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At least 91 records · Page 5

Integration of Low-Fidelity MDO and CFD-Based Redesign of Low-Boom Supersonic Transports

A mixed-fidelity low-boom multidisciplinary optimization (MDO) problem is formulated for integration of low-fidelity MDO and computational fluid dynamics (CFD) based low-boom inverse design optimization. The mixed-fidelity low-boom MDO problem aims to enforce the weight consistency for CFD-based low-boom inverse design optimization: the optimum low-boom configuration is designed for the weight at the start of cruise of the same configuration for the low-boom overland mission. Moreover, it also seeks the optimum trades among the maximum takeoff gross weight (MTOGW), cruise Mach, and range for the low-boom overland mission while meeting the requirement of flying a transatlantic overwater mission. A block coordinate optimization (BCO) method is developed to find an approximate solution of the mixed-fidelity low-boom MDO problem. The BCO method is successfully applied to generate two CFD-based low-boom configurations that closely match two reversed equivalent area targets with ground noise levels below 70 PLdB, respectively. Moreover, these CFD-based low-boom configurations can be obtained with minor wing modifications from the solutions of the low-fidelity MDO problem. The low-fidelity MDO solutions are Pareto points for constrained multiobjective optimization of MTOGW, low-boom cruise Mach, and low-boom range. The best low-boom concept has a predetermined fuselage shape tailored for passengers and main gear storage, carries 40 passengers at seat pitch of 48 in, flies a low-boom overland mission with cruise Mach of 1.8 and range of 2,950 nm, cruises overwater at Mach 1.8 with range of 3,600 nm, satisfies the specified constraints for landing/cruise/takeoff, has MTOGW of 145,164 lb, trims the low-boom cruise flight with fuel redistributions instead of control surface deflections, and has a reversed equivalent area distribution closely matching a target with ground noise level below 70 PLdB.

low-boom supersonic transports

Computational aerodynamic design methodology

The transonic wing design process has been vastly improved at Lockheed-Georgia. The revised design procedure enhances useability and reliability by combining numerical optimization and inverse design into a single wing design code with transonic analysis provided by a modified version of FLO22. A more versatile set of geometric decision variables has been integrated into the optimization portion for geometry perturbations. An automatic restart feature permits the interchangeability of solutions between optimization and inverse design as the design progresses. In combination, these improvements enable practical utilization of a VAX 11/780 computer and significantly reduce the elapsed time required to complete a transonic wing design.

Burris, C. B.

Design and performance of a fixed, nonaccelerating, guide vane cascade that operates over an inlet flow angle range of 60 deg

A unique set of wind tunnel guide vanes are designed with an inverse design code and analyzed with a panel method and an integral boundary layer code developed at the NASA Lewis Research Center. The fixed guide vanes, 80 feet long with 6-foot chord length, were designed for the NASA Ames 40 x 80/80 x 120 ft Wind Tunnel. Low subsonic flow is accepted over a 60 deg range of inlet angle from either the 40 x 80 leg or the 80 x 120 leg of the wind tunnel, and directed axially into the main leg of the tunnel where drive fans are located. Experimental tests of 1/10-scale models were conducted to verify design calculations.

Sanz, J. M.

Design and performance of a fixed, nonaccelerating guide vane cascade that operates over an inlet flow angle range of 60 deg

A unique set of wind tunnel guide vanes are designed with an inverse design code and analyzed with a panel method and an integral boundary layer code developed at the NASA Lewis Research Center. The fixed guide vanes, 80 feet long with 6-foot chord length, were designed for the NASA Ames 40 x 80/80 x 120 ft Wind Tunnel. Low subsonic flow is accepted over a 60 deg range of inlet angle from either the 40 x 80 leg or the 80 x 120 leg of the wind tunnel, and directed axially into the main leg of the tunnel where drive fans are located. Experimental tests of 1/10-scale models were conducted to verify design calculations.

Sanz, J. M.

Hypersonic waverider analysis - A comparison of numerical and experimental results

In this study two waverider configurations are analyzed numerically and experimentally. The geometries are designed using an inverse design and optimization code with the optimization procedure driven by maximized L/D and limited by geometric constraints. Euler and Navier-Stokes numerical simulations are performed with a partially flux-split finite-difference code developed at NASA Ames, F3D. Experimental data is obtained at NASA Langley in the Unitary Plan Wind Tunnel (UPWT) and the 20-Inch Mach 6 wind tunnel for flow visualization, force/moment, and surface pressure measurements at both on- and off-design conditions. Euler simulations are compared with analytic results obtained from conical flow theory, and Navier-Stokes simulations are compared with experimental results both qualitatively and quantitatively for on- and off-design conditions.

Jones, K. D.

Structural control design based on reduced-order observer

An observer-based structural control design method is proposed in this paper. The method is a semi-inverse design procedure in that the control law is not designed before the observer system, but is a result that comes from the observer design. However, the observer design is not completely independent of the control design either, but seeks to yield a control law that is close to a prescribed control law. First, the observer design problem is considered as the reconstruction of a linear function of the state vector. The linear state function to be reconstructed is the given control law. Then, based on the derivation for linear state function observers, the observer design is formulated as a parameter optimization problem. The optimization objective is to generate a matrix that is close to the optimal feedback gain matrix. Based on that matrix, the form of the observer and a new control law can be determined. The semi-inverse design procedure can yield a reduced-order observer with dimension considerably smaller than that of the system. Two examples are used to demonstrate the proposed design procedure.

Su, Tzu-Jeng

Multidisciplinary Design Optimization of Low-Boom Supersonic Aircraft with Mission Constraints

Conceptual design of low-boom supersonic aircraft is heavily dictated by aircraft volume and lift distributions. These unique design characteristics make it a challenge to enforce mission requirements (such as static margins and trim requirements) during design optimization. This low-boom design challenge is resolved by using reversed equivalent area targets for low-fidelity low-boom inverse design and a block coordinate optimization (BCO) method for multidisciplinary design optimization (MDO). The corresponding low-boom MDO problem includes aircraft mission constraints on ranges, cruise speeds, trim for low-boom cruise, static margins for takeoff/cruise/landing, takeoff/landing field lengths, approach velocity, and tail rotation angles for trim at takeoff/landing, as well as fuselage volume constraints for passengers and main gear storage. The BCO method is developed to optimally resolve the conflicts between the low-boom inverse design objective and other design constraints. This method is successfully applied to design a low-boom supersonic configuration that carries 40 passengers, flies a low-boom mission with cruise Mach of 1.6 and range of 2,500 nm, and cruises overwater at Mach 1.8 with range of 3,600 nm. The generated configuration satisfies all specified mission constraints and has the potential to match a reversed equivalent area target with ground noise level below 70 PLdB.

Multidisciplinary design optimization

Viscous Design of TCA Configuration

The goal in this effort is to redesign the baseline TCA configuration for improved performance at both supersonic and transonic cruise. Viscous analyses are conducted with OVERFLOW, a Navier-Stokes code for overset grids, using PEGSUS to compute the interpolations between overset grids. Viscous designs are conducted with OVERDISC, a script which couples OVERFLOW with the Constrained Direct Iterative Surface Curvature (CDISC) inverse design method. The successful execution of any computational fluid dynamics (CFD) based aerodynamic design method for complex configurations requires an efficient method for regenerating the computational grids to account for modifications to the configuration shape. The first section of this presentation deals with the automated regridding procedure used to generate overset grids for the fuselage/wing/diverter/nacelle configurations analysed in this effort. The second section outlines the procedures utilized to conduct OVERDISC inverse designs. The third section briefly covers the work conducted by Dick Campbell, in which a dual-point design at Mach 2.4 and 0.9 was attempted using OVERDISC; the initial configuration from which this design effort was started is an early version of the optimized shape for the TCA configuration developed by the Boeing Commercial Airplane Group (BCAG), which eventually evolved into the NCV design. The final section presents results from application of the Natural Flow Wing design philosophy to the TCA configuration.

Krist, Steven E.

An inverse problem design method for branched and unbranched axially symmetrical ducts

This paper concerns the potential flow design of axially symmetrical ducts of both circular and annular cross section with or without wall suction or blowing slots. The objective of the work was to develop a method by which such ducts could be designed with directly prescribed wall pressure variation. Previous axially symmetrical design methods applied only to circular cross sectional ducts and required that the pressure distribution be prescribed along the duct centerline and not along the duct wall. The present method uses an inverse problem approach which extends the method of Stanitz to the axially symmetrical case, and an approximation is used to account for the stagnation point in branched duct designs. Two examples of successful designs of diffusers with suction slots are presented.

Nelson, C. D.

Aerodynamic Design Study of Advanced Multistage Axial Compressor

As a direct response to the need for further performance gains from current multistage axial compressors, an investigation of advanced aerodynamic design concepts that will lead to compact, high-efficiency, and wide-operability configurations is being pursued. Part I of this report describes the projected level of technical advancement relative to the state of the art and quantifies it in terms of basic aerodynamic technology elements of current design systems. A rational enhancement of these elements is shown to lead to a substantial expansion of the design and operability space. Aerodynamic design considerations for a four-stage core compressor intended to serve as a vehicle to develop, integrate, and demonstrate aerotechnology advancements are discussed. This design is biased toward high efficiency at high loading. Three-dimensional blading and spanwise tailoring of vector diagrams guided by computational fluid dynamics (CFD) are used to manage the aerodynamics of the high-loaded endwall regions. Certain deleterious flow features, such as leakage-vortex-dominated endwall flow and strong shock-boundary-layer interactions, were identified and targeted for improvement. However, the preliminary results were encouraging and the front two stages were extracted for further aerodynamic trimming using a three-dimensional inverse design method described in part II of this report. The benefits of the inverse design method are illustrated by developing an appropriate pressure-loading strategy for transonic blading and applying it to reblade the rotors in the front two stages of the four-stage configuration. Multistage CFD simulations based on the average passage formulation indicated an overall efficiency potential far exceeding current practice for the front two stages. Results of the CFD simulation at the aerodynamic design point are interrogated to identify areas requiring additional development. In spite of the significantly higher aerodynamic loadings, advanced CFD-based tools were able to effectively guide the design of a very efficient axial compressor under state-of-the-art aeromechanical constraints.

Larosiliere, Louis M.

Robust Conceptual Design of Transonic Airfoils

This paper describes an integrated, multi-fidelity analysis and heuristic design approach that can be used to derive initial airfoil designs for transonic flight. If successful, the final result is a geometry that can be expected to produce reasonable aerodynamic performance when used with higher order analysis methods. A key aspect of the methodology is the use of a “sonic-plateau” pressure distribution as the target distribution for inverse design. The sonic- plateau distribution is easily parameterized and has the advantage of automatically resulting in a smooth airfoil shape without any discontinuities built into the surface due to the presence of a shock in the target pressure distribution. Inverse design is performed on each airfoil using a parametrically defined pressure distribution at a reduced lift coefficient and Mach number from the design condition. The methodology is demonstrated by designing an airfoil at 38% of the wing semispan for a 737-200-like aircraft. The demonstration problem shows that the methodology is able to achieve rapid and robust convergence to the solution. The calculated designed airfoil was found to be sufficiently higher than Mach number, and the maximum thickness was close to the targeted value.

Olson, Erik D.

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE

Design of Materials with Alchemite

Machine learning models that establish the relationships between materials processing and properties can enable inverse design of materials through active learning. Alchemite is a commercial software that can perform inverse materials design on sparse data. Here we evaluate Alchemite’s performance on a dataset of shape memory alloys and a dataset of heat exchangers compared to baseline random forest models. Alchemite had higher accuracy when making predictions on sparse data and was more accurate or nearly as accurate as random forests on complete datasets while also quantifying uncertainty. The software was also used to suggest processing steps and design parameters to optimize properties and performance; however, physical validation of the suggested design parameters was beyond the scope of this work. Several useful design insights were gained about the impact of the design parameters on properties and performance including the importance of dopant choice and amount for shape memory alloys and the importance of height and weight on the thermal resistance of heat exchangers.

Machine learning

Transonic airfoil analysis and design in nonuniform flow

A nonuniform transonic airfoil code is developed for applications in analysis, inverse design and direct optimization involving an airfoil immersed in propfan slipstream. Problems concerning the numerical stability, convergence, divergence and solution oscillations are discussed. The code is validated by comparing with some known results in incompressible flow. A parametric investigation indicates that the airfoil lift-drag ratio can be increased by decreasing the thickness ratio. A better performance can be achieved if the airfoil is located below the slipstream center. Airfoil characteristics designed by the inverse method and a direct optimization are compared. The airfoil designed with the method of direct optimization exhibits better characteristics and achieves a gain of 22 percent in lift-drag ratio with a reduction of 4 percent in thickness.

Chang, J. F.

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.