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At least 235 records · Page 13

The Analysis and Design of Low Boom Configurations Using CFD and Numerical Optimization Techniques

The use of computational fluid dynamics (CFD) for the analysis of sonic booms generated by aircraft has been shown to increase the accuracy and reliability of predictions. CFD takes into account important three-dimensional and nonlinear effects that are generally neglected by modified linear theory (MLT) methods. Up to the present time, CFD methods have been primarily used for analysis or prediction. Some investigators have used CFD to impact the design of low boom configurations using trial and error methods. One investigator developed a hybrid design method using a combination of Modified Linear Theory (e.g. F-functions) and CFD to provide equivalent area due to lift driven by a numerical optimizer to redesign or modify an existing configuration to achieve a shaped sonic boom signature. A three-dimensional design methodology has not yet been developed that completely uses nonlinear methods or CFD. Constrained numerical optimization techniques have existed for some time. Many of these methods use gradients to search for the minimum of a specified objective function subject to a variety of design variable bounds, linear and nonlinear constraints. Gradient based design optimization methods require the determination of the objective function gradients with respect to each of the design variables. These optimization methods are efficient and work well if the gradients can be obtained analytically. If analytical gradients are not available, the objective gradients or derivatives with respect to the design variables must be obtained numerically. To obtain numerical gradients, say, for 10 design variables, might require anywhere from 10 to 20 objective function evaluations. Typically, 5-10 global iterations of the optimizer are required to minimize the objective function. In terms of using CFD as a design optimization tool, the numerical evaluation of gradients can require anywhere from 100 to 200 CFD computations per design for only 10 design variables. If one CFD computation requires an hour of computational time on a Cray computer, one can see that the use of constrained numerical optimization quickly becomes impractical.Hence, in order to practically couple a numerical design optimization technique with a CFD method, the CFD method must be extremely efficient with running times on the order of only minutes. The CFD Euler code developed under NASA sponsorship and referred to as MIM3D-SB for the most part fulfills these efficiency requirements. Analysis of wing- body configurations can be computed in a matter of a few minutes. The present study will concentrate on the feasibility of the use of this CFD code in conjunction with a numerical design optimization technique for the sonic boom reduction of candidate HSCT configurations. A preliminary supersonic aircraft design system has been established that utilizes the numerical design optimization code NPSOL developed at Stanford University coupled with the supersonic NUM3D-SB CFD code. Many questions still need to be answered in regard to using CFD and numerical optimizers as design tools. There are difficulties related to both the CFD codes and the numerical optimizers. Numerical optimizers can converge to a local minima rather than a global minima. This behavior is largely a function of the initial guess in the design space. The optimizer also is searching for a minimum of the function in terms of its derivative without any regard to the actual function value. Numerically (i.e. CFD) determined gradients can also generate spurious numerical local minima. In addition, for the sonic boom problem, grid fineness will also determine the accuracy of the final design solution. Design optimization methods work well on problems defined by continuous objective functions. The sonic boom signature design problem is not necessarily defined by a continuous objective function. The signature can have a variety of shapes; i.e. from N-wave to multiple shocks. The far-field or ground signature may not transition continuously from one shape to another and hence, may exhibit discontinuous behavior. This is also a source of difficulty in using design optimization methods.In the following sections, several low boom and one reference aircraft configuration will be analyzed to predict their sonic boom signature characteristics. Modifications to some of these designs will also be presented to demonstrate the feasibility of using CFD as a design tool and to demonstrate the feasibility of designing shaped sonic boom signatures. Design modifications to some configurations will be presented to demonstrate the feasibility of achieving shaped signatures with reduced levels and not necessarily to represent realistic or aerodynamically efficient design modifications. Fuselage volume or camber are used as design variables in order to have a minimal effect on the primary wing aerodynamics. The paper will also seek to demonstrate whether a hybrid or ramped signature is feasible to achieve. For the low-boom configurations, the CFD predicted signatures will be compared qualitatively to their MLT design signatures.

Siclari, Michael J.↗

Multidisciplinary optimization of a controlled space structure using 150 design variables

A controls-structures interaction design method is presented. The method coordinates standard finite-element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structure and control system of a spacecraft. Global sensitivity equations are used to account for coupling between the disciplines. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Design problems using 15, 63, and 150 design variables to optimize truss member sizes and feedback gain values are solved and the results are presented. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporation of the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables.

James, Benjamin B.↗

Design of a Propeller with Global Minimum Torque

Academia, industry, and Government are actively working towards a future where dozens of small to large Unmanned Aerial Systems (UAS) are present within urban environments. In this environment, high noise pollution and inefficiencies have the potential to render these new technologies impractical due to public annoyance and nonacceptance. This study aims to design and analyze a novel propeller design for minimum global torque using an optimization algorithm to find the full three dimensional solution of maximum efficiency. This resulted in a 𝐶 𝑙 distribution defining the global minimum torque solution for propeller design which corresponded with moving as much lift inboard as possible and reducing lift rapidly at the blade tip. The novel propeller (dubbed "Prandtl" propeller) was then compared with the current gold standard in propeller design, a minimum induced loss (MIL) propeller, which had all the same geometric properties except for blade twist and produced the same amount of thrust at the same advance ratio. The results of multiple iterations of Prandtl propellers showed an increase in efficiency of 2.0-3.3% for the Prandtl blade when compared to the equivalent MIL blade. A potential added benefit of this blade design is lower noise generation due to the lower lift loading at the tip reducing the large shear layer intensity which is the point source of noise in propellers. Two major breakthroughs for enabling widespread use of UAS in urban environments are noise reduction and vehicle efficiency, and this new propeller design has the potential to provide both.

Propeller↗

Design of a Propeller with Global Minimum Torque

Academia, industry, and Government are actively working towards a future where dozens of small to large Unmanned Aerial Systems (UAS) are present within urban environments. In this environment, high noise pollution and inefficiencies have the potential to render these new technologies impractical due to public annoyance and nonacceptance. This study aims to design and analyze a novel propeller design for minimum global torque using an optimization algorithm to find the full three dimensional solution of maximum efficiency. This resulted in a 𝐶 𝑙 distribution defining the global minimum torque solution for propeller design which corresponded with moving as much lift inboard as possible and reducing lift rapidly at the blade tip. The novel propeller (dubbed "Prandtl" propeller) was then compared with the current gold standard in propeller design, a minimum induced loss (MIL) propeller, which had all the same geometric properties except for blade twist and produced the same amount of thrust at the same advance ratio. The results of multiple iterations of Prandtl propellers showed an increase in efficiency of 2.0-3.3% for the Prandtl blade when compared to the equivalent MIL blade. A potential added benefit of this blade design is lower noise generation due to the lower lift loading at the tip reducing the large shear layer intensity which is the point source of noise in propellers. Two major breakthroughs for enabling widespread use of UAS in urban environments are noise reduction and vehicle efficiency, and this new propeller design has the potential to provide both.

Propeller↗

GMI Instrument Spin Balance Method, Optimization, Calibration, and Test

The Global Microwave Imager (GMI) instrument must spin at a constant rate of 32 rpm continuously for the 3 year mission life. Therefore, GMI must be very precisely balanced about the spin axis and CG to maintain stable scan pointing and to minimize disturbances imparted to the spacecraft and attitude control on-orbit. The GMI instrument is part of the core Global Precipitation Measurement (GPM) spacecraft and is used to make calibrated radiometric measurements at multiple microwave frequencies and polarizations. The GPM mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and frequent precipitation measurements. Ball Aerospace and Technologies Corporation (BATC) was selected by NASA Goddard Space Flight Center to design, build, and test the GMI instrument. The GMI design has to meet a challenging set of spin balance requirements and had to be brought into simultaneous static and dynamic spin balance after the entire instrument was already assembled and before environmental tests began. The focus of this contribution is on the analytical and test activities undertaken to meet the challenging spin balance requirements of the GMI instrument. The novel process of measuring the residual static and dynamic imbalances with a very high level of accuracy and precision is presented together with the prediction of the optimal balance masses and their locations.

Ayari, Laoucet↗

GMI Instrument Spin Balance Method, Optimization, Calibration and Test

The Global Microwave Imager (GMI) instrument must spin at a constant rate of 32 rpm continuously for the 3-year mission life. Therefore, GMI must be very precisely balanced about the spin axis and center of gravity (CG) to maintain stable scan pointing and to minimize disturbances imparted to the spacecraft and attitude control on-orbit. The GMI instrument is part of the core Global Precipitation Measurement (GPM) spacecraft and is used to make calibrated radiometric measurements at multiple microwave frequencies and polarizations. The GPM mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and frequent precipitation measurements. Ball Aerospace and Technologies Corporation (BATC) was selected by NASA Goddard Space Flight Center to design, build, and test the GMI instrument. The GMI design has to meet a challenging set of spin balance requirements and had to be brought into simultaneous static and dynamic spin balance after the entire instrument was already assembled and before environmental tests began. The focus of this contribution is on the analytical and test activities undertaken to meet the challenging spin balance requirements of the GMI instrument. The novel process of measuring the residual static and dynamic imbalances with a very high level of accuracy and precision is presented together with the prediction of the optimal balance masses and their locations.

Ayari, Laoucet↗

Local Food Crop Production can Fulfil Demand for Less than One-Third of the Population

The distance between the origin and end-point of food supply chains, and the ‘localness’ of food systems, are key considerations of many narratives associated with sustainability. Yet, information on the minimum distance to food crops is still scarce at the global level. Using an optimization model based on ‘foodsheds’ (that is, self-sufficient areas with internal dependencies), we calculate the potential minimum distance between food production and consumption for six crop types around the world. We show that only 11–28% of the global population can fulfil their demand for specific crops within a 100-km radius, with substantial variation between different regions and crops. For 26–64% of the population, that distance is greater than 1,000 km. Even if transnational foodsheds were in place, large parts of the globe would still depend on trade to feed themselves. Although yield gap closure and food loss reductions could favour more local food systems, particularly in Africa and Asia, global supply chains would still be needed to ensure an adequate and stable food supply.

Crop production↗

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Madavan, Nateri K.↗

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Madavan, Nateri K.↗

Design for global damage tolerance and associated mass penalties

A structural design with global damage tolerance is defined as a design that can tolerate the destruction of one or more major structural components. The mass penalty associated with improving the global damage tolerance of optimized structures is evaluated herein for structures typically used in aircraft wing construction. It is shown that this mass penalty is strongly related to the degree of redundancy of the structure, being most severe for structures of low redundancy. For highly redundant wing-box structures made of composite materials, it is shown that significant improvement in global damage tolerance may be achieved without any mass penalty.

Haftka, R. T.↗

Optimized Non-Obstructive Particle Damping (NOPD) Treatment for Composite Honeycomb Structures

Non-Obstructive Particle Damping (NOPD) technology is a passive vibration damping approach whereby metallic or non-metallic particles in spherical or irregular shapes, of heavy or light consistency, and even liquid particles are placed inside cavities or attached to structures by an appropriate means at strategic locations, to absorb vibration energy. The objective of the work described herein is the development of a design optimization procedure and discussion of test results for such a NOPD treatment on honeycomb (HC) composite structures, based on finite element modeling (FEM) analyses, optimization and tests. Modeling and predictions were performed and tests were carried out to correlate the test data with the FEM. The optimization procedure consisted of defining a global objective function, using finite difference methods, to determine the optimal values of the design variables through quadratic linear programming. The optimization process was carried out by targeting the highest dynamic displacements of several vibration modes of the structure and finding an optimal treatment configuration that will minimize them. An optimal design was thus derived and laboratory tests were conducted to evaluate its performance under different vibration environments. Three honeycomb composite beams, with Nomex core and aluminum face sheets, empty (untreated), uniformly treated with NOPD, and optimally treated with NOPD, according to the analytically predicted optimal design configuration, were tested in the laboratory. It is shown that the beam with optimal treatment has the lowest response amplitude. Described below are results of modal vibration tests and FEM analyses from predictions of the modal characteristics of honeycomb beams under zero, 50% uniform treatment and an optimal NOPD treatment design configuration and verification with test data.

Panossian, H.↗

Global Sensitivity Analyses for Test Planning with Black-Box Models for Mars Sample Return

This work describes sensitivity analyses performed on complex black-box models used to support experimental test planning under limited resources in the context of the Mars Sample Return program, which aims at bringing to Earth rock and atmospheric samples from Mars. We develop a systematic workflow that allows the analysts to simultaneously obtain quantitative insights on key drivers of uncertainty, on the direction of impact, and the presence of interactions. We apply novel optimal transport-based global sensitivity measures to tackle the multivariate nature of the output. On the modeling side, we apply multi-fidelity techniques that leverage low-fidelity models to speed up the calculations and make up for the limited amount of high-fidelity samples, while keeping these in the loop for accuracy guarantees. The sensitivity analysis reveals insights useful for the analysts to understand the model's behavior and identify the factors to focus on during testing in order to maximize the value of information extracted from them to ensure mission success when limited resources are available.

Giuseppe Cataldo↗

Tropical Ocean and Global Atmosphere (TOGA) heat exchange project: A summary report

A pilot data center to compute ocean atmosphere heat exchange over the tropical ocean is prposed at the Jet Propulsion Laboratory (JPL) in response to the scientific needs of the Tropical Ocean and Global Atmosphere (TOGA) Program. Optimal methods will be used to estimate sea surface temperature (SET), surface wind speed, and humidity from spaceborne observations. A monthly summary of these parameters will be used to compute ocean atmosphere latent heat exchanges. Monthly fields of surface heat flux over tropical oceans will be constructed using estimations of latent heat exchanges and short wave radiation from satellite data. Verification of all satellite data sets with in situ measurements at a few locations will be provided. The data center will be an experimental active archive where the quality and quantity of data required for TOGA flux computation are managed. The center is essential to facilitate the construction of composite data sets from global measurements taken from different sensors on various satellites. It will provide efficient utilization and easy access to the large volume of satellite data available for studies of ocean atmosphere energy exchanges.

Liu, W. T.↗

Designing a Unique Single Point Cross Over Method

The idea behind genetic algorithms is to extract optimization strategies nature uses successfully - known as Darwinian Evolution - and transform them for application in mathematical optimization theory to find the global optimum in a defined phase space. One could imagine a population of individual 'explorers' sent into the optimization phase-space. Each explorer is defined by its genes, what means, its position inside the phase-space is coded in his genes. Every explorer has the duty to find a value of the quality of his position in the phase space. (Consider the phase-space being a number of variables in some technological process, the value of quality of any position in the phase space - in other words: any set of the variables - can be expressed by the yield of the desired chemical product.) Then the struggle of 'life' begins. The three fundamental principles are selection, mating/crossover, and mutation. Only explorers (= genes) sitting on the best places will reproduce and create a new population. This is performed in the second step (mating/crossover). The 'hope' behind this part of the algorithm is, that 'good' sections of two parents will be recombined to yet better fitting children. In fact, many of the created children will not be successful (as in biological evolution), but a few children will indeed fulfill this hope. These good sections are named in some publications as building blocks. Now there appears a problem. Repeating these steps, no new area would be explored. The two former steps would only exploit the already known regions in the phase space, which could lead to premature convergence of the algorithm with the consequence of missing the global optimum by exploiting some local optimum. The third step, mutation, ensures the necessary accidental effects. One can imagine the new population being mixed up a little bit to bring some new information into this set of genes. Whereas in biology a gene is described as a macro-molecule with four different bases to code the genetic information, a gene in genetic algorithms is usually defined as a bitstring (a sequence of b 1's and 0's).

Wilson, Richard Phillip↗

Optimization of a Remote Sensing Energy Balance Method over Different Canopy Applied at Global Scale

Parameterization methods which calculate turbulent heat and water fluxes with thermal remote sensing data were evaluated in the revised remote sensing surface energy balance system (SEBS) model (Chen et al., 2013). The model calculates sensible heat (H) based on the Monin-Obukhov similarity theory (MOST) and determines latent heat (LE) as the residual of energy balance. We examined the uncertainties of H and LE in the SEBS model due to five key parameters at the local station point scale. Observations at 27 flux towers located in seven land cover types (needle-leaf forest, broad leaf forest, shrub, savanna, grassland, cropland, and sparsely vegetated land) and an artificial intelligence particle swarm optimization (PSO) algorithm was combined to calibrate the five parameters (leaf drag coefficient, leaf heat transfer coefficients, roughness length for soil, and two parameters for ground heat calculation) in the SEBS model. The root-mean-square error at the site scale was reduced by 9 W/sq.m for H, and 92 W/sq.m for LE, and their correlation coefficients were increased by 0.07 (H) and 0.11 (LE) after using the calibrated parameters. The updated model validation was further conducted globally for the remotely sensed evapotranspiration (ET) calculations. Overestimation of SEBS global ET was significantly improved by using the optimized values of the parameters. The results suggested PSO was able to consistently locate the global optimum of the SEBS model, and appears to be capable of solving the ET model optimization problem.

Chen, Xuelong↗