Multi-Disciplinary Optimization of Airship Envelope Shape

Kanikdale, Tushar; Marathe, Anil; Pant, Rajkumar S.

doi:10.2514/6.2004-4411

Cited by 26 publications

(12 citation statements)

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“…Methods to determine the weight of the tether to be carried by the aerostat have also been employed in order to study the effect of drag on the payload capacity of the aerostat. The shape generation algorithm proposed by Kanikdale et al 1 has been made more robust by introducing a new constraint to avoid kinks and folds to develop on the shape. The payload of an aerostat of the GNVR shape has been estimated for a single fabric and multi-fabric construction.…”

Section: Discussionmentioning

confidence: 99%

“…In a previous study by Kanikdale et al 1 , the envelope geometry of an aerostat was parameterized using a sphere for the nose, two cubic splines for the mid-body and a parabola for the rear, as shown in Figure 1.…”

Section: Previous Study In Aerostat Envelope Shape Optimizationmentioning

confidence: 99%

“…Parameterization of geometry 1The defining equations for the various shape segments are given in Eqns (1…”

mentioning

confidence: 99%

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Multi-disciplinary Shape Optimization of Aerostat Envelopes

Ram¹,

Pant²

2007

7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; Followed by 2nd TEOS

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This paper discusses an MDO approach for identifying the optimum shape of an aerostat envelope that results in the largest payload capacity for a given envelope volume. The participating disciplines in this optimization problem are Aerodynamics, Flight Mechanics and Structures. Constraints that take into consideration the difficulty in fabrication of certain kinds of shapes have been included. The paper starts with a description of how the aerostat envelope shape affects its payload carrying ability. Some details of a previous study on parameterization of envelope shape and optimization from aerodynamic and structural considerations alone are presented. A methodology for fin sizing from static stability considerations is presented, which includes determination of tether profile. Results of envelope shape optimization studies reveal that payload capacity can be increased by around 6.5% by using multi-fabric construction, by using lighter fabric in less stressed regions. Sensitivity analyses revealed that the payload capacity decreases considerably with increase in fabric density, and tether weight per unit length due to increased self weight, and angle of attack. It was also seen that the fin weight and the location of confluence point depend to a great extent, on the location of CG.

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Section: Discussionmentioning

confidence: 99%

Section: Previous Study In Aerostat Envelope Shape Optimizationmentioning

confidence: 99%

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Multi-disciplinary Shape Optimization of Aerostat Envelopes

Ram¹,

Pant²

2007

7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; Followed by 2nd TEOS

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“…The problem is thus multidisciplinary in nature involving structures (in terms of fabric stresses), aerodynamics (in terms of drag) and flight dynamics( in terms of trim angle and stability). Figure 1Parameterization of Shape Kanikdale et al [2] proposed a shape generation algorithm for airship bodies where the envelope is modeled as a body of revolution of a compound profile made up of 4 curves.…”

Section: )mentioning

confidence: 99%

Multidisciplinary Shape Optimization of Aerostat Envelopes

Ram

Pant

2010

Journal of Aircraft

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Aerostat is an aerodynamically shaped tethered body, belonging to the family of Lighter Than Air (LTA) vehicles. Aerostat envelopes are filled with a LTA gas (which is Helium or Hydrogen in most cases) and thus generate lift due to buoyancy, which is used to raise a given payload to a certain height. The aerodynamically shaped envelope has least drag when it is aligned with the direction of wind. Hence, adequately sized fins have to be provided on the envelope to impart it stability during wind disturbances. The tether load is distributed across the several points along the length of the envelope through ropes called confluence lines to avoid excessive load on the membrane at a single point. The confluence lines are joined with the tether at the confluence point through a pivot which allows the aerostat to rotate freely and align with the direction of the wind. Payloads in modern day aerostats are usually radars, surveillance cameras or communication equipment. In order to deploy more sophisticated equipment on aerostats, it is always desirable to increase their payload capacity, without compromising on their operating altitude. The envelope shape affects the payload capacity of an aerostat in several ways. This paper discusses an MDO approach for identifying the shape of an aerostat envelope that results in the largest payload capacity for a given envelope volume. Effect of envelope shape on payload capacity The envelope shape affects the payload capacity in the following ways 1)Surface Area: The envelope weight is decided by the Total Surface Area (TSA) of the envelope. W env =TSA* ρ matl where *Sr.

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“…And several approaches were proposed to optimize the envelope of airship. [4][5][6][7][8] However, only the aerodynamic subsystem was considered in these studies. Wang,Q et al developed a methodology for optimization design and analysis of stratosphere airship.…”

Section: Introductionmentioning

confidence: 99%

Conceptual Design Optimization of High Altitude Airship in Concurrent Subspace Optimization

Liang

Zhu

Guo

et al. 2012

50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition

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Science and Technology on Aircraft Control LaboratoryMultidisciplinary design optimization (MDO) is introduced to the conceptual design optimization of high altitude airship (HAA). The framework of concurrent subspace optimization (CSSO), as a MDO methodology, is established for HAA conceptual design. Three subsystems, including aerodynamic and propulsion, structure, and energy subsystem, are discussed in detail. The coupled information in subsystem analysis is supplied by the response surface approximations. And the shape of envelope and the location of solar array are optimized simultaneously with the goal of minimum total mass. In addition, the optimization process and an optimal design that includes shape of envelope, location of solar array and weight components, are obtained. Nomenclature a = major radius of ellipse in Fig. 2 b = minor radius of ellipse in Fig. 2 C DV,hull = volumetric coefficient of the envelope drag which is based on V 2/3 C DV,total = volumetric coefficient of the total drag C F = coefficient of the skin friction D total = total drag of the airship E 0 = eccentricity correction factor of the Earth's orbit E t = different time g = standard specific gravitational force h = design altitude I 0n = intensity of the normal solar radiation without atmosphere attenuation I n = intensity of the normal solar radiation with atmosphere attenuation I SC = normal extraterrestrial solar radiation L = buoyance of the envelope L bg = rotation matrix from the north-east-down frame to the airship body frame L e , L s = local longitude and longitude of the standard meridian for the local time zone l = length of the envelope l I = direction of the rays from the Sun in the north-east-down frame MW gas = molecular weight of the lifting gas MW air = molecular weight of air m array = mass of solar array m c = mass of other components in structure subsystem m energy = mass of energy subsystem m fin = mass of fins 1 2 m gas = mass of the lifting gas m hull = mass of the envelope m payload = mass of payload m store = mass of equipment for storing energy m structure = mass of structure subsystem m thrust = mass of aerodynamic and propulsion subsystem m total = total mass of airship N = ratio C DV,total /C DV,hull n b = normal direction of solar array surface at some point P control = power to control system P payload = power to payload P thrust = power to overcome the drag of airship P total = total power requirement of the airship Q req = energy requirement among one day Q sup = energy supply generated by solar array among one day Re = Reynolds number S array = area of the solar array S fin = fin area S hull = surface area of the envelope T a = aerosol scattering and absorption attenuation factor to the solar radiation T g = permanent gas absorption attenuation factor to the solar radiation T R = Rayleigh scattering attenuation factor to the solar radiation T w = water vapor absorption attenuation factor to the solar radiation t day , t night = day time and night time t LAT , t LST = local apparent time and loca...

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Multi-Disciplinary Optimization of Airship Envelope Shape

Cited by 26 publications

References 0 publications

Multi-disciplinary Shape Optimization of Aerostat Envelopes

Multi-disciplinary Shape Optimization of Aerostat Envelopes

Multidisciplinary Shape Optimization of Aerostat Envelopes

Conceptual Design Optimization of High Altitude Airship in Concurrent Subspace Optimization

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