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Indian Space Capabilities

Consider the case of developing L, X , S band MMICs in country BUT industrial scale manufacturing is indeed missing.

So we very much can and have done quite a lot of work in that field. The S-band LSTAR AEW&C radar is a product of that research.

The IIT professor isn't exactly incorrect since semi-conductor research is limited to specialized institutions like GAETEC and not existent in the higher education institutes like IIT (most engineering institutes of a high caliber will have on-going student and researcher led projects in the field or professors who are running projects under government or private grants- industry oriented research is very low due to policies and structural issues).



What will be the private fabs like when they are setup say 2-4 years down the line- will they be capable of catering to the demands of mil-grade MMICs for our sensors?

Oh yeah. I am not aware of any industrial scale production of MMICs in India. I believe the professor (a Dr Ranade or Rawade) was talking about defense research. He was a consultant for DRDO in a lab with a confoundingly long acronym.

Industry/private sector research expenditure is fairly low in India across the board anyway, so it comes as no surprise that they are taking a back foot here.

Regarding the bolded part: UWA (my university) is ranked 84th in the world and as far as I'm aware has no ongoing research in the field. That being said most semi-conductor research in the West (as with the rest of the world) is done by industry.
 
Are the flush air sensors operational or still in the design phase?

Hypersonic wind tunnel set up ho gaya?

FADS employing neural network are ready for HEX01.

NEURAL NETWORK BASED FLUSH AIR DATA SYSTEM (FADS) FOR REUSABLE LAUNCH VEHICLES
Abstract
Flush air data systems (FADS) are gaining importance for use in measurement of air data parameters like angle of attack, sideslip angle, Mach number and dynamic pressure for reentry and reusable vehicles, advanced aircrafts, interplanetary space probes etc. These air data parameters are critical for successful mission management of the vehicle during the flight phases dominated by complex aero thermal effects.

Flush Air Data System makes use of a matrix of flush pressure orifices located on the nose region (or stagnation region) of the vehicle to estimate air data parameters. The surface pressures are sensed using highly accurate absolute pressure transducers. The multivariable relationship between the pressure measurement and the output air data parameters is complex and highly nonlinear. Different methods are proposed in literature for the estimation of air data parameters using surface pressure measurements. Some of the earlier semi-empirical model based approaches used to process FADS pressure data have experienced numerical instabilities resulting in momentary degradation in system performance.

In this paper a neural network based FADS algorithm is developed for a reusable launch vehicle technology demonstrator. FADS is proposed to be used for the flight regime from Mach number 2.5 to 0. Neural networks, which require large quantities of training aerodynamic data set offer a simple, flexible and accurate solution for such complex applications. Neural network systems allow for the correlation of complex nonlinear systems without requiring explicit knowledge of the functional relationship that exists between the input and output variables of the system. Further, algorithms with neural network techniques are inherently stable for the calibration of nonlinear data involving more number of independent parameters.

The pressure port configuration used in this paper consists of nine pressure ports located on the nosecone of the vehicle. The pressure ports are arranged in a crucifix fashion with five ports located in the vertical meridian and four in the horizontal meridian. The pressure ports are connected to the pressure transducer using pneumatic tubing designed to satisfy frequency and thermal response requirements. The developed algorithm is validated using calibration data generated from wind tunnel tests. Back propagation technique is used to train the neural network to achieve the desired level of accuracy. The present study shows that with properly trained networks, the neural network can be used effectively for real-time prediction of air data states during the critical flight phases.

Kab ka hogaya bhai :yay:

It is flush air data system.
Air data system collects air-velocity,type of air flow,pressure that arises in front of the nose via pilot-tube in front of the fighter,then this data goes into FBW control system but long pilot tube tube increases the drag in hypersonic vehicles while it increases the RCS of supersonic fighter.
In FADS,tiny sensors are embedded all around the Nosecone so that the problem of drag and RCS is solved.

And Pitot tubes wont survive the heat during hypersonic flights.
 
FADS employing neural network are ready for HEX01.

NEURAL NETWORK BASED FLUSH AIR DATA SYSTEM (FADS) FOR REUSABLE LAUNCH VEHICLES
Abstract
Flush air data systems (FADS) are gaining importance for use in measurement of air data parameters like angle of attack, sideslip angle, Mach number and dynamic pressure for reentry and reusable vehicles, advanced aircrafts, interplanetary space probes etc. These air data parameters are critical for successful mission management of the vehicle during the flight phases dominated by complex aero thermal effects.

Flush Air Data System makes use of a matrix of flush pressure orifices located on the nose region (or stagnation region) of the vehicle to estimate air data parameters. The surface pressures are sensed using highly accurate absolute pressure transducers. The multivariable relationship between the pressure measurement and the output air data parameters is complex and highly nonlinear. Different methods are proposed in literature for the estimation of air data parameters using surface pressure measurements. Some of the earlier semi-empirical model based approaches used to process FADS pressure data have experienced numerical instabilities resulting in momentary degradation in system performance.

In this paper a neural network based FADS algorithm is developed for a reusable launch vehicle technology demonstrator. FADS is proposed to be used for the flight regime from Mach number 2.5 to 0. Neural networks, which require large quantities of training aerodynamic data set offer a simple, flexible and accurate solution for such complex applications. Neural network systems allow for the correlation of complex nonlinear systems without requiring explicit knowledge of the functional relationship that exists between the input and output variables of the system. Further, algorithms with neural network techniques are inherently stable for the calibration of nonlinear data involving more number of independent parameters.

The pressure port configuration used in this paper consists of nine pressure ports located on the nosecone of the vehicle. The pressure ports are arranged in a crucifix fashion with five ports located in the vertical meridian and four in the horizontal meridian. The pressure ports are connected to the pressure transducer using pneumatic tubing designed to satisfy frequency and thermal response requirements. The developed algorithm is validated using calibration data generated from wind tunnel tests. Back propagation technique is used to train the neural network to achieve the desired level of accuracy. The present study shows that with properly trained networks, the neural network can be used effectively for real-time prediction of air data states during the critical flight phases.

Kab ka hogaya bhai :yay:



And Pitot tubes wont survive the heat during hypersonic flights.

So what are the technological barriers that ISRO has breached?

FADS is here- has a working model been tested? On what platform would it be tested?

But seriously this is a large volume of work being undertaken.

Has ISRO been able to work out proficiency with Al-li alloys? A lot of these alloys aren't just difficult to produce but also difficult to work with. What sort of teach sharing exists in between ISRO and the DPSUs IF any given that that might raise eyebrows?

Any plans for extending the IRNSS coverage in the neighborhood?
 
bhai what about the company who has to set up here??

it was intel and one more...............unse bhi to koi pooch le:taz:

Yaar , I don't know the adcd of semi-conductors and this field .

I just posted it because those guys were discussing about it few pages back .
 
Yaar , I don't know the adcd of semi-conductors and this field .

I just posted it because those guys were discussing about it few pages back .

main to maze le raha tha yaar

actually our govt floated this idea even in 2007 but intel rejected it as
1)we could not gurantee continous power
2)unavailability of pure water on large scale

thats why i am keeping fingers crossed this time
 
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Life on Mars? We will seek to reveal: ISRO


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BANGALORE (PTI): India's upcoming Mars Orbiter Mission (MOM) seeks to reveal whether there is methane, considered a "precursor chemical" for life, on the Red Planet, key officials behind the ambitious venture said.

A Methane Sensor, one of the five payloads (scientific instruments) onboard the spacecraft, would look to detect the presence of the gas, MOM Project Director Arunan S said.

He said the sensor was aimed at understanding whether life existed on Mars or if it would have life in future.

"Methane is fundamentally base for life on any planet," he said.

M Annadurai, Programme Director, IRS & SSS (Indian Remote Sensing & Small, Science and Student Satellites), said: "Most probably we will be able to answer whether there is presence of Methane. If it's there, yes; if it's not, not there. If it's available, where it's available".

After a media preview of the Mars orbiter at ISRO Satellite Centre here, where it is being given final shape, officials of the space agency indicated that the aim is to launch the mission on October 21, weather permitting.

The launch window is from October 21 to November 19.

MOM is a Rs 450 crore mission -- Rs 110 crore for building PSLV-C25 that would launch the Rs 150 crore spacecraft, with the remaining amount spent on augmenting ground segment, including those required for deep space communication.

Once launched from the spaceport of Sriharikota, the spacecraft would go around the earth for 20-25 days before embarking on a 9-month voyage to Mars. The minimum life of the spacecraft around Mars is six months but it would certainly outlive it, as similar satellites orbited by other countries have sometimes lasted six-seven years, Arunan said.

Life on Mars? We will seek to reveal: ISRO - Brahmand.com
 
Isro to make new stage for GSLV

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The high-level task team constituted to probe the August 19 failure of the Geosynchronous Satellite Launch Vehicle-D5 (GSLV-D5) is yet to submit the final report on the reasons for the glitch, but the Indian Space Research Organisation (Isro) has decided to assemble a new second stage for the rocket.

A senior Isro official, while stating that the exact date for the launch of GSLV-D5 can only be set in November, added that the launcher would be launched into space in December, carrying the GSAT-14.

“Going by the availability of hardware and components, the GSLV assembly and checkout is expected to be completed at the vehicle assembly building by the first week of December,” said a note issued by Isro.



“Although the exact reasons for the leakage in the second stage of the engine, which prevented the launch on August 19, are being probed by the team headed by K Narayanan, it has been decided that a new liquid second stage (GS-2) will be assembled to replace the leaked stage,” said the official.

He added that the process of assembling has begun, and that besides the GS-2, all the four liquid strap-on stages are being replaced with new ones.

Another official, while stating that the team is also inspecting the first stage (solid) and core base shroud, added that if any of the elements are found to be affected, “we will replace even those”.

“The satellite assembly, avionics equipment bay and the cryogenic stage will be preserved, following prescribed practices,” said an official note issued by Isro.
Isro to make new stage for GSLV | idrw.org
 
So what are the technological barriers that ISRO has breached?

FADS is here- has a working model been tested? On what platform would it be tested?

But seriously this is a large volume of work being undertaken.

Has ISRO been able to work out proficiency with Al-li alloys? A lot of these alloys aren't just difficult to produce but also difficult to work with. What sort of teach sharing exists in between ISRO and the DPSUs IF any given that that might raise eyebrows?

Any plans for extending the IRNSS coverage in the neighborhood?

Working model tested only tested in a wind tunnel and within one year it will be tested in flight. FADS allows the extreme hypersonic heating caused by the small radius of a flow-sensing probe (like pitot tube or a deployable probe) to be avoided that allows extending the useful range of the airdata measurement system to the hypersonic flow regime.
 
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