines (VAWTs). Due to small efficiency, particularly in low and variable winds, main topic here is development of optimal flow concentrator that locally augments wind velocity, facilitates turbine start and increases generated power. Conceptual design was performed by combining finite volume method and artificial intelligence (AI). Smaller set of computational results (velocity profiles induced by existence of different concentrators in flow field) was used for creation, training and validation of several artificial neural networks. Multi-objective optimization of concentrator geometric parameters was realized through coupling of generated neural networks with genetic algorithm. Final solution from the acquired Pareto set is studied in more detail. Resulting computed velocity field is illustrated. Aerodynamic performances of small-scale VAWT with and without optimal flow concentrator are estimated and compared. The performed research demonstrates that, with use of flow concentrator, average increase in wind speed of 20%-25% can be expected. It also proves that contemporary AI techniques can significantly facilitate and accelerate design processes in the field of wind engineering
Structural analysis of small-scale composite propeller blade
Contemporary, light-weight, unmanned air vehicles almost exclusively imply propeller rotors that enable them to hover, as well as to move vertically and horizontally at acceptable amount of required power (that is usually supplied by electric motors). Rotor main parts are blades β curved, rotational lifting surfaces subject to conjugate aerodynamic, inertial and gravitational loads. Their skin is usually made of composite materials, i.e. glass or carbon fibres (or their combination) immersed in epoxy resin. Additional inner structural elements may include shear webs, spar caps, ribs or foam fillers. The goal of the presented research study is conducting and validating structural analysis of a propeller blade by finite element method. Different structural models (containing just skin, or skin with foam filler), materials (glass or carbon, uni-or biaxial plies), and ply-up sequences (differing in layer numbers and orientations) are considered. The complete blade geometry is modelled, including the root and tip sections. The blade is clamed at the root, while computed aerodynamic, inertial and gravitational forces are distributed along its surface (and volume). Since the blade operates in axisymmetric conditions, it was possible to perform static structural analyses. Obtained results include deflection (and deformation) fields, normal and shear stress distributions along the plies, etc. From the acquired numerical values, it is possible to define an adequate blade structure that will be able to withstand all working loads (multiplied by necessary safety factors) and ensure safe flight of the aircraft. Future research may include modal or fatigue analyses of propeller blades