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Computational Tools to Enable Development of Alloys and Coatings for Advanced Gas Turbine Engines

Description:

 
 

TECHNOLOGY AREA(S): Battlespace, Ground/Sea Vehicles, Materials/Processes

ACQUISITION PROGRAM: FNC EPE FY15-02 Gas Turbine Developments for Reduced Total Ownership Cost, Improved Ship Impact

OBJECTIVE: To develop a suite of computational tools that will accelerate the creation and development of alloys and coatings for gas turbine engines. The computational, informatics-based suite should be capable of utilizing various material database formats, and be able to convert and integrate modeling and simulation tools with experimental data and existing materials databases to provide the foundation for optimal materials design and development.

DESCRIPTION: Current state of the art software tools and associated infrastructure presently available do not address the data heterogeneity and fragmentation challenges in a way conducive to the feasible development and maintenance of high-quality databases of commercial alloys or coating reaching 12-15 components. This gap comprises a significant scientific and economic opportunity to enhance the ability of scientists and engineers to solve challenges in developing new engineering alloys and coatings. The quality of materials databases is uneven in the literature and requires labor and time to investigate and determine what constitutes viable materials data sources. As an example, the data required as inputs to Calculation of Phase Diagrams (CALPHAD) models are highly fragmented across numerous literature and non-literature sources. There is an urgent need for creating and developing specialized informatic tools for data capture, management, analysis, and dissemination. Advances in computer power created in recent years, coupled with computer modeling and simulation, and materials properties databases will enable accelerated creation and development of new materials. Using these informatic tools as sources will facilitate Integrated Computational Materials (Science and Engineering) (ICMSE/ICME)) to reliably predict the composition and behavior of new materials. This proposed SBIR effort seeks the development of tools that will allow usage of various open and closed materials data sources to create useful thermodynamic and kinetic data formats with computational methodologies for creating and developing propulsion materials.

PHASE I: Identify a material (alloy or coating), material system, or material process that will produce a viable component for a marine gas turbine engine. Identify the boundary conditions to which the material, material system, or materials process must conform such as chemical composition, corrosion and/or oxidation resistance, fatigue, interdiffusion resistance, creep, resistance to phase transitions, coefficient of thermal expansion compatibility durability, stress, temperature stability, etc. The small business needs to assemble and assess a suite of modeling tools to predict processing outcomes and desirable materials properties. The modeling tools should have a history that the modeling results represent real-world conditions and provide an accurate mathematical representation of the engineering principles and relationships and predict the materials behavior that they were designed to represent. The small business needs to create an informatics-based framework that will be able to assess the type and quality of the databases required by ICME and other computational programs that can also work with materials modeling and simulation tools. The small business needs to demonstrate the functionality of this framework on a limited scale.

PHASE II: Using the outline of a framework created in Phase I, the informatics –based program needs to be expanded to determine the quality of different database sources. The program(s) should be able to identify errors in databases such as data entry errors, measurements errors, distillation errors, and data integration errors. Models should be developed to summarize general trends and complexity in data using e.g. linear regression, logistic regression focus on attribute relationships, identify data points that do not conform to well-fitting models as potential outliers, perform goodness of fit tests (DQ for analysis/mining), and check suitableness of model to data, verify validity of assumptions, and determine if the database is rich enough to provide the necessary inputs to the materials computational models. The small business should have a "good" baseline database so that the discriminating program can detect potentially corrupt sections in the test data set of other databases. The discriminating database program should be able to perform nonparametric statistical tests for a rapid section-wise comparison of two or more massive data sets, and repair errors in databases. The program should provide a means for capturing, sharing, and transforming materials data into a structured format that is amenable to transformation to other formats for use by ICME and other computational programs and modeling and simulation methods. The data can be searched and retrieved via several means.

PHASE III DUAL USE APPLICATIONS: The small business should engage with a government, public, commercial, company, or professional technical society that retains materials databases. The small business should demonstrate the means for capturing, sharing, and transforming materials data into a structured format that is amenable to transformation to other formats and the range of sources of materials databases it can use as inputs to materials computational tools that are used to describe various materials properties. The results should be compared to a previously verified "good" materials database. The small business also needs to interface with a software company that promotes and delivers materials computational programs to explore and develop an integration pathway for the database discriminating program with their software. The outcome of this technology development program will be a commercial suite of informatics-derived tools that can will be able to reliably analyze and discriminate various sources of materials databases to optimize the capability of ICME, other computational techniques, and modeling and simulation tools to work together to accelerate materials design and development for DoD ever-increasing material demands. Private Sector Commercial Potential: ICME and other computational programs are oriented toward reducing the time and cost of developing a material, a coating, or a materials system or manufacturing process in order to support the development of advanced products. But the military and the commercial world need to develop new informatics-based tools that will reliably discriminate various materials and properties databases so that these computational tools do not lead to flawed materials design. These informatics tools will help mitigate the time and cost to assess database quality manually. The tools developed in the research will expand and automate the determination of database quality so that integrated computational materials science and engineering tools provide more consistent results for public (Military) and private commercial use.

REFERENCES:

  • S.M. Arnold and T.t. Wong, editors, "Models, Databases, and Simulation Tools Needed for the Realization of Integrated Computational Materials Engineering", ASM International, Materials Park, OH (2010).
  • C.J. Kuehmann and G.B. Olson, "Computational Materials Design and Engineering", Materials Science and Technology, 25, 7 (2009).
  • B. Cowles, D. Backman, and R. Dutton, "Verification and Validation of ICME Methods and Models for Aerospace Applications", Integrating Materials and Manufacturing Innovation, 1, 16 (2012).
  • D. Furrer and J.Schirra, "The Development of the ICME Supply-Chain Route to ICME Implementation and Sustainment," JOM, 63(4) pp. 42-48 (2011).

KEYWORDS: ICME, materials database, materials development, data processing, regression analysis, modeling, infomatics

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