This document summarizes numerical investigations on using unsteady fluid injection to reduce drag on an Ahmed body. 2D simulations identified optimal parameters for steady blowing jets but found unsteady jets less effective. 3D simulations showed unsteady jet behavior changes and synthetic jets reducing drag up to 13%. Future work includes additional 3D simulations and experimental validation of active control systems.
Research paper on indoor drone application with acoustic localization. Paper was accepted to the ISEEE 2019 conference (International Symposium on Electrical and Electronics Engineering).
Research paper on indoor drone application with acoustic localization. Paper was accepted to the ISEEE 2019 conference (International Symposium on Electrical and Electronics Engineering).
Shota Yamanaka and Homei Miyashita. Scale Effects in the Steering Time Difference between Narrowing and Widening Linear Tunnels. In Proceedings of NordiCHI 2016.
Episode 39 : Hopper Design
Problem:
1 -experiments with shear box jenike on a particulate catalyst to give the family
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a-from design chart silo cone, do design a mass flow hopper for the material.
b-if the average size is 100 um, calculate the discharge flow rate passing through the discharge opening
2 - For the above materials using stainless steel is required to store 1000 tons of particulate in it. Coefficient of friction at the wall is given as 0.45 for each value and the formula that you use the appropriate justify the design.
a - draw the dimensions of the silo you and draw a vertical stress profile and the wall of the silo whole time say powerful particle
b- specify the maximum vertical stress and the wall of the silo you
c - if you use several different approaches in the design you provide appropriate recommendations to your employer for work before the end of the casting device fabrication started.
d - if problems such as the formation of the entrance are available after a certain time interval suggest measures - flow improvement measures to be taken to your employer
SAJJAD KHUDHUR ABBAS
Ceo , Founder & Head of SHacademy
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
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Shota Yamanaka and Homei Miyashita. Scale Effects in the Steering Time Difference between Narrowing and Widening Linear Tunnels. In Proceedings of NordiCHI 2016.
Episode 39 : Hopper Design
Problem:
1 -experiments with shear box jenike on a particulate catalyst to give the family
yield locus as in 1. given that the bulk density is 1000 kg/m3 particulates and wall friction angle is 15
a-from design chart silo cone, do design a mass flow hopper for the material.
b-if the average size is 100 um, calculate the discharge flow rate passing through the discharge opening
2 - For the above materials using stainless steel is required to store 1000 tons of particulate in it. Coefficient of friction at the wall is given as 0.45 for each value and the formula that you use the appropriate justify the design.
a - draw the dimensions of the silo you and draw a vertical stress profile and the wall of the silo whole time say powerful particle
b- specify the maximum vertical stress and the wall of the silo you
c - if you use several different approaches in the design you provide appropriate recommendations to your employer for work before the end of the casting device fabrication started.
d - if problems such as the formation of the entrance are available after a certain time interval suggest measures - flow improvement measures to be taken to your employer
SAJJAD KHUDHUR ABBAS
Ceo , Founder & Head of SHacademy
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
Optimal and Pid Controller for Controlling Camera's Position InUnmanned Aeria...Zac Darcy
This paper describes two controllers designed specifically for adjusting camera’s position in a small
unmanned aerial vehicle (UAV). The optimal controller was designed and first simulated by using
MATLAB technique and the results displayed graphically, also PID controller was designedand
simulatedby using MATLAB technique .The goal of this paper is to connect the tow controllers in cascade
mode to obtain the desired performance and correction in camera’s position in both roll and pitch.
This article considers different approaches for autopilot controller gain values adjustment. The correct autopilot
performance is tested using modeling methods. A variant of land-based autopilot is considered. Examined are
scenarios of UAV airplanes in level flight. The latter are applicable to tasks such as remote sensing, controlled
area surveillance, etc.
Optimal and pid controller for controlling camera’s position in unmanned aeri...Zac Darcy
This paper describes two controllers designed specifically for adjusting camera’s position in a small unmanned aerial vehicle (UAV). The optimal controller was designed and first simulated by using MATLAB technique and the results displayed graphically, also PID controller was designedand simulatedby using MATLAB technique .The goal of this paper is to connect the tow controllers in cascade mode to obtain the desired performance and correction in camera’s position in both roll and pitch.
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SLIDES_PEGASUS_CALISE
1. Università degli Studi di Napoli Federico II - Facoltà di Ingegneria
Dipartimento di Ingegneria Industriale
Numerical investigations on Ahmed body for
drag reduction with unsteady fluid injection
AIAA Pegasus Student Conference 2013 - Milano (MI) - April 3-6, 2013
2. Table of contents
The problem: cars aerodynamic drag
2D simulations:
Test case 1: synthetic jet into quiescient air
Test case 2: synthetic jet behaviour on CIRA wing section
Active flow control system on Ahmed body
3D simulations:
Active flow control system on Ahmed body
Final Remarks
3. Introduction to the problem
For V > 100 km/h, car fuel consumption is
caused is caused almost for 75 ÷ 80% by its
aerodynamic drag.
Tipically, analysis of car aerodynamic drag
is made on geometrically simplified model
similar to that represented below.
Ahmed body(1984)
The main contribution to its aerodynamic
drag depends on slant angle.
4. Flow structure
Ahmed observed that flow behind the
body exhibit a precise flow structure,
which depends on Φ angle
(0◦
< Φ < 40◦
).
• squareback
• fastback
• notchback
5. Flow control systems
Active control systems
Flexibility
Invisible
Energy supply
Design
Passive control systems
Energy supply
Design
Flexibility
Appearance
Target: find some design indications for the production of an active control
system able to reduce Ahmed body drag.
• Steady blowing
• Unsteady pulsed blowing
• Synthetic jet
These systems are different for their relative operating principle and power
required.
6. Test case 1:
synthetic jet into quiescient air
Test cases are useful to setup the simulations URANS in Star-CCM+
Equation of the simulated synthetic jet V (t) = 10 sin ( 2 π 1000 t )
Computational domain detail
Synthetic jet operating cycle
7. t1 = 0.003 00 s
t3 = 0.003 50 s
t2 = 0.003 25 s
t4 = 0.003 75 s
8. Test case 2:
synthetic jet behaviour on CIRA wing section
Test cases are useful to setup the simulations URANS in Star-CCM+.
Star-CCM+ ability in simulating the interaction between a synthetic jet and
a crossflow was investigated.
Computational domain
Mesh detail
CIRA wing section used during
reference experimental tests
9. Lift curve Drag curve
Red curve represents experimental tests. Blue curve is the simulated CIRA
wing section with no control systems. Cyan curve is the simulated CIRA
wing section with the synthetic jet system, while green curve is relative to
the same case with the unsteady blowing system.
Simulations reveals a ∆Emax
∼= +3% for α = 8◦
, according to the reference
experimental tests.
10. Active flow control systems on 2D Ahmed body
Using Star-CCM+ some trend curves were extracted for the several active flow
control system analyzed.
The simulations were both steady and unsteady, depending on active control
system characteristics.
11. Some mesh details
Probe no
8 reveals that
separation point is located
immediately after the Ahmed
body corner on its slanted
surface
Velocity profile on slanted surface
12. Steady blowing parameters
Active control flow system depends
on many parameters:
• Position (x)
• Mean inflow velocity (|V |)
• Inflow angle (φ)
Injector diameter is fixed (5 mm) and
its shape is not relevant for two
dimensional simulations (only max
diameter is simulated)
Reference frames
13. Some important results are shown below.
• x = 0.005 m position is less sensitive respect to φ changes
• Advantageous inflow angle φ should be small (5◦
φ 20◦
)
• Control jet is ineffective for |V | 20 m/s
• Control jet efficency is not working-well for |V | 40 m/s
Steady two dimensional simulations point out a CD reduction of about 50%.
14. Unsteady jet parameters
An unsteady jet is modelled by V (t) = |V | sin ( 2 π f t) + |Vm|.
To previous parameters, others have to be added:
• inflow frequency (f )
• mean jet velocity (|Vm|)
Mean unsteady jet parameters are chosen having steady simulations as
reference.
Synthetic jet
•
xpre = −0.005 m
xpost = +0.005 m
• |V | = 50 m/s
• |Vm| = 0 m/s
• φ = 90◦
Unsteady blowing
•
xpre = −0.005 m
xpost = +0.005 m
•
|V1| = |Vm1| = 25 m/s
|V2| = |Vm2| = 50 m/s
• φ = 10◦
15. Synthetic jet simulations results
xpre = −0.005 m xpost = +0.005 m
Two dimensional simulations show that using a synthetic jet causes Ahmed body
CD
∗
growth. Increase is proportional to jet frequency f and is greater for
post-corner position; pre-corner configuration is indipendent from frequency f .
16. Unsteady blowing simulations results
xpre = −0.005 m xpost = +0.005 m
Two dimensional simulations show that also using an unsteady jet causes Ahmed
body CD
∗
growth. Jet frequency influence is the same to synthetic jet, causing an
higher CD
∗
increase.
17. Active flow control systems on 3D Ahmed body
2D simulations have shown Ahmed
body pressure drag reduction by
means of a steady blowing jet. From
2D to 3D simulations, unsteady jets
may change their behaviour and
efficency due to three-dimensional
structures growing.
3D computational domain has
about 14M cells.
Some three-dimensional mesh details
18. Two-dimensional (top) and
three-dimensional (bottom)
solutions at z = 0 are
compared.
• New flow acceleration on
3D Ahmed body
• Different velocity and
pressure fields
• 2D Ahmed body has
thicker boundary layer
• 3D wake shape is different
to 2D one
Three-dimensional vortices
effects influence Ahmed body
aerodynamic behaviour
19. Jet outlet has rectangular shape (0.379 m x 0.002 m). It extends for more than
95% of the width of the Ahmed body.
20. 1
Synthetic jet Velocity Frequency Position Slot width CD
∗
V = |V |sin(2πft) (m/s) (Hz) (m) (m)
..SJ_40_250.sim 40 250
+0.005
(post−corner)
0.002 0.236
– 40 250
−0.005
(pre−corner)
0.002 –
..SJ_40_350.sim 40 350
+0.005
(post−corner)
0.002 0.242
..SJ_40_350_pre.sim 40 350
−0.005
(pre−corner)
0.002 0.332
..SJ_40_450.sim 40 450
+0.005
(post−corner)
0.002 0.250
– 40 450
−0.005
(pre−corner)
0.002 –
..SJ_40_550.sim 40 350
+0.005
(post−corner)
0.002 0.296
– 40 350
−0.005
(pre−corner)
0.002 –
No ground-effect simulations (no_ge)
..baseline_noge.sim 0.312
..SJ_40_250_noge.sim 40 250
+0.005
(post−corner)
0.002 0.269
..SJ_40_350_noge.sim 40 350
+0.005
(post−corner)
0.002 0.270
CD
∗
base = 0.280 (0.3 s)
Max flow rate: ˙m = ρVA = 0.0371 kg/s CD
∗
base = 0.272 (0.4 s)
Jet shape: slot – 0.379 m x 0.002 m CD
∗
no_ge = 0.312 (+11%)
Tabella 1: 3D simulations for synthetic jet active control system
Simulations run until physical time criterion (t = 0.4 s) is satisfated. Simulations
are really computationally expensive and time consuming, thus they are performed
on S.C.o.P.E. facility: using 64 cpus, solver needs about 2 days for each of them.
21. Unsteady blowing Mean velocity Inflow angle Frequency Position Slot width CD
∗
V = |V |sin(2πft) + |Vm| (m/s) ()◦
(Hz) (m) (m)
..UB20_a10_f100.sim 20 10 100
+0.005
(post−corner)
0.002 0.242
– 20 10 100
−0.005
(pre−corner)
0.002 –
..UB20_a10_f200.sim 20 10 200
+0.005
(post−corner)
0.002 0.244
– 20 10 200
−0.005
(pre−corner)
0.002 –
..UB20_a20_f100.sim 20 20 100
+0.005
(post−corner)
0.002 0.246
..UB20_a20_f100_pre.sim 20 20 100
−0.005
(pre−corner)
0.002 0.256
..UB20_a20_f200.sim 20 20 200
+0.005
(post−corner)
0.002 0.244
..UB20_a20_f200_pre.sim 20 20 200
−0.005
(pre−corner)
0.002 0.240
Max flow rate: ˙m = ρVA = 0.0371 kg/s CD
∗
base = 0.280 (0.3 s)
Mean flow rate: ˙m = ρVmA = 0.0186 kg/s CD
∗
base = 0.272 (0.4 s)
Jet shape: slot – 0.379 m x 0.002 m CD
∗
no_ge = 0.312 (+11%)
Tabella 1: 3D simulations for unsteady blowing active control system
Simulations run until physical time criterion (t = 0.4 s) is satisfated. Simulations
are really computationally expensive and time consuming, thus they are performed
on S.C.o.P.E. facility: using 64 cpus, solver needs about 2 days for each of them.
22. No active control system
Unsteady blowing system (f = 200 Hz e
α = 20◦
)
Synthetic jet system (f = 250 Hz e
Vmax = 40 m/s)
23. 2D velocity mapping – Unsteady blowing
Pos. 1 Pos. 2
No active control system
Control system activated
Pos. 3
Unsteady blowing jet operates on tip vortices detaching from the body, destroying
them. Referring to better operating condition, unsteady blowing assures a CD
∗
reduction of about 11%.
24. 2D velocity mapping – Synthetic jet
Pos. 1 Pos. 2
No active control system
Control system activated
Pos. 3
Synthetic jet generates a proper vortical structure, non homogeneous, which
overall produces drag reduction. Referring to better operating condition, synthetic
jet assures a CD
∗
reduction of about 13%.
25. Final remarks
• Ahmed body allows to study complex phenomena connected to typical
automotive flow field
• Star-CCM+ simulations show a good compliance with known cases
• 2D simulations indicate a set of parameters which makes steady blowing jet
functioning optimal; conversely, both unsteady jets don’t work well
• 3D simulations highlight a behaviour change of unsteady jets; synthetic jets
assure better results, producing (∆CD
∗
)max = −13%
26. Final remarks
• Ahmed body allows to study complex phenomena connected to typical
automotive flow field
• Star-CCM+ simulations show a good compliance with known cases
• 2D simulations indicate a set of parameters which makes steady blowing jet
functioning optimal; conversely, both unsteady jets don’t work well
• 3D simulations highlight a behaviour change of unsteady jets; synthetic jets
assure better results, producing (∆CD
∗
)max = −13%
Future works:
• To perform other 3D simulations to support experimental tests, collecting
more situations (e.g.: simulations without tapis roulant)
• To implement a properly designed experimental tests to validate active control
systems