Pfeiffer et al., 2014 - Google Patents
Aircraft configuration analysis using a low-fidelity, physics based aerospace framework under uncertainty considerationsPfeiffer et al., 2014
View PDF- Document ID
- 3569742319432620018
- Author
- Pfeiffer T
- Moerland E
- Böhnke D
- Nagel B
- Gollnick V
- Publication year
External Links
Snippet
During the early stages of aircraft design, limited information is available to conduct decisions that base on the quality of aircraft configurations. In the present study, information on physical and statistical models is supplemented by the uncertainty that is inherent to the …
- 238000004458 analytical method 0 title abstract description 66
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
- G06F17/5018—Computer-aided design using simulation using finite difference methods or finite element methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
- G06F17/5022—Logic simulation, e.g. for logic circuit operation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5045—Circuit design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5086—Mechanical design, e.g. parametric or variational design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2705—Parsing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/46—Fuselage
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/80—Thermal analysis and optimization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/16—Numerical modeling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/02—Component-based CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/34—Graphical or visual programming
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3457—Performance evaluation by simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lefebvre et al. | Methodological enhancements in MDO process investigated in the AGILE European project | |
| Gu et al. | An automated CFD analysis workflow in overall aircraft design applications | |
| KR101612506B1 (en) | System and method for Aircraft areodynamic analysis using CFD | |
| Trifari et al. | Multi-disciplinary analysis and optimization Java tool for aircraft design | |
| Pfeiffer et al. | Aircraft configuration analysis using a low-fidelity, physics based aerospace framework under uncertainty considerations | |
| Swaminathan et al. | Integrating mbse and mdo through an extended requirements-functional-logical-physical (rflp) framework | |
| Taylor et al. | A Process for Identifying Requirements for Physical Referent Data to Support Computational Model Validation | |
| Panzeri et al. | Uncertainty quantification and robust design optimization applied to aircraft propulsion systems | |
| Ciampa et al. | Aeroelastic design and optimization of unconventional aircraft configurations in a distributed design environment | |
| Fazal et al. | Integration of uncertainty quantification in a model-based systems analysis and engineering framework | |
| Du et al. | Aircraft design optimization with uncertainty based on fuzzy clustering analysis | |
| Ciampa et al. | Preliminary design for flexible aircraft in a collaborative environment | |
| Phillips et al. | Design Under Uncertainty for Conceptual Aircraft Design Leveraging Analytical Gradients | |
| Zill et al. | Preliminary aircraft design in a collaborative multidisciplinary design environment | |
| Di Bianchi et al. | A framework for enhanced decision-making in aircraft conceptual design optimisation under uncertainty | |
| Daoud | Aeroelastic shape and sizing optimization of aircraft products supported by AGILE design paradigm | |
| Dewez et al. | From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning | |
| Cooke et al. | Sculpting: A fast, interactive method for probabilistic design space exploration and margin allocation | |
| Lefebvre et al. | Overview of MDO enhancement in the AGILE project: a clustered and surrogate-based MDA use case | |
| Foti et al. | Subgrid-scale characterization and asymptotic behavior of multidimensional upwind schemes for the vorticity transport equations | |
| Roshanian et al. | Metamodel-based multidisciplinary design optimization of a general aviation aircraft | |
| Anusonti-Inthra et al. | Development of Multi-Fidelity Surrogate Models for Rotor Performance Prediction | |
| Economon et al. | Design and optimization of future aircraft for assessing the fuel burn trends of commercial aviation | |
| Pfeiffer et al. | Implementation of a heterogeneous, variable-fidelity framework for flight mechanics analysis in preliminary aircraft design | |
| Zaidi et al. | Copulas theory for probabilistic assessment: Overview with application to airplane performance analysis |