Some design considerations for spin-stabilized satellites with rigid expandable structures
Design considerations for spin stabilized satellites with rigid expandable structures
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Design considerations for spin stabilized satellites with rigid expandable structures
Design, analysis, and sizing methods for two novel structural panel concepts have been developed and incorporated into the HyperSizer Structural Sizing Software. Reinforced Core Sandwich (RCS) panels consist of a foam core with reinforcing composite webs connecting composite facesheets. Boeing s Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) panels use a pultruded unidirectional composite rod to provide axial stiffness along with integrated transverse frames and stitching. Both of these structural concepts are ovencured and have shown great promise applications in lightweight structures, but have suffered from the lack of efficient sizing capabilities similar to those that exist for honeycomb sandwich, foam sandwich, hat stiffened, and other, more traditional concepts. Now, with accurate design methods for RCS and PRSEUS panels available in HyperSizer, these concepts can be traded and used in designs as is done with the more traditional structural concepts. The methods developed to enable sizing of RCS and PRSEUS are outlined, as are results showing the validity and utility of the methods. Applications include several large NASA heavy lift launch vehicle structures.
The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains a challenge. Here we describe a general solution to this problem that starts with a broad exploration of the vast space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate the broad applicability of this approach through the de novo design of binding proteins to 12 diverse protein targets with different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and, following experimental optimization, bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder–target complexes, and all five closely match the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein–protein interactions, and should guide improvements of both. Our approach enables the targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.
A homotopy approach involving multiobjective functions is developed to outline the methods that have evolved for the combined control-structure optimization of physical systems encountered in the technology of large space structures. A method to effect a timely consideration of the control performance prior to the finalization of the structural design involves integrating the control and structural design processes into a unified design methodology that combines the two optimization problems into a single formulation. This study uses the combined optimization problem as a family of weighted structural and control costs. Connections with vector optimizations are described; an analysis of the zero-set of required conditions is made, and a numerical example is given.
The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.
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Structures under stress are designed much more rapidly -- allowing for remarkable increases in productivity -- since NASTRAN (for NASA Structural Analysis) has become available. The versatile computer program, written originally to help design more efficient space vehicles, finds additional applications each year.
Structural design and component test data for disk gap-band planetary entry parachute
Structural failure is rarely a "sudden death" type of event, such sudden failures may occur only under abnormal loadings like bomb or gas explosions and very strong earthquakes. In most cases, structures fail due to damage accumulated under normal loadings such as wind loads, dead and live loads. The consequence of cumulative damage will affect the reliability of surviving components and finally causes collapse of the system. The cumulative damage effects on system reliability under time-invariant loadings are of practical interest in structural design and therefore will be investigated in this study. The scope of this study is, however, restricted to the consideration of damage accumulation as the increase in the number of failed components due to the violation of their strength limits.
Subspace and Lanczos iterations have been developed, well documented, and widely accepted as efficient methods for obtaining p-lowest eigen-pair solutions of large-scale, practical engineering problems. The focus of this paper is to incorporate recent developments in vectorized sparse technologies in conjunction with Subspace and Lanczos iterative algorithms for computational enhancements. Numerical performance, in terms of accuracy and efficiency of the proposed sparse strategies for Subspace and Lanczos algorithm, is demonstrated by solving for the lowest frequencies and mode shapes of structural problems on the IBM-R6000/590 and SunSparc 20 workstations.
Shape memory alloys (SMA) have a unique ability to recover small amounts of plastic strain through a temperature induced phase change. For these materials, mechanical displacement can be accomplished by heating the structure to induce a phase change, through which some of the plastic strain previously introduced to the structure can be reversed. This paper introduces a concept whereby an SMA phase is incorporated into a conventional alloy matrix in a co-continuous reticulated arrangement forming a bi-metallic composite structure. Through memory activation of the mechanically constrained SMA phase, a controlled residual stress field is developed in the interior of the structure. The presented experimental data show that the memory activation of the SMA composite component significantly changes the residual stress distribution in the overall structure. Designing the structural arrangement of the two phases to produce a controlled residual stress field could be used to create structures that have much improved durability and damage tolerance properties.
Abstract A new three-dimensional electromagnetic modeling tool ( ThinCurr ) has been developed using the existing PSI-Tet finite-element code in support of conducting structure design work for both the SPARC and DIII-D tokamaks. Within this framework a 3D conducting structure model was created for both the SPARC and DIII-D tokamaks in the thin-wall limit. This model includes accurate details of the vacuum vessel and other conducting structural elements with realistic material resistivities. This model was leveraged to support the design of a passive runaway electron mitigation coil (REMC), studying the effect of various design parameters, including coil resistivity, current quench duration, and plasma vertical position, on the effectiveness of the coil. The REMC is a non-axisymmetric coil designed to passively drive large non-axisymmetric fields during the plasma disruption thereby destroying flux surfaces and deconfining RE seed populations. These studies indicate that current designs should apply substantial 3D fields at the plasma surface during future plasma current disruptions as well as highlight the importance of having the REMC conductors away from the machine midplane in order to ensure they are robust to off-normal disruption scenarios.
In this talk we shall discuss algorithms and CAD tools for the design and analysis of structures for high performance applications using advanced composite materials. An extensive mathematical theory for optimal structural (e.g., shape) design was developed over the past thirty years. Aspects of this theory have been used in the design of components for hypersonic vehicles and thermal diffusion systems based on homogeneous materials. Enhancement of the design methods to include optimization of the microstructure of the component is a significant innovation which can lead to major enhancements in component performance. Our work is focused on the adaptation of existing theories of optimal structural design (e.g., optimal shape design) to treat the design of structures using advanced composite materials (e.g., fiber reinforced, resin matrix materials). In this talk we shall discuss models and algorithms for the design of simple structures from composite materials, focussing on a problem in thermal management. We shall also discuss methods for the integration of active structural controls into the design process.
A unique methodology providing global optimization of spacecraft protective structures is presented. The Geometric Programming optimization technique, which has a long history of application to structural design problems, is employed to minimize spacecraft weight of protective structural systems exposed to meteoroid and space debris hypervelocity impacts. The space debris and meteoroid environment are defined followed by the formulation of the general weight objective function. The Wilkinson, Burch, and Nysmith hypervelocity impact predictor models are then used in example cases to display Geometric Programming capabilities. Results show that global nonlinear design optimization can be performed for hypervelocity impact models that follow the Geometric Programming form.
The provisions of this project call for the design of the structure of the wing and carry-through structure for the Viper primary trainer, which is to be certified as a utility category trainer under FAR part 23. The specific items to be designed in this statement of work were Front Spar, Rear Spar, Aileron Structure, Wing Skin, and Fuselage Carry-through Structure. In the design of these parts, provisions for the fuel system, electrical system, and control routing were required. Also, the total weight of the entire wing planform could not exceed 216 lbs. Since this aircraft is to be used as a primary trainer, and the SOW requires a useful life of 107 cycles, it was decided that all of the principle stresses in the structural members would be kept below 10 ksi. The only drawback to this approach is a weight penalty.
The design criteria and test options for aerospace structural reliability were investigated. A decision methodology was developed for selecting a combination of structural tests and structural design factors. The decision method involves the use of Bayesian statistics and statistical decision theory. Procedures are discussed for obtaining and updating data-based probabilistic strength distributions for aerospace structures when test information is available and for obtaining subjective distributions when data are not available. The techniques used in developing the distributions are explained.
The application of the elastic-viscoelastic correspondence principle is presented as a design tool for structural design engineers for composite material applications. The classical problem of cantilever beams is used as the illustration problem. Both closed-form and approximate numerical solutions are presented for several different problems. The application of the collocation method is presented as a viable and simple design tool to determine the time-dependent behavior and response of viscoelastic composite beams under load.
The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated by using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network with the code NETS. Optimum designs for new design conditions were predicted by using the trained network. Neural net prediction of optimum designs was found to be satisfactory for most of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.