Multidisciplinary Design Optimization of an Aircraft Considering Path-Dependent Performance

Aircraft are multidisciplinary systems that are challenging to design due to interactions between the subsystems. The relevant disciplines, such as aerodynamic, thermal, and propulsion systems, must be considered simultaneously using a path-dependent formulation to accurately assess aircraft performance. The overarching contribution of this work is the construction and exploration of a coupled aero-thermal-propulsive-mission multidisciplinary model to optimize supersonic aircraft considering their path-dependent performance. First, the mission, thermal, and propulsion disciplines are examined in detail. The aerostructural design and mission of a morphing-wing aircraft is optimized before the optimal flight profile for a supersonic strike mission is investigated. Then a fuel thermal management system, commonly used to dissipate excess thermal energy from supersonic aircraft, is constructed and presented. Engine design is then investigated through two main applications: multipoint optimization of a variable-cycle engine and coupled thermal-engine optimization considering a bypass duct heat exchanger. This culminates into a fully-coupled path-dependent mission optimization problem considering the aerodynamic, propulsion, and thermal systems. This large-scale optimization problem captures non-intuitive design trades that single disciplinary models and path-independent methods cannot resolve. Although the focal application is a supersonic aircraft, the methods presented here are applicable to any air or space vehicle and other path-dependent problems. This level of highly-coupled design optimization considering these disciplines has not been performed before. The framework, modeling, and results from this dissertation will be useful for designers of commercial and military aircraft. Specifically, optimizing the design and trajectory of commercial aircraft to minimize fuel usage leads to a more sustainable and more connected world as the rate of air travel continues to increase. The methods presented are flexible and powerful enough to design supersonic military aircraft systems, as demonstrated using an application aircraft. This dissertation has been shaped through direct collaborations with NASA, the Air Force Research Lab (AFRL), and other academic institutions, which shows the broad appeal and applicability of this work to a multitude of design problems.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155269/1/johnjasa_1.pd

Component-based Geometry Manipulation for Aerodynamic Shape Optimization with Overset Meshes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143082/1/6.2017-3327.pd

How Certain Physical Considerations Impact Aerostructural Wing Optimization

Wing design optimization has been studied extensively and is of continued interest as optimization tools are developed and become more accessible. In each of these studies, certain assumptions and simplifications are made to make the design problem tractable. However, it is difficult to find systematic studies in which several considerations are added or removed one at a time to study how much impact they have. In this work, we examine how certain physical considerations (viscous drag, wave drag, thrust loads, and inertial relief from structural, fuel, and engine masses), impact the aerostructural optimization results for three distinct aircraft wings. The goal is to help develop a rough idea of how important these physical considerations are. We do this using gradient-based optimization and a multidisciplinary design optimization framework, OpenMDAO. We use the open-source tool OpenAeroStruct that couples a vortex lattice method to a finite element method. We establish a baseline aerostructural design optimization problem then perform a series of optimizations, each with one physical consideration removed from the baseline case. We find that depending on the size of the aircraft and flight conditions, the importance of some of these physical considerations varies considerably whereas the importance of others do not. Specifically, the optimal designs change radically without proper viscous and wave drag considerations and smaller aircraft with more distributed propulsion are more affected by the inclusion of engine loads

Multifidelity optimization under uncertainty for a tailless aircraft

This paper presents a multifidelity method for optimization under uncertainty for aerospace problems. In this work, the effectiveness of the method is demonstrated for the robust optimization of a tailless aircraft that is based on the Boeing Insitu ScanEagle. Aircraft design is often affected by uncertainties in manufacturing and operating conditions. Accounting for uncertainties during optimization ensures a robust design that is more likely to meet performance requirements. Designing robust systems can be computationally prohibitive due to the numerous evaluations of expensive-to-evaluate high-fidelity numerical models required to estimate system-level statistics at each optimization iteration. This work uses a multifidelity Monte Carlo approach to estimate the mean and the variance of the system outputs for robust optimization. The method uses control variates to exploit multiple fidelities and optimally allocates resources to different fidelities to minimize the variance in the estimates for a given budget. The results for the ScanEagle application show that the proposed multifidelity method achieves substantial speed-ups as compared to a regular Monte-Carlo-based robust optimization.United States. Air Force. Office of Scientific Research. Multidisciplinary University Research Initiative (FA9550-15-1-0038

G95-1132 Estimating Percent Residue Cover

This NebGuide briefly describes the direct observation, line-transect, photo comparison, and calculation methods that are used to estimate the percentage of the soil surface covered with crop residue. Leaving crop residue on the soil surface is the easiest and most cost-effective way to reduce soil erosion caused by water and wind. Residue reduces water erosion by lessening the impact of the raindrops, thus reducing the amount of soil that is detached. It also slows flowing water, reducing the amount of soil that can be transported. Residue helps reduce wind erosion by reducing wind velocity near the soil surface and by trapping soil particles carried by the wind. Many conservation plans that were developed to meet conservation compliance provisions of the 1985 Food Security Act and the 1990 Food, Agriculture, Conservation, and Trade Act (Farm Bills) specify crop residue management as the primary method for erosion control. Four methods direct observation, line-transect, photo-comparison, and calculation are frequently used to estimate percent residue cover

G88-876 Ridge Plant Systems: Equipment

Ridge plant systems, ridge cleaning equipment, planter stabilizing attachments, cultivation and ridge management are discussed here. Ridge plant systems are methods of planting crops into a ridge formed during cultivation of the previous crop. Such systems combine tillage and herbicides to control weeds. Weed seed and residue lying on the soil surface are pushed from the ridge to the area between the rows by row-cleaning devices on the planter. Crop seed is planted into the old row in a cleanly tilled strip at an elevation slightly higher than the row middles. A band application of herbicide behind the planter typically is used in the row for weed control. Crop cultivation controls weeds between the rows and rebuilds ridges for the following year

A Comparison of Eight Optimization Methods Applied to a Wind Farm Layout Optimization Problem

Selecting a wind farm layout optimization method is difficult. Comparisons between optimization methods in different papers can be uncertain due to the difficulty of exactly reproducing the objective function. Comparisons by just a few authors in one paper can be uncertain if the authors do not have experience using each algorithm. In this work we provide an algorithm comparison for a wind farm layout optimization case study between eight optimization methods applied, or directed, by researchers who developed those algorithms or who had other experience using them. We provided the objective function to each researcher to avoid ambiguity about relative performance due to a difference in objective function. While these comparisons are not perfect, we try to treat each algorithm more fairly by having researchers with experience using each algorithm apply each algorithm and by having a common objective function provided for analysis. The case study is from the IEA Wind Task 37, based on the Borssele III and IV wind farms with 81 turbines. Of particular interest in this case study is the presence of disconnected boundary regions and concave boundary features. The optimization methods studied represent a wide range of approaches, including gradient-free, gradient-based, and hybrid methods; discrete and continuous problem formulations; single-run and multi-start approaches; and mathematical and heuristic algorithms. We provide descriptions and references (where applicable) for each optimization method as well as lists of pros and cons to help readers determine an appropriate method for their use case. All the optimization methods perform similarly, with optimized wake loss values between 15.48 % and 15.70 % as compared to 17.28 % for the unoptimized provided layout. Each of the layouts found were different, but all layouts exhibited similar characteristics. Strong similarities across all the layouts include tightly packing wind turbines along the outer borders, loosely spacing turbines in the internal regions, and allocating similar numbers of turbines to each discrete boundary region. The best layout by AEP was found using a new sequential allocation method, discreet exploration-based optimization (DEBO). Based on the results in this study, it appears that using an optimization algorithm can significantly improve wind farm performance, but there are many optimization methods that can perform well on the wind farm layout optimization problem given that they are applied correctly.</p

Multidisciplinary Design Optimization Framework with Coupled Derivative Computation for Hybrid Aircraft

Hybrid-electric aircraft are a potential way to reduce the environmental footprint of aviation. Research aimed at this subject has been pursued over the last decade; nevertheless, at this stage, a full overall aircraft design procedure is still an open issue. This work proposes to enrich the procedure for the conceptual design of hybrid aircraft found in literature through the definition of a multidisciplinary design optimization (MDO) framework aimed at handling design problems for such kinds of aircraft. The MDO technique has been chosen because the hybrid aircraft design problem shows more interaction between disciplines than a conventional configuration, and the classical approach based on multidisciplinary design analysis may neglect relevant features. The procedure has been tested on the case study of a single-aisle aircraft featuring hybrid propulsion with distributed electric ducted fans. The analysis considers three configurations (with 16, 32, and 48 electric motors) compared with a conventional baseline at the same 2035 technological horizon. To demonstrate the framework’s capability, these configurations are optimized with respect to fuel and energy consumption. It is shown that the hybrid-electric concept consumes less fuel/energy when it flies on short range due to the partial mission electrification. When one increases the design range, penalties in weight introduced by hybrid propulsion overcome the advantages of electrified mission segment: the range for which hybrid aircraft have the same performance of the reference conventional aircraft is named the “breakdown range.” Starting from this range, the concept is no longer advantageous compared to conventional aircraft. Furthermore, a tradeoff between aerodynamic and propulsive efficiency is detected, and the optimal configuration is the one that balances these two effects. Finally, multiobjective optimization is performed to establish a tradeoff between airframe weight and energy consumption

Software for Extracting Deformation Gradient and Stress from MD Simulations: Simulations using the CHARMM Force Field

Software was developed, and is provided under a general use license, to calculate continuum level deformation gradient and stress for any group of atoms in an MD simulation that uses the Charmm force fields. This software can also calculate the interaction stress applied by one group of atoms on any other group. To obtain deformation gradient and stress, the user needs to provide the selected group(s) of atoms in an atom group identification file, and provide the associated LAMMPS format files and force field parameter file. An example is included to demonstrate the use of the software

Extracting continuum-like deformation and stress from molecular dynamics simulations

We present methods that use results from molecular dynamics (MD) simulations to construct continuum parameters, such as deformation gradient and Cauchy stress, from all or any part of an MD system. These parameters are based on the idea of minimizing the difference between MD measures for deformation and traction and their continuum counterparts. The procedures should be applicable to non-equilibrium and inhomogeneous systems, and to any part of a system, such as a polymer chain. The resulting procedures provide methods to obtain first and higher order deformation gradients associated with any subset of the MD system, and associated expressions for the Cauchy and nominal stresses. As these procedures are independent of the type of interactions, they can be used to study any MD simulation in a manner consistent with continuum mechanics and to extract information exploitable at the continuum scale to help construct continuum-level constitutive models