Ferritic-martensitic steels, such as T91, are candidate materials for high-temperature applications, including superheaters, heat exchangers, and advanced nuclear reactors. Considering these alloys’ wide applications, an atomistic understanding of the underlying mechanisms responsible for their excellent mechano-chemical properties is crucial. Here, we developed a modified embedded-atom method (MEAM) potential for the Fe-Cr-Si-Mo quaternary alloy system—i.e., four major elements of T91—using a multi-objective optimization approach to fit thermomechanical properties reported using density functional theory (DFT) calculations and experimental measurements. Elastic constants calculated using the proposed potential for binary interactions agreed well with ab initio calculations. Furthermore, the computed thermal expansion and self-diffusion coefficients employing this potential are in good agreement with other studies. This potential will offer insightful atomistic knowledge to design alloys for use in harsh environments.
more »
« less
Bayesian optimization with active learning of design constraints using an entropy-based approach
The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and constraints. Candidate alloys must be ductile at room temperature and retain their yield strength at high temperatures, as well as possess low density, high thermal conductivity, narrow solidification range, high solidus temperature, and a small linear thermal expansion coefficient. Traditional Integrated Computational Materials Engineering (ICME) methods are not sufficient for exploring combinatorially-vast alloy design spaces, optimizing for multiple objectives, nor ensuring that multiple constraints are met. In this work, we propose an approach for solving a constrained multi-objective materials design problem over a large composition space, specifically focusing on the Mo-Nb-Ti-V-W system as a representative Multi-Principal Element Alloy (MPEA) for potential use in next-generation gas turbine blades. Our approach is able to learn and adapt to unknown constraints in the design space, making decisions about the best course of action at each stage of the process. As a result, we identify 21 Pareto-optimal alloys that satisfy all constraints. Our proposed framework is significantly more efficient and faster than a brute force approach.
more » « less- PAR ID:
- 10404996
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- npj Computational Materials
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2057-3960
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Alloying is a common technique to optimize the functional properties of materials for thermoelectrics, photovoltaics, energy storage etc. Designing thermoelectric (TE) alloys is especially challenging because it is a multi-property optimization problem, where the properties that contribute to high TE performance are interdependent. In this work, we develop a computational framework that combines first-principles calculations with alloy and point defect modeling to identify alloy compositions that optimize the electronic, thermal, and defect properties. We apply this framework to design n-type Ba 2(1− x ) Sr 2 x CdP 2 Zintl thermoelectric alloys. Our predictions of the crystallographic properties such as lattice parameters and site disorder are validated with experiments. To optimize the conduction band electronic structure, we perform band unfolding to sketch the effective band structures of alloys and find a range of compositions that facilitate band convergence and minimize alloy scattering of electrons. We assess the n-type dopability of the alloys by extending the standard approach for computing point defect energetics in ordered structures. Through the application of this framework, we identify an optimal alloy composition range with the desired electronic and thermal transport properties, and n-type dopability. Such a computational framework can also be used to design alloys for other functional applications beyond TE.more » « less
-
more » « less
Abstract This paper proposes a linear parameter varying (LPV) control design for a Clipper Liberty C96 2.5 MW wind turbine to operate in all wind conditions. A standard approach is to use multiple single‐input, single‐output loops for control objectives at different wind speeds. This LPV controller instead takes these objectives into a uniformed multi‐input, multi‐output design framework. The key difference is that the LPV controller is specifically designed to smoothly transition from Region 2 to Region 3 operation. Reducing structural loads is another major concern in the design. Synthesis of the controller relies on a gridded‐based LPV model of the turbine, which is constructed by interpolation of linearized turbine models at different wind speeds. To overcome the conservativeness in the design, parameter varying rates will be considered based on turbulent wind conditions. The performance of the LPV controller is evaluated using a high fidelity FAST model provided by Clipper. The LPV controller is directly compared with the baseline controller currently operating on the turbine. Simulations and analysis show that the LPV controller meets all performance objectives and has better load reduction performance.
-
null (Ed.)The cluster expansion formalism for alloys is used to construct surrogate models for three refractory high-entropy alloys (NbTiVZr, HfNbTaTiZr, and AlHfNbTaTiZr). These cluster expansion models are then used along with Monte Carlo methods and thermodynamic integration to calculate the configurational entropy of these refractory high-entropy alloys as a function of temperature. Many solid solution alloy design guidelines are based on the ideal entropy of mixing, which increases monotonically with N, the number of elements in the alloy. However, our results show that at low temperatures, the configurational entropy of these materials is largely independent of N, and the assumption described above only holds in the high-temperature limit. This suggests that alloy design guidelines based on the ideal entropy of mixing require further examination.more » « less
-
The production of wind energy worldwide has increased 20-fold since 2001. Composite material wind turbine blades, typically designed for a 20-year fatigue life, are beginning to come out of service in large numbers. In general, these de-commission blades, composed primarily of glass fibers in a thermoset matrix, are demolished and landfilled. There is little motivation for recycling the composite materials, as the processes for reclaiming the fibers (solvolysis, pyrolysis) have not been proven to be economically viable. This research seeks to establish structural re-use applications for wind turbine blades in civil engineering infrastructure, hypothesizing that advanced composite materials may be an attractive alternative to conventional infrastructure materials (e.g. steel, reinforced concrete). This paper presents an analysis and materials characterization of a 47 meter Clipper C96 wind blade. The primarily numerical analysis is accompanied by materials characterization taken from an un-used Clipper blade donated to the project from the Wind Turbine Testing Center (WTTC). The paper presents a brief background on wind turbine blade adaptive re-use, proposing a hypothetical load bearing application of the Clipper wind blade as an electrical transmission tower structure carrying axial compression, along with flapwise and edgewise bending forces. The paper summarizes the composite laminates and cross-section geometries of the blade and establishes the axial and flexural stiffnesses of the blade at multiple sections along the blade length. From a first-order estimation of applied loads for the tower application, the resulting stresses in the composite materials are estimated and compared to the design material properties for the wind blade as originally constructed.more » « less
