Engineering topics

Martins, Joaquim R. R. A.

Publications and source records attributed to Martins, Joaquim R. R. A..

9 records

DOE OSTI2023

CFD-based design optimization of ducted hydrokinetic turbines

Abstract Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines.

13 HYDRO ENERGY↗

DOE OSTI2022

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_v$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

42 ENGINEERING↗

NASA NTRS2019

Multipoint Variable Cycle Engine Design Using Gradient-based Optimization

Supersonic aircraft are challenging to optimally design due to the widely varying constraints and flight conditions they experience. Additionally, a large number of disciplinary subsystems must be considered due to highly complex design requirements. One subsystem that has a major effect on overall performance is the engine. In this work, we construct a supersonic mixed-flow variable cycle engine and perform multipoint gradient-based optimization using this model. We see that the operational variables allow the optimizer to tailor performance at each individual flight condition, leading to better overall performance. To simulate airframe integration constraints, we run successive optimizations with increasingly restrictive inlet areas and see decreases in engine performance. This work is part of a larger effort to incorporate engine design into aero-thermal-mission optimization of a supersonic aircraft.

Cycle analysis↗

NASA NTRS2018

Aeropropulsive Design Optimization of a Turboelectric Boundary Layer Ingestion Propulsion System

Boundary Layer Ingestion (BLI) for aircraft applications was first proposed by Apollo Smith and Howard Roberts in a 1947 paper that studied the use of jet intakes embedded in the boundary layer as a means to maintain laminar flow and reduce aircraft drag. While the use of BLI in aviation didn't catch on it was heavily studied and utilized for marine applications. In 1993 interest in BLI applications to aircraft design was renewed when Leyroy Smith published novel work using a boundary layer analysis combined with basic propulsion modeling to show the potential for significant fuel burn reduction. Smith identified the tightly coupled aero-propulsive nature of BLI as a key challenge in the analysis and design of the concept.

Gray, Justin S.↗

NASA NTRS2018

Next Generation Aircraft Design Considering Airline Operations and Economics

Traditional approaches to design and optimization of a new system often use a system-centric objective and do not take into consideration how the operator will use this new system alongside other existing systems. When the new system design is incorporated into the broader group of systems, the performance of the operator-level objective can be sub-optimal due to the unmodeled interaction between the new system and the other systems. Among the few available references that describe attempts to address this disconnect, most follow an MDO (Multidisciplinary Design Optimization)-motivated sequential decomposition approach of first designing a very good system and then providing this system to the operator who, decides the best way to use this new system along with the existing systems. This paper addresses this issue by including aircraft design, airline operations, and revenue management "subspaces"; and presents an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem rather than the traditional approach described above. The monolithic approach makes the problem an expensive Mixed Integer Non-Linear Programming problem, which are extremely difficult to solve. To address the problem, we use a recently developed optimization framework that simultaneously solves the subspaces to capture the "synergy" in the problem that the previous decomposition approaches did not exploit, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. This approach solves an 11-route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. Simultaneously solving the subspaces leads to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach.

Roy, Satadru↗

NASA NTRS2017

High-Fidelity Multidisciplinary Design Optimization of Aircraft Configurations

To evaluate new airframe technologies we need design tools based on high-fidelity models that consider multidisciplinary interactions early in the design process. The overarching goal of this NRA is to develop tools that enable high-fidelity multidisciplinary design optimization of aircraft configurations, and to apply these tools to the design of high aspect ratio flexible wings. We develop a geometry engine that is capable of quickly generating conventional and unconventional aircraft configurations including the internal structure. This geometry engine features adjoint derivative computation for efficient gradient-based optimization. We also added overset capability to a computational fluid dynamics solver, complete with an adjoint implementation and semiautomatic mesh generation. We also developed an approach to constraining buffet and started the development of an approach for constraining utter. On the applications side, we developed a new common high-fidelity model for aeroelastic studies of high aspect ratio wings. We performed optimal design trade-o s between fuel burn and aircraft weight for metal, conventional composite, and carbon nanotube composite wings. We also assessed a continuous morphing trailing edge technology applied to high aspect ratio wings. This research resulted in the publication of 26 manuscripts so far, and the developed methodologies were used in two other NRAs. 1

Martins, Joaquim R. R. A.↗

NASA NTRS2017

Approach to Modeling Boundary Layer Ingestion Using a Fully Coupled Propulsion-RANS Model

Although boundary layer ingestion (BLI), or wake ingestion, is commonly applied in marine propulsion applications, it has not yet seen wide-spread adoption in aircraft applications. However, recent studies have predicted that BLI offers a potential for a 10 reduction in aircraft fuel burn, even on a fairly traditional aircraft configuration. This dramatic reduction in fuel burn is achieved via tight integration of the propulsion system and airframe aerodynamics, but actually realizing such large performance gains will require modifying the aircraft design process to account for this integration. Traditionally, in aircraft design, the airframe and the propulsion system are designed separately and then the engine sizing is managed with a rubber-engine approach. This works when the propulsion system is placed in the free-stream air, away from the aerodynamic influence of the airframe, and it is reasonable to assume that small changes to either system won't have a strong impact on the other.

propulsion↗

NASA NTRS2017

Approach to Modeling Boundary Layer Ingestion Using a Fully Coupled Propulsion-RANS Model

Airframe-propulsion integration concepts that use boundary layer ingestion have the potential to reduce aircraft fuel burn. One concept that has been recently explored is NASA's Starc-ABL aircraft configuration, which offers the potential for 12% mission fuel burn reduction by using a turbo-electric propulsion system with an aft-mounted electrically driven boundary layer ingestion propulsor. This large potential for improved performance motivates a more detailed study of the boundary layer ingestion propulsor design, but to date, analyses of boundary layer ingestion have used uncoupled methods. These methods account for only aerodynamic effects on the propulsion system or propulsion system effects on the aerodynamics, but not both simultaneously. This work presents a new approach for building fully coupled propulsive-aerodynamic models of boundary layer ingestion propulsion systems. A 1D thermodynamic cycle analysis is coupled to a RANS simulation to model the Starc-ABL aft propulsor at a cruise condition and the effects variation in propulsor design on performance are examined. The results indicates that both propulsion and aerodynamic effects contribute equally toward the overall performance and that the fully coupled model yields substantially different results compared to uncoupled. The most significant finding is that boundary layer ingestion, while offering substantial fuel burn savings, introduces throttle dependent aerodynamics effects that need to be accounted for. This work represents a first step toward the multidisciplinary design optimization of boundary layer ingestion propulsion systems.

Boundary Layer Ingestion↗

NASA NTRS2016

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

Propulsion↗