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A definition of the multidisciplinary design optimization (MDO) is introduced, and functionality and relationship of the MDO conceptual components are examined. The latter include design-oriented analysis, approximation concepts, mathematical system modeling, design space search, an optimization procedure, and a humane interface.
Nickel-based superalloys and near-equiatomic high-entropy alloys containing molybdenum are known for higher temperature strength and corrosion resistance. Yet, complex solid-solution alloys offer a huge design space to tune for optimal properties at slightly reduced entropy. For refractory Mo-W-Ta-Ti-Zr, we showcase KKR electronic structure methods via the coherent-potential approximation to identify alloys over five-dimensional design space with improved mechanical properties and necessary global (formation enthalpy) and local (short-range order) stability. Deformation is modeled with classical molecular dynamic simulations, validated from our first-principle data. We predict complex solid-solution alloys of improved stability with greatly enhanced modulus of elasticity (3× at 300 K) over near-equiatomic cases, as validated experimentally, and with higher moduli above 500 K over commercial alloys (2.3× at 2000 K). We also show that optimal complex solid-solution alloys are not described well by classical potentials due to critical electronic effects.
This paper describes a preliminary study and conceptual design of a low concentration ratio solar array for a space station application with approximately a 100 kW power requirement. The baseline design calls for a multiple series of inverted, truncated, pyramidal optical elements with a geometric concentration ratio (GCR) of 6. It also calls for low life cycle cost, simple on-orbit maintainability, 1984 technology readiness date, and gallium arsenide (GaAs) of silicon (Si) solar cell interchangeability. Due to the large area needed to produce the amount of power required for the baseline space station, a symmetrical wing design, making maximum use of the commonality of parts approach, was taken. This paper will describe the mechanical and structural design of a mass-producible solar array that is very easy to tailor to the needs of the individual user requirement.
A new type of continuously operating, in-situ, remotely monitored sensor is presented. The sensor is comprised of a thin film array of magnetostatically coupled, magnetically soft ferromagnetic thin film structures, adhered to or encased within a thin polymer layer. The polymer is made so that it swells or shrinks in response to the chemical analyte of interest, which in this case is pH. As the polymer swells or shrinks, the magnetostatic coupling between the magnetic elements changes, resulting in changes in the magnetic switching characteristics of the sensor. Placed within a sinusoidal magnetic field the magnetization vector of the coupled sensor elements periodically reverses directions, generating magnetic flux that can be remotely detected as a series of voltage spikes in appropriately placed pickup coils. one preliminary sensor design consists of four triangles, initially spaced approximately 50 micrometers apart, arranged to form a 12 mm x 12 mm square with the triangle tips centered at a common origin. Our preliminary work has focused on monitoring of pH using a lightly crosslinked pH sensitive polymer layer of hydroxyethylmethacrylate and 2-(dimethylamino) ethylmethacrylate. As the polymer swells or shrinks the magnetostatic coupling between the triangles changes, resulting in measurable changes in the amplitude of the detected voltage spirits.
This paper proposes a novel data-driven method for the reliable prediction of the power grid’s post-fault trajectories, i.e., the power grid’s dynamic response after a disturbance or fault. Here, the proposed method is based on the recently proposed concept of Deep Operator Networks (DeepONets). Unlike traditional neural networks that learn to approximate functions, DeepONets are designed to approximate nonlinear operators, i.e., mappings between infinite-dimensional spaces. Under this operator framework, we design a novel and efficient DeepONet that (i) takes as inputs the trajectories collected before and during the fault and (ii) outputs the predicted post-fault trajectories. In addition, we endow our method with the much-needed ability to balance efficiency with reliable/trustworthy predictions via uncertainty quantification. To this end, we propose and compare two novel methods that enable quantifying the predictive uncertainty. First, we propose a Bayesian DeepONet (B-DeepONet) that uses stochastic gradient Hamiltonian Monte-Carlo to sample from the posterior distribution of the DeepONet trainable parameters. Then, we design a Probabilistic DeepONet (Prob-DeepONet) that uses a probabilistic training strategy to enable quantifying uncertainty at virtually no extra computational cost. Finally, we validate the proposed methods’ predictive power and uncertainty quantification capability using the New York-New England power grid model.
The literature offers a number of approximations for analytically and/or efficiently computing the probability of collision between two space objects. However, only one of these techniques is a completely analytical approximation that is suitable for use in the preliminary design phase, when it is more important to quickly analyze a large segment of the trade space than it is to precisely compute collision probabilities. Unfortunately, among the types of formations that one might consider, some combine a range of conditions for which this analytical method is less suitable. This work proposes a simple, conservative approximation that produces reasonable upper bounds on the collision probability in such conditions. Although its estimates are much too conservative under other conditions, such conditions are typically well suited for use of the existing method.
This paper describes a space mission for visible direct detection and spectroscopy of Earth like extrasolar planets using a nulling coronagraph instrument behind a moderately sized (approximately 4m) telescope in space. In our design, a 4 beam nulling interferometer is synthesized from the telescope pupil, producing a deep null proportional to theta (sup 4) which is then filtered by a coherent array of single mode fibers to suppress the residual scattered light. With diffraction limited telescope optics and similar quality components in the optical train (lambda/20), suppression of the starlight to 10 (exp -10) is achievable. We describe key features of the basic analysis, show how this effects a space mission design, present latest results of laboratory measurements demonstrating achievable null depth and component development, and discuss future key technical milestones.
A method is presented for the minimum mass design of three dimensional space frames constructed of thin walled rectangular cross-section members. Constraints on nodal displacements and rotations, material stress, local buckling, and cross sectional dimensions are included. A high quality separable approximate problem is formed in terms of the reciprocals of the four section properties of the frame element cross section, replacing all implicit functions with simplified explicit relations. The cross sectional dimensions are efficiently calculated without using multilevel techniques. Several test problems are solved, demonstrating that a series of approximate problem solutions converge rapidly to an optimal design.
The integration of Kennedy Space Center (KSC) ground support systems with the new launch processing system and new launch vehicle provided KSC with a unique challenge in system design and analysis for the Space Transportation System. Approximately 70 support systems are controlled and monitored by the launch processing system. Typical systems are main propulsion oxygen and hydrogen loading systems, environmental control life support system, hydraulics, etc. An End-to-End concept of documentation and analysis was chosen and applied to these systems. Unique problems were resolved in the areas of software analysis, safing under emergency conditions, sampling rates, and control loop analysis. New methods of performing End-to-End reliability analyses were implemented. The systems design approach selected and the resolution of major problem areas are discussed.
The recommendations summarized herein constitute a basis on which an initial exercise prescription can be formulated. It is noteworthy that any exercise program designed currently would be an approximation. Examination of the existing space-flight data reveals a scarcity of in-flight data on which to rigorously design an exercise program. The relevant experience within the U.S. space program (with regard to long-duration space flight) is limited to the Skylab Program. Lessons learned from Skylab are relevant to the design of a Space Station exercise program, especially with regard to the total length of exercise time required, cardiovascular (CV) deconditioning/reconditioning, and bone loss. Certain observations of the U.S.S.R. exercise activities can also contribute to the formulation of an exercise prescription of Space Station. Reportedly, the U.S.S.R. uses both a bicycle ergometer and a treadmill device on long-duration missions with some degree of success. Using the third crew of Salyut 6, which was a 175-day stay, as a representative mission, the typical time dedicated to exercise varies from 2 to 3 hours per day. In addition, the cosmonauts wear an elasticized suit, called a penquin suit, for time periods ranging from 12 to 16 hours per day. This device provides a load across the axial skeleton against which the wearer must exert himself. Despite these extensive countermeasures, the effects of adaptation are not totally prevented.
All-dielectric metasurfaces exhibit exotic electromagnetic responses, similar to those obtained with metal-based metamaterials. Research in all-dielectric metasurfaces currently uses relatively simple unit-cell designs, but increased geometrical complexity may yield even greater scattering states. Although machine learning has recently been applied to the design of metasurfaces with impressive results, the much more challenging task of finding a geometry that yields a desired spectra remains largely unsolved. We propose and demonstrate a method capable of finding accurate solutions to ill-posed inverse problems, where the conditions of existence and uniqueness are violated. A specific example of finding the metasurface geometry which yields a radiant exitance matching the external quantum efficiency of gallium antimonide is demonstrated. We also show how the neural-adjoint method can intelligently grow the design search space to include designs that increasingly and accurately approximate the desired scattering response. The neural-adjoint method is not restricted to the case demonstrated and may be applied to plasmonics, photonic crystal, and other artificial electromagnetic materials.
Design analyses showed that an ion thruster of approximately 50 cm in diameter will be required to produce a thrust of 0.5 N using xenon or argon as propellants, and operating the thruster at a specific impulse of 3530 sec or 6076 sec respectively. A multipole magnetic confinement discharge chamber was specified.
Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machine learning to systematically optimize the production of isoprenol, a sustainable aviation fuel precursor, in Pseudomonas putida. The simultaneous downregulation through CRISPR interference of combinations of up to four gene targets, guided by machine learning, permitted us to increase isoprenol titer 5-fold in six consecutive design-build-test-learn cycles. Moreover, machine learning enabled us to swiftly explore a vast experimental design space of 800,000 possible combinations by strategically recommending approximately 400 priority constructs. High-throughput proteomics allowed us to validate CRISPRi downregulation and identify biological mechanisms driving production increases. Our work demonstrates that ML-driven automated design-build-test-learn cycles, when combined with rigorous data validation, can rapidly enhance titers without specific biological knowledge, suggesting that it can be applied to any host, product, or pathway.
To determine the best configuration from all candidate configurations, it was necessary first to calculate minimum system weights and performance. To optimize the design, it is necessary to vary configuration-specific variables such as total system weight, thrust-to-weight ratios, burn durations, total thrust available, and mass fraction for the system. Optimizing each of these variables at the same time is technically unfeasible and not necessarily mathematically possible. However, discrete sets of data can be generated which will eliminate many candidate configurations. From the most promising remaining designs, a final configuration can be selected. Included are the three most important designs considered: one which closely approximates the design criteria set forth in a Marshall Space Flight Center study of the Shuttle 2; the configuration used in the initial proposal; and the final configuration. A listing by cell of the formulas used to generate the aforementioned data is included for reference.
Performance requirements and costs for transportation, fabrication, and orbital assembly are the drivers in the design of large space antennas will range in size from approximately 30 m to 1 km in diameter and include radiometers, multibeam lens antennas, and microwave power transmission systems. Research and development is required to define comprehensive structural criteria for specific missions, to determine optimized geometries for truss elements and truss configurations and to establish requirements for joint design with consideration of tolerances, load transfer, thermal compatibility, and assembly and disassembly. Candidate structural elements, materials systems for the low pressure rapid cure of advanced composite materials, and various on orbit assembly and fabrication techniques must also be developed.
Turbulent, direct drag has been measured for a series of riblet models in air with continuous, low-level suction or blowing applied through narrow streamwise slots located at the peak, base, or valley of the rectangularly shaped riblets. Riblet spacing was approximately that of low-speed wall streaks. The models were designed to test whether wall vortices which are known to occur along widely spaced riblets are integral to turbulence production by attempting to alter them with localized suction or blowing. The drag data show trends that are consistent with reduced or enhanced inflectional breakdown of wall vortices. The trends, however, may also be explained by more fundamental mean-flow effects.
The minimum weight optimum design of damped linearly elastic structural systems subjected to periodic loading with behavior constraints on maximum deflections and side constraints on design variables is addressed. Attention is focused on the two major impediments to an optimal solution: (1) the time parametric nature of the behavior constraints; and (2) the severe nonconvexity of the design space. A solution method based on upper bound approximations for the behavior constraints and an innovative mathematical programming scheme for seeking the optimal frequency subspace is set forth. Numerical results for several test problems illustrate the effectiveness of the method reported.
Generally, it has been documented that the wearing of engine parts forms a failure distribution which can be approximated by a function developed by Weibull. The purpose here is to examine to what extent the Weibull distribution approximates failure data for designated engine parts of the Space Shuttle Main Engine (SSME). The current testing certification requirements will be examined in order to establish confidence levels. An examination of the failure history of SSME parts/assemblies (turbine blades, main combustion chamber, or high pressure fuel pump first stage impellers) which are limited in usage by time or starts will be done by using updated Weibull techniques. Efforts will be made by the investigator to predict failure trends by using Weibull techniques for SSME parts (turbine temperature sensors, chamber pressure transducers, actuators, and controllers) which are not severely limited by time or starts.