Optimization of space antenna structures
Spacecraft antenna concepts, structural types, and materials
Heer, E.↗
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Optimal estimation of large structure model errors
In-flight estimation of large structure model errors is usually required as a means of detecting inevitable deficiencies in large structure controller/estimator models. The present paper deals with a least-squares formulation which seeks to minimize a quadratic functional of the model errors. The properties of these error estimates are analyzed. It is shown that an arbitrary model error can be decomposed as the sum of two components that are orthogonal in a suitably defined function space. Relations between true and estimated errors are defined. The estimates are found to be approximations that retain many of the significant dynamics of the true model errors. Current efforts are directed toward application of the analytical results to a reference large structure model.
Rodriguez, G.↗
Shape optimization of 3D continuum structures via force approximation techniques
The existing need to develop methods whereby the shape design efficiency can be improved through the use of high quality approximation methods is addressed. An efficient approximation method for stress constraints in 3D shape design problems is proposed based on expanding the nodal forces in Taylor series with respect to shape variations. The significance of this new method is shown through elementary beam theory calculations and via numerical computations using 3D solid finite elements. Numerical examples including the classical cantilever beam structure and realistic automotive parts like the engine connecting rod are designed for optimum shape using the proposed method. The numerical results obtained from these methods are compared with other published results, to assess the efficiency and the convergence rate of the proposed method.
Vanderplaats, Garret N.↗
Optimization of helicopter airframe structures for vibration reduction - Considerations, formulations, and applications
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Sreekanta Murthy, T.↗
Applications of multiple-constraint matrix updates to the optimal control of large structures
Low-authority control or vibration suppression in large, flexible space structures can be formulated as a linear feedback control problem requiring computation of displacement and velocity feedback gain matrices. To ensure stability in the uncontrolled modes, these gain matrices must be symmetric and positive definite. In this paper, efficient computation of symmetric, positive-definite feedback gain matrices is accomplished through the use of multiple-constraint matrix update techniques originally developed for structural identification applications. Two systems were used to illustrate the application: a simple spring-mass system and a planar truss. From these demonstrations, use of this multiple-constraint technique is seen to provide a straightforward approach for computing the low-authority gains.
Smith, S. W.↗
Optimization of a Hot Structure Aeroshell and Nose Cap for Mars Atmospheric Entry
The National Aeronautics and Space Administration (NASA) is preparing to send humans beyond Low Earth Orbit and eventually to the surface of Mars. As part of the Evolvable Mars Campaign, different vehicle configurations are being designed and considered for delivering large payloads to the surface of Mars. Weight and packing volume are driving factors in the vehicle design, and the thermal protection system (TPS) for planetary entry is a technology area which can offer potential weight and volume savings. The feasibility and potential benefits of a ceramic matrix composite hot structure concept for different vehicle configurations are explored in this paper, including the nose cap for a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) and an aeroshell for a mid lift-to-drag (Mid L/D) concept. The TPS of a planetary entry vehicle is a critical component required to survive the severe aerodynamic heating environment during atmospheric en- try. The current state-of-the-art is an ablative material to protect the vehicle from the heat load. The ablator is bonded to an underlying structure, which carries the mechanical loads associated with entry. The alternative hot structure design utilizes an advanced carbon-carbon material system on the outer surface of the vehicle, which is exposed to the severe heating and acts as a load carrying structure. The preliminary design using the hot structure concept and the ablative concept is determined for the spherical nose cap of the HIAD entry vehicle and the aeroshell of the Mid L/D entry vehicle. The results of the study indicate that the use of hot structures for both vehicle concepts leads to a feasible design with potential weight and volume savings benefits over current state-of-the-art TPS technology that could enable future missions.
Langston, Sarah L.↗
Design of Wind Tunnel Balance Structure Using Robust Topology Optimization Under Multiple Stress Constraints
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Topology optimization↗
MetaHeuristic Feature Selection for Energy Group Optimization and Analysis
Energy discretization is a crucial component of deterministic neutron transport simulations. Metaheuristic (MH) optimizers are effective algorithms to determine group structures that maximize both solution accuracy and computational efficiency. This project establishes a framework for optimizing group structures for PARTISN simulations using the Python library MEALPY. Group structure optimization is formulated as a binary feature selection problem, and results are investigated with permutation and material importance techniques to determine physically relevant energy bounds. We conclude that MH optimizers find group structures that drastically improve flux calculations while preserving k-effective accuracy. Further, we find that individual energy bounds are not necessarily physically relevant, but rather specific energy ranges are.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Optimization of rotor blades for combined structural, performance, and aeroelastic characteristics
The strategies whereby helicopter rotor blades can be optimized for combined structural, inertial, dynamic, aeroelastic, and aerodynamic performance characteristics are outlined. There are three key ingredients in the successful execution of such an interdisciplinary optimization. The first is the definition of a satisfactory performance index that combines all aspects of the problem without too many constraints. The second element is the judicious choice of computationally efficient analysis tools for the various quantitative components in both the cost functional and constraints. The third element is an effective strategy for combining the various disciplines either in parallel or sequential optimizations.
Peters, David A.↗
Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification
Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.
Yang Zhang↗
Electrochemical characterization of InP structures
Electrochemical (EC) techniques represent a simple and yet accurate method to characterize InP and related materials structures. With EC techniques, uncertainties in the measurements arising from factors such as surface effects, the composition and thickness of a front dead layer, the contacts, etc., can be significantly reduced when both a suitable electrolyte is used and the measuring conditions are carefully selected. In this work, the use of photoelectrochemical techniques with InP structures is reported. The work focuses on both the characterization and the optimization of structures grown by thermal diffusion and by epitaxial methods. Characterization of the structures is done by studying the variation in the density of surface states, number of defects, and net majority carrier concentration as a function of material removed. A step-by-step optimization process of n(sup +)p and p(sup+)n InP structures is also described. This involves the passivation and subsequent removal of damaged layers in order to extract the performance parameters of solar cells fabricated with these structures.
Faur, Maria↗
Optimization of continuous one-dimensional structures under steady harmonic excitation
The paper examines some questions relating to the optimal design of continuous one-dimensional structures driven by harmonically oscillating loads. Optimal-control methods are applied to a cantilever bar driven sinusoidally by an axial force at its tip to illustrate the minimum-weight design of one-dimensional structures under dynamic excitation. Realistic constraints are imposed during the optimizations, including a maximum allowable stress amplitude at any point along the bar and a minimum cross-sectional area. It is shown that in the absence of damping, the design space may contain many disjoint feasible regions, and multiple optima can exist. Detailed solutions are obtained for continuous bars with an excitation frequency less than, and then greater than, the fundamental free-vibration frequency. It is found that above a certain excitation frequency, two or more arcs with different constraints characterize the optimal designs. It is concluded that when more than two different constrained arcs characterize the optimal solution, the continuum approach may be impractical, and finite-element approximations may offer the only alternative.
Johnson, E. H.↗
Optimal Signal Filtration in Optical Sensors with Natural Squeezing of Vacuum Noises
The structure of optimal receiver is discussed for optical sensor measuring a small displacement of probe mass. Due to nonlinear interaction of the field and the mirror, a reflected wave is in squeezed state (natural squeezing), two quadratures of which are correlated and therefore one can increase signal-to-noise ratio and overcome the SQL. A measurement procedure realizing such correlation processing of two quadratures is clarified. The required combination of quadratures can be produced via mixing of pump field reflected from the mirror with local oscillator phase modulated field in duel-detector homodyne scheme. Such measurement procedure could be useful not only for resonant bar gravitational detector but for laser longbase interferometric detectors as well.
Gusev, A. V.↗
Composite Bus Structure for the SMEX/WIRE Satellite
In an effort to reduce the weight and optimize the structural design of the Small Explorer (SMEX) Wide-Field Infrared Explorer (WIRE) spacecraft, it has become desirable to change the material and construction from mechanically fastened aluminum structure to a fully bonded fiber-reinforced composite (FRC) structure. GSFC has developed the WIRE spacecraft structural bus design concept, including the instrument and launch vehicle requirements. The WIRE Satellite is the fifth of a series of SMEX satellites to be launched once per year. GSFC has chosen Composite Optics Inc. (COI) as the prime contractor for the development and procurement of the WIRE composite structure. The detailed design of the fully bonded FRC structure is based on COI's Short Notice Accelerated Production SATellite ("SNAPSAT") approach. SNAPSAT is a state of the art design and manufacturing technology for advanced composite materials which utilizes flat-stock detail parts bonded together to produce a final structural assembly. The structural design approach adopted for the WIRE structure provides a very viable alternative to both traditional aluminum construction as well as high tech. molded type composite structures. This approach to composite structure design is much less costly than molded or honeycomb sandwich type composite construction, but may cost slightly more than conventional aluminum construction on the subsystem level. However on the overall program level the weight saving achieved is very cost effective, since the primary objective is to allocate more mass for science payloads.
Rosanova, Giulio G.↗
Minimal complexity control law synthesis
A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.
Bernstein, Dennis S.↗
An efficiency study of the simultaneous analysis and design of structures
The efficiency of the Simultaneous Analysis and Design (SAND) approach in the minimum weight optimization of structural systems subject to strength and displacement constraints as well as size side constraints is investigated. SAND allows for an optimization to take place in one single operation as opposed to the more traditional and sequential Nested Analysis and Design (NAND) method, where analyses and optimizations alternate. Thus, SAND has the advantage that the stiffness matrix is never factored during the optimization retaining its original sparsity. One of SAND's disadvantages is the increase in the number of design variables and in the associated number of constraint gradient evaluations. If SAND is to be an acceptable player in the optimization field, it is essential to investigate the efficiency of the method and to present a possible cure for any inherent deficiencies.
Striz, Alfred G.↗
RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design
Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.
Genetic algorithms↗