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An analysis and optimization of a mirror-actuator system for large excursion/high-frequency chopping is developed. The results of this analysis, combined with laboratory measurements of a prototype actuator operating at cryogenic temperatures, allow performance predictions to be made for a real system utilizing this technology.
COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.
An approximate structural eigenvalue/vector analysis technique which uses eigensensitivities in a truncated Taylor series expression is presented. It is shown that this technique can provide the computational efficiency urgently needed for large scale control-structure optimization problems. In addition, a unified formulation and solution approach for calculating eigenvalue and eigenvector derivatives of the real symmetric structural eigenvalue problem is presented.
Simultaneously achieving the fuel consumption and noise reduction goals set forth by NASA's Environmentally Responsible Aviation (ERA) project requires innovative and unconventional aircraft concepts. In response, advanced hybrid wing body (HWB) aircraft concepts have been proposed and analyzed as a means of meeting these objectives. For the current study, several HWB concepts were analyzed using the Hybrid wing body Conceptual Design and structural optimization (HCDstruct) analysis code. HCDstruct is a medium-fidelity finite element based conceptual design and structural optimization tool developed to fill the critical analysis gap existing between lower order structural sizing approaches and detailed, often finite element based sizing methods for HWB aircraft concepts. Whereas prior versions of the tool used a half-model approach in building the representative finite element model, a full wing-tip-to-wing-tip modeling capability was recently added to HCDstruct, which alleviated the symmetry constraints at the model centerline in place of a free-flying model and allowed for more realistic center body, aft body, and wing loading and trim response. The latest version of HCDstruct was applied to two ERA reference cases, including the Boeing Open Rotor Engine Integration On an HWB (OREIO) concept and the Boeing ERA-0009H1 concept, and results agreed favorably with detailed Boeing design data and related Flight Optimization System (FLOPS) analyses. Following these benchmark cases, HCDstruct was used to size NASA's ERA HWB concepts and to perform a related scaling study.
Computer models of rocket engines and single-stage-to-orbit vehicles that were developed by the authors at DFVLR and NASA have been combined. The resulting code consists of engine mass, performance, trajectory and vehicle sizing models. The engine mass model includes equations for each subsystem and describes their dependences on various propulsion parameters. The engine performance model consists of multidimensional sets of theoretical propulsion properties and a complete thermodynamic analysis of the engine cycle. The vehicle analyses include an optimized trajectory analysis, mass estimation, and vehicle sizing. A vertical-takeoff, horizontal-landing, single-stage, winged, manned, fully reusable vehicle with a payload capability of 13.6 Mg (30,000 lb) to low earth orbit was selected. Hydrogen, methane, propane, and dual-fuel engines were studied with staged-combustion, gas-generator, dual bell, and the dual-expander cycles. Mixture ratio, chamber pressure, nozzle exit pressure liftoff acceleration, and dual fuel propulsive parameters were optimized.
A quieter and aerodynamically more efficient proprotor design requires high-fidelity and well-integrated optimization and analysis tools. To fulfill that requirement, the present paper delivers a methodology based on multidisciplinary, adjoint-based, discrete optimization. SU2-based code development involves the implementation of aeroacoustic analysis, adjoint computations, and integrations into a multidisciplinary rotorcraft optimization suite. Submodules utilized in the optimization are verified with wind tunnel data to demonstrate the accuracy of aerodynamic and aeroacoustic analyses. The developed code is used for NASA's helically twisted proprotor to maximize the aeroacoustic performance of the proprotor while holding thrust constant. The optimization process considers multiple flight conditions (hence, multipoint), which are forward flight and hovering. As an outcome of the analyses, the optimized blade design propagates lower noise as perceived by multiple observers in both flight conditions
An overview is presented of current research activities which, in a broad context, are focused on the development and verification of integrated structural analysis and optimal design capabilities for advanced aerospace propulsion and power systems. The overview encompasses a variety of subject areas including: (1) composite materials; (2) advanced structural analysis; (3) constitutive modeling; (4) computational simulation; (5) probabilistic analysis; and (6) multidisciplinary optimization. Typical results are presented which illustrate the benefit and utility of the emerging technologies as applied to propulsion and power system structures.
A method is developed for sensitivity analysis and optimization of nodal point locations in connection with vibration reduction. A straightforward derivation of the expression for the derivative of nodal locations is given, and the role of the derivative in assessing design trends is demonstrated. An optimization process is developed which uses added lumped masses on the structure as design variables to move the node to a preselected location; for example, where low response amplitude is required or to a point which makes the mode shape nearly orthogonal to the force distribution, thereby minimizing the generalized force. The optimization formulation leads to values for added masses that adjust a nodal location while minimizing the total amount of added mass required to do so. As an example, the node of the second mode of a cantilever box beam is relocated to coincide with the centroid of a prescribed force distribution, thereby reducing the generalized force substantially without adding excessive mass. A comparison with an optimization formulation that directly minimizes the generalized force indicates that nodal placement gives essentially a minimum generalized force when the node is appropriately placed.
The accuracy and robustness of a two-dimensional smoothing methodology is examined for the problem of recovering accurate interlaminar shear stress distributions in laminated composite and sandwich plates. The smoothing methodology is based on a variational formulation which combines discrete least-squares and penalty-constraint functionals in a single variational form. The smoothing analysis utilizes optimal strains computed at discrete locations in a finite element analysis. These discrete strain data are smoothed with a smoothing element discretization, producing superior accuracy strains and their first gradients. The approach enables the resulting smooth strain field to be practically C1-continuous throughout the domain of smoothing, exhibiting superconvergent properties of the smoothed quantity. The continuous strain gradients are also obtained directly from the solution. The recovered strain gradients are subsequently employed in the integration o equilibrium equations to obtain accurate interlaminar shear stresses. The problem is a simply-supported rectangular plate under a doubly sinusoidal load. The problem has an exact analytic solution which serves as a measure of goodness of the recovered interlaminar shear stresses. The method has the versatility of being applicable to the analysis of rather general and complex structures built of distinct components and materials, such as found in aircraft design. For these types of structures, the smoothing is achieved with 'patches', each patch covering the domain in which the smoothed quantity is physically continuous.
A major goal of NASA is to create an advance space transportation system that provides a safe, affordable highway through the air and into space. The long-term plans are to reduce the risk of crew loss to 1 in 1,000,000 missions and reduce the cost of Low-Earth Orbit by a factor of 100 from today's costs. A third generation reusable concept vehicle (RCV) was developed to assess technologies required to meet NASA's space access goals. The vehicle will launch from Cape Kennedy carrying a 25,000 lb. payload to the International Space Station (ISS). The system is an air breathing launch vehicle (ABLV) hypersonic lifting body with rockets and uses triple point hydrogen and liquid oxygen propellant. The focus of this paper is on the structural concepts and analysis methods used in developing the third generation reusable launch vehicle (RLV). Member sizes, concepts and material selections will be discussed as well as analysis methods used in optimizing the structure. Analysis based on the HyperSizer structural sizing software will be discussed. Design trades required to optimize structural weight will be presented.
NASA's Aeronautics Research Mission Directorate recently restructured its Vehicle Systems Program, refocusing it towards understanding the fundamental physics that govern flight in all speed regimes. Now called the Fundamental Aeronautics Program, it is comprised of four new projects, Subsonic Fixed Wing, Subsonic Rotary Wing, Supersonics, and Hypersonics. The Aeronautics Research Mission Directorate has charged the Hypersonics Project with having a basic understanding of all systems that travel at hypersonic speeds within the Earth's and other planets atmospheres. This includes both powered and unpowered systems, such as re-entry vehicles and vehicles powered by rocket or airbreathing propulsion that cruise in and accelerate through the atmosphere. The primary objective of the Hypersonics Project is to develop physics-based predictive tools that enable the design, analysis and optimization of such systems. The Hypersonics Project charges the systems analysis discipline team with providing it the decision-making information it needs to properly guide research and technology development. Credible, rapid, and robust multi-disciplinary system analysis processes and design tools are required in order to generate this information. To this end, the principal challenges for the systems analysis team are the introduction of high fidelity physics into the analysis process and integration into a design environment, quantification of design uncertainty through the use of probabilistic methods, reduction in design cycle time, and the development and implementation of robust processes and tools enabling a wide design space and associated technology assessment capability. This paper will discuss the roles and responsibilities of the systems analysis discipline team within the Hypersonics Project as well as the tools, methods, processes, and approach that the team will undertake in order to perform its project designated functions.
In support of Electrified Powertrain Flight Demonstrator and Advanced Air Transport Technologies programs at NASA, engineers at NASA Ames and NASA Glenn Research Centers have developed a new tool for coupled engine and airframe optimization and analysis. The new tool combines the engineering-level analysis methods of the FORTRAN General Aviation Synthesis Program (GASP) with the OpenMDAO framework to handle highly coupled problems that legacy tools struggle to optimize. The tool has been verified to match GASP with good agreement on a 737 MAX8 baseline vehicle closure problem, and preliminary efforts have been made to integrate the pyCycle thermodynamic cycle analysis tool for electrified engine optimization in the context of a vehicle optimization problem.
Realizing the SETO 2030 mission of reducing solar energy costs to 3-5 c/kWh will require innovative enabling research on effective, cost-efficient integration of local PV within distribution systems. However, the intermittent and variable nature of PVs compels operators to impose conservative hosting capacity constraints. Given the extremely high variability of (intermittent and unpredictable) solar energy generation, relaxing the capacity constraints (which are currently around 15%) and achieving 100% or greater integration of renewables will require a fundamental transformation of the power grid via the utilization of exponentially larger amounts of AMI enabled fine-grained data. To address the challenges in increasing the penetration of renewable energy based DERs, this project envisions an Enhanced System Layer (ESL) at the distribution network level that is reliable, cost-effective and scalable to millions of Distributed Energy Resources (DERs)/devices. This includes developing: 1) Transformative and highly scalable machine learning based predictive analytics tools that plug into distribution system planning and provide real-time situational awareness at the distribution level for short and long-term operational planning. The tools will be built using novel data-driven energy models of millions of active nodes with AMI, 2) Adaptive stochastic analysis and optimization algorithms for real-time grid operations, 3) Dynamic Scenario Analysis using parallel Cloudenabled implementations with < 1 minute computational cycle times.
Zileuton (ZLT) is an active oral inhibitor of enzyme 5-lipoxygenase, and long-term intake and overdose of ZLT cause adverse effects, leading to critical conditions in patients. This is a well-recognized issue that necessitates a better approach for ZLT sensing. Given the increasing interest in ZLT sensing and the limitations of previous techniques, there is a need for a highly sensitive, robust, and fast operation method that is inexpensive and easy to use. Thus, for the sensitive detection and determination of ZLT, an electrochemical sensor based on graphene was fabricated. Graphene has excellent properties, such as high surface area, low toxicity, conductivity, and electroactive conjugation with biomolecules, making it suitable for sensing. The electrocatalytic property of graphene promotes the redox-coupled reaction of ZLT. Electrochemical investigation of the modifier was carried out by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). An optimization and analysis of the influence of different parameters on the electrochemical behavior of ZLT were carried out using the CV approach. The scan rate study aided in exploring the physicochemical properties of the electrode process, and two electrons with two protons were found to be involved in the electrooxidation of ZLT. The fabricated sensor showed a wide range of linearity with ZLT, from 0.3 µM to 100.0 µM, and the detection limit was evaluated as 0.03 µM under optimized conditions. The analysis of spiked urine samples, with good recovery values for percent RSD, provided support for the efficiency and applicability of the developed electrode.
The sizing, criteria, cost analysis, and optimized taper of the Solar Power Satellite (SPS) transmitting antenna are discussed. The sizing parameters considered were a thermal limit of 23 kW/sq m in the antenna, a peak power density of 23 mW/sq cm in the ionosphere, and cost effectiveness. Cost schedules and equations are presented for the SPS, and four antenna tapers are analyzed and compared, including the reference 10 dB Gaussian taper. An even powered quadratic series is formulated to minimize electricity cost and stay within thermal and ionospheric power level limits. The optimized Johnson Space Center taper is found to display the lowest energy costs, 4% below the 10 dB Gaussian, and can deliver 5.69 GW at 45.4 mills/kWh to the grid. Further studies are indicated for the optimal antenna and rectenna sizes
Results are presented for four optimization benchmark problems posed by the AIAA Aerodynamic Design Optimization Discussion Group. The benchmarks are intended to exercise optimization frameworks on representative airfoil and wing design problems. All problems involve drag minimization subject to geometric and aerodynamic constraints. Our design approach involves two forms of adaptation. First, the shape parameterization is gradually and automatically enriched from an initially coarse search space. Second, adjoint solutions are used to drive adaptive mesh refinement to control discretization error. The error threshold is tailored so that the nest meshes, with the greatest accuracy, are used only when nearing the optimum. On the inviscid airfoil design problem, while reducing the drag by a factor of 10, we show how the combination of progressive parameterization and tiered discretization error control can dramatically accelerate the optimization. On the viscous airfoil design problem, we use inviscid analysis-driven optimization to reduce the total drag by a factor of two. Next, we improve the span efficiency factor of a wing by performing twist optimization. Finally, we optimize the Common Research Model wing, managing to hold drag roughly fixed, while targeting an initially-violated pitching moment constraint. Our approach aims to introduce greater complexity and accuracy only when necessary to improve the design, and also support a greater degree of automation.
A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.
Fundamental explosive testing was conducted by the NASA/MSFC Blast Team (N2L) to determine yields produced from cryogenic liquid mixtures of methane and oxygen for a range of oxygen-to-fuel ratios. The blast wave overpressure and high-speed video data were processed by the NASA led multi-agency data analysis team. This document serves to provide a summary of the optimized data analysis produced and the resulting conclusions regarding the yields achieved during this test program.