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Secondary impact hazard assessment

A series of light gas gun shots (4 to 7 km/sec) were performed with 5 mg nylon and aluminum projectiles to determine the size, mass, velocity, and spatial distribution of spall and ejecta from a number of graphite/epoxy targets. Similar determinations were also performed on a few aluminum targets. Target thickness and material were chosen to be representative of proposed Space Station structure. The data from these shots and other information were used to predict the hazard to Space Station elements from secondary particles resulting from impacts of micrometeoroids and orbital debris on the Space Station. This hazard was quantified as an additional flux over and above the primary micrometeoroid and orbital debris flux that must be considered in the design process. In order to simplify the calculations, eject and spall mass were assumed to scale directly with the energy of the projectile. Other scaling systems may be closer to reality. The secondary particles considered are only those particles that may impact other structure immediately after the primary impact. The addition to the orbital debris problem from these primary impacts was not addressed. Data from this study should be fed into the orbital debris model to see if Space Station secondaries make a significant contribution to orbital debris. The hazard to a Space Station element from secondary particles above and beyond the micrometeoroid and orbital debris hazard is categorized in terms of two factors: (1) the 'view factor' of the element to other Space Station structure or the geometry of placement of the element, and (2) the sensitivity to damage, stated in terms of energy. Several example cases were chosen, the Space Station module windows, windows of a Shuttle docked to the Space Station, the habitat module walls, and the photovoltaic solar cell arrays. For the examples chosen the secondary flux contributed no more than 10 percent to the total flux (primary and secondary) above a given calculated critical energy. A key assumption in these calculations is that above a certain critical energy, significant damage will be done. This is not true for all structures. Double-walled, bumpered structures are an example for which damage may be reduced as energy goes up. The critical energy assumption is probably conservative, however, in terms of secondary damage. To understand why the secondary impacts seem to, in general, contribute less than 10 percent of the flux above a given critical energy, consider the case of a meteoroid impact of a given energy on a fixed, large surface. This impact results in a variety of secondary particles, all of which have much less energy than the original impact. Conservation of energy prohibits any other situation. Thus if damage is linked to a critical energy of a particle, the primary flux will always deliver particles of much greater energy. Even if all the secondary particles impacted other Space Station structures, none would have a kinetic energy more than a fraction of the primary impact energy.

Source record↗

Origin of the Outer Solar System

Our ongoing research program combines extensive deep and wide-field observations using a variety of observational platforms with numerical studies of the dynamics of small bodies in the outer solar system in order to advance the main scientific goals of the community studying the Kuiper belt and the outer solar system. These include: (1) determining the relative populations of the known classes of KBOs as well as other possible classes; (2) determining the size distributions or luminosity function of the individual populations or the Kuiper belt as a whole; (3) determining the inclinations distributions of these populations; (4) establishing the radial extent of the Kuiper belt; (5) measuring and relating the physical properties of different types of KBOs to those of other solar system bodies; and, (6) completing our systematic inventory of the satellites of the outer planets.

Holman, Matthew J.↗

Origin of Outer Solar System

Our ongoing research program combines extensive deep and wide-field observations using a variety of observational platforms with numerical studies of the dynamics of small bodies in the outer solar system in order to advance the main scientific goals of the community studying the Kuiper belt and the outer solar system. These include: (1) determining the relative populations of the known classes of KBOs as well as other possible classes; ( 2 ) determining the size distributions or luminosity function of the individual populations or the Kuiper belt as a whole; (3) determining the inclinations distributions of these populations; (4) establishing the radial extent of the Kuiper belt; ( 5 ) measuring and relating the physical properties of different types of KBOs to those of other solar system bodies; and, (6) completing our systematic inventory of the satellites of the outer planets.

Holman, Matthew J.↗

An Investigation into the Grain Structure of Impact Ice

To design effective anti-icing and de-icing technology for aircraft, scientists and engineers must obtain a fundamental understanding of the microstructural characteristics of impact ice. This study investigates the effects of icing parameters, such as airspeed and liquid water content (LWC), on impact ice microstructure near the interface to a metal substrate. Ice samples were accreted in the NASA Glenn Icing Research Tunnel and tested in the NASA Revolutionary Icing Materials Evaluation Laboratory. A microtome was used to shave down the ice to a thickness of < 1 mm for examination under a microscope. Samples were imaged at multiple magnifications using bright field imaging. The average grain size was determined for each sample in accordance with ASTM standard methods, and relationships between airspeed, LWC, and grain size were identified. It was observed that the average grain area in a given cross-section was linearly related to the distance of the cross-section from the metal surface. Finally, the effects of annealing and sublimation on the microstructure were also explored. Results show significant variation in the grain structure, suggesting a means by which icing condition influences adhesion strength.

grain↗

NDARC NASA Design and Analysis of Rotorcraft - Input, Appendix 4

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description consists of all the information, input and derived, that denes the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions. The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for anti-torque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude.

Rotorcraft Input↗

NDARC - NASA Design and Analysis of Rotorcraft: Input and Data Structures - Vol 2

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NDARC - NASA Design and Analysis of Rotorcraft: Input - Vol 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NDARC - NASA Design and Analysis of Rotorcraft: Input - Appendix 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

Improved silicon nitride for advanced heat engines

The AiResearch Casting Company baseline silicon nitride (92 percent GTE SN-502 Si sub 3 N sub 4 plus 6 percent Y sub 2 O sub 3 plus 2 percent Al sub 2 O sub 3) was characterized with methods that included chemical analysis, oxygen content determination, electrophoresis, particle size distribution analysis, surface area determination, and analysis of the degree of agglomeration and maximum particle size of elutriated powder. Test bars were injection molded and processed through sintering at 0.68 MPa (100 psi) of nitrogen. The as-sintered test bars were evaluated by X-ray phase analysis, room and elevated temperature modulus of rupture strength, Weibull modulus, stress rupture, strength after oxidation, fracture origins, microstructure, and density from quantities of samples sufficiently large to generate statistically valid results. A series of small test matrices were conducted to study the effects and interactions of processing parameters which included raw materials, binder systems, binder removal cycles, injection molding temperatures, particle size distribution, sintering additives, and sintering cycle parameters.

Yeh, H. C.↗

Design and optimization of a self-deploying single axis tracking PV array

This study was performed in order to design a tracking photovoltaic (PV) array and optimize the design for maximum specific power. The design considerations were minimal deployment time, high reliability, and small stowage volume. The array design was self-deployable, from a compact stowage configuration, using a passive pressurized gas deployment mechanism. The array structural components consist of a combination of beams, columns, and cables used to deploy and orient a flexible PV blanket. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces to which it would be subjected. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power. The optimization was performed for both lunar and Martian environments with 4 types of PV blankets (silicon, GaAs/Ge, GaAs CLEFT, and amorphous silicon). For the lunar environment, the amorphous silicon array produced the highest specific power, whereas, for Mars the GaAs CLEFT array produced the highest specific power. A comparison was made to a fixed PV tent array of similar design. The tracking array produced a higher specific power with all types of the PV blankets examined except amorphous silicon at both locations.

Colozza, Anthony J.↗

Design and optimization of a self-deploying single axis tracking PV array

This study was performed in order to design a tracking photovoltaic (PV) array and optimize the design for maximum specific power. The design considerations were minimal deployment time, high reliability, and small stowage volume. The array design was self-deployable, from a compact stowage configuration, using a passive pressurized gas deployment mechanism. The array structural components consist of a combination of beams, columns, and cables used to deploy and orient a flexible PV blanket. Each structural component of the design was analyzer to determine the size necessary to withstand the various forces to which it would be subjected. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power. The optimization was performed for both lunar and Martian environments with 4 types of PV blankets (silicon, GaAs/Ge, GaAs CLEFT, and amorphous Silicon). For the lunar environment, the amorphous silicon array produced the highest specific power, whereas, for Mars the GaAs CLEFT array produced the highest specific power. A comparison was made to a fixed PV tent array of similar design. The tracking array produced a higher specific power with all types of the PV blankets examined except amorphous silicon at both locations.

Colozza, Anthony J.↗

Comparing the Earth Impact Flux from Comets and Near-Earth Asteroids

Long-period comets (LPC), defined here as those active comets with orbital periods greater than 200 years, are the most difficult objects to mitigate should one be found on an Earth threatening trajectory. The arrival of these objects from the distant Oort cloud cannot be predicted and the impact warning time would be measured in a few months - not years. At the distance of Jupiter, an inactive cometary nucleus with a diameter of one kilometer and a geometric albedo equal to 0.04 would have an apparent magnitude fainter than 25 near opposition and, hence would be well outside the detection capability of current NEO search telescopes. In general LPCs do not become active, and hence discoverable, until inside the orbit of Jupiter and it takes but nine months for a LPC to travel the distance from Jupiter's orbit to that of the Earth.Estimating the impact energy for long-period comets is particularly difficult because the sizes and masses of these objects are not well known. Their solid nuclei are hidden from ground-based telescopes by their gas and dust atmospheres and even when nearby spacecraft observations can determine a size and shape for a cometary nucleus, there are no direct determinations of any cometary mass or bulk density to date. However, a variety of indirect bulk density determinations consistently provide values below one gram per cubic centimeter, the value for water. From measurements made by the Deep Impact spacecraft during its encounter with comet Tempel 1 in July 2005, the bulk density was estimated to be 0.6 grams per cubic centimeter. The mean impact velocity of a LPC is about 51 km/s, three times the 17 km/s value for a typical near-Earth asteroid (NEA) so the impact energy for an LPC would be 9 times that of a NEA of similar mass. However, the bulk density of a comet (approx. 0.6 g/cu cm) is several times less than the density of a stony NEA (approx. 2.6 g/ cu cm) so for a LPC and a stony NEA of the same size, the LPC's impact energy would be about twice that of the NEA.To properly allocate the limited resources available for NEO surveys and physical characterization, it is important to understand the relative threat from long-period comets versus the threat posed by near-Earth asteroids.

near Earth objects↗

Inverse design of a proper number, shapes, sizes, and locations of coolant flow passages

During the past several years we have developed an inverse method that allows a thermal cooling system designer to determine proper sizes, shapes, and locations of coolant passages (holes) in, say, an internally cooled turbine blade, a scram jet strut, a rocket chamber wall, etc. Using this method the designer can enforce a desired heat flux distribution on the hot outer surface of the object, while simultaneously enforcing desired temperature distributions on the same hot outer surface as well as on the cooled interior surfaces of each of the coolant passages. This constitutes an over-specified problem which is solved by allowing the number, sizes, locations and shapes of the holes to adjust iteratively until the final internally cooled configuration satisfies the over-specified surface thermal conditions and the governing equation for the steady temperature field. The problem is solved by minimizing an error function expressing the difference between the specified and the computed hot surface heat fluxes. The temperature field analysis was performed using our highly accurate boundary integral element code with linearly varying temperature along straight surface panels. Examples of the inverse design applied to internally cooled turbine blades and scram jet struts (coated and non-coated) having circular and non-circular coolant flow passages will be shown.

George S. Dulikravich↗

Simple algorithms for remote determination of mineral abundances and particle sizes from reflectance spectra

Algorithms were developed, based on Hapke's (1981) equations, for remote determinations of mineral abundances and particle sizes from reflectance spectra. In this method, spectra are modeled as a function of end-member abundances and illumination/viewing geometry. The method was tested on a laboratory data set. It is emphasized that, although there exist more sophisticated models, the present algorithms are particularly suited for remotely sensed data, where little opportunity exists to independently measure reflectance versus article size and phase function.

Johnson, Paul E.↗

Design and optimization of a self-deploying PV tent array

A study was performed to design a self-deploying tent shaped PV (photovoltaic) array and optimize the design for maximum specific power. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces it would be subjected to. Through this analysis the component weights were determined. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power for a given PV blanket. This optimization was performed for both Lunar and Martian environmental conditions. The performance specifications for the array at both locations and with various PV blankets were determined.

Colozza, Anthony J.↗

A Scoping Study to Determine the Location-Specific WEC Threshold Size for Wave-Powered AUV Recharging

The aim of this study is to determine the threshold wave energy converter (WEC) type and size to charge a fleet of U.S. Navy autonomous underwater vehicles (AUVs) in various geographic locations of interest. The U.S. Navy deploys AUVs in locations around the world that must be charged manually, decreasing their operational endurance and creating operational limitations. Ocean waves are a potential power source that can be converted into electricity using a WEC and stored using a battery. It would be beneficial to develop a WEC that could autonomously charge AUVs offshore. Numerous locations were analyzed to determine the minimum size of a WEC capable of providing sufficient charging power and offering a strategic advantage. By predicting the WEC efficiency (based on empirical equations) and wave resource (based on available data), electrical power generation across numerous WEC types and locations was compared in MATLAB. The generalized process developed here could be used to determine the required size and type of WECs to charge a fleet of AUVs in different locations around the world.

16 TIDAL AND WAVE POWER↗

Numerical analysis of coalescence-induced bubble departure for enhanced boiling heat transfer

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

42 ENGINEERING↗

Design, optimization, and analysis of a self-deploying PV tent array

A tent shaped PV array was designed and the design was optimized for maximum specific power. In order to minimize output power variation a tent angle of 60 deg was chosen. Based on the chosen tent angle an array structure was designed. The design considerations were minimal deployment time, high reliability, and small stowage volume. To meet these considerations the array was chosen to be self-deployable, form a compact storage configuration, using a passive pressurized gas deployment mechanism. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces to which it would be subjected. Through this analysis the component weights were determined. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power for a given PV blanket. This optimization was performed for both lunar and Martian environmental conditions. Other factors such as PV blanket types, structural material, and wind velocity (for Mars array), were varied to determine what influence they had on the design point. The performance specifications for the array at both locations and with each type of PV blanket were determined. These specifications were calculated using the Arimid fiber composite as the structural material. The four PV blanket types considered were silicon, GaAs/Ge, GaAsCLEFT, and amorphous silicon. The specifications used for each blanket represented either present day or near term technology. For both the Moon and Mars the amorphous silicon arrays produced the highest specific power.

Collozza, Anthony J.↗