1、, b95534 0003220 57T U Special Copvright Notice o I999 by the American Institute of Aeronautics and Astronautics. All rights reserved. AIAA SO71 A-I 999 Standard Assessment of Experimental Uncertainty With Application to Wind Tunnel Testing AIAA SO71 A-I 999 Standard Assessment of Experimental Uncer
2、tainty with Application to Wind Tunnel Testing Sponsor American Institute of Aeronautics and Astronautics Abstract This AIAA Standard provides a new methodology for assessment of experimental uncertainty and a tech- nique for evaluating wind tunnel error sources. The methodology is then applied to a
3、 force and pressure test. The document is revision to the original document which was based on a Report of the NATO Advi- sory Group on Aerospace Research and Development (AGARD). AIAA S-O71 A-1999 Library of Congress Cataloging-in-Publication Data Assessment of experimental uncertainty with applica
4、tion to wind tunnel testing. p. cm. “AIAA S-O71 A-1999” Includes bibliographical references (.p), ISBN 1-56347-363-1 (softcover) - ISBN 1 -56347-364-X (electronic) 1. Wind tunnels. 2. Airplanes-Models-Testing. I. American Institute of Aeronautics and Astro nau t ics . TL567.W5 A87 1999 629.13452 21-
5、dc21 99-041 147 Published by American Institute of Astronautics and Aeronautics 1801 Alexander Bell Drive, Suite 500, Reston, VA 20191 Copyright O 1999 American Institute of Aeronautics and Astronautics All rights reserved. No part of this publication may be reproduced in any form, in an electronic
6、retrieval system or otherwise, without prior written permission of the publisher. Printed in the United States of America. II AIAA S-O71 A-1999 Contents Foreword v 1. 2. 2.1 2.2 2.2.1 2.2.2 2.2.3 2.3 2.3.1 2.3.2 2.3.3 2.4 2.5 3. 3.1 3.2 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5 3.3 3.4 4. 4.1 4.2 4.3 4.3.1 4.3.
7、2 4.3.3 4.3.4 4.3.5 4.3.6 4.4 4.4.1 4.4.2 4.4.3 4.4.4 4.4.5 4.4.6 4.5 4.6 5. Introduction . 1 sessment Methodology . 4 . ertainty Components in Measured Variables . Estimating Precision Limits Estimating Bias Limits . 6 Estimating Uncertainty Components for Experimental Results . f Precision Limits
8、into an Experimental Result Propagation of Bias Limits into an Experimental Result . Summary of Methodology . 12 Reporting Uncertainties . . 13 References . . 13 Wind Tunnel Error Sources . 19 Introduction . 19 Process Error Sources . . 19 Test Tech n que . 20 Model Shape and Finish . 22 Tunnel Flow
9、 Quality . . 22 Instrumentation . 23 Math Models . 24 Significance of Error Sources . 25 Concluding Remarks . 30 Application of the Uncertainty Met and Pressure Test . 31 Introduction . 31 Test Description . . 31 Uncertainty of a Measurement System . 33 Uncertainty Evaluation Data . 33 Outlier Detec
10、tion . 35 Uncertainty of an Instrumentation . . 37 Discussion of Systems with Multiple Dependent Channels . 39 Uncertainty Evaluation of Other Test Systems Estimated Uncertainties of Various Parameters Data Reduction and Estimated Uncertainty of the Forebody Drag Coefficient Tunnel Conditions 42 Mod
11、el Attitude Measured Gross Axial and Normal Forces 46 Model Aerodynamic Axial and Normal Model Base Axial Force 50 Wind Tunnel Aerodynamic Drag Coefficient Adjustment to the Aerodynamic Reference Condition Reporting Uncertainty References . Summary and Recommendations Nomenclature . . 82 . . 111 AIA
12、A S-O71 A-1999 Annexes 2-A 2-B 4-A 4-B 4-C 4-D 4-E A Comprehensive Uncertainty Analysis Methodology . 14 Identification and Elimination of Outliers in Samples . 18 Uncertainty Methodology for Multiple Channel Instrumentation Systems 58 Determination and Evaluation of the Partial Derivatives Used in
13、the Text . 60 The Effect of Determining the Partial Derivatives with Respect to Dependent Parameters 70 Pressure Integration Example 73 Uncertainty of an Incremental Value 78 iv AIAA S-O71 A-1999 Foreword Measurement uncertainty has long been a topic of discussion and controversy within the aerospac
14、e com- munity. The problem is not the lack of good methodology in this area, references on the subject exist and are readily available. The difficulty has been in the application of the methodology by researchers and en- gineers with consistency and regularity. The AIAA Standards Technical Council a
15、pproved an AIAA Standard on measurement uncertainty in 1995. The AIAA has adopted the standard set forth by the NATO Advisory Group for Aerospace Research and Development (AGARD) through AGARD publication AR-304. This standard is the result of an AGARD working group and represents methodology consis
16、tent with that adopted by the AIAA Ground Test Tech- nical Committee which has provided support and guidance in the adoption and review of this publication. At the AGARD Fluid Dynamics Panel symposium on Aerodynamic Data Accuracy and Quality: Require- ments and Capabilities in Wind Tunnel Testing in
17、 October 1987, continuing important problems related to aerodynamic data quality were noted. The technical evaluator suggested that improved treatment of data uncertainty would help alleviate some problems. The panel approved an examination of data quality as- sessment methodologies with the intent
18、of recommending specific improvements. Measurement uncertainty is a complex subject involving both statistical techniques and engineering judg- ment. The method reported here was adapted from currently accepted practices by Working Group 15 of the AGARD Fluid Dynamics Panel and has been revised by t
19、he Standards Subcommittee of the AIAA Ground Testing Technical Committee. The objective of the document, is to provide a rational and practical framework for quantifying and reporting uncertainty in wind tunnel test data. The quantitative assessment method was to be compatible with existing methodol
20、ogies within the technical community. Uncertainties that are difficult to quantify were to be identified and guidelines given on how to report these uncertainties. Although this document uses wind tunnel testing examples exclusively in its treatment of experimental uncertainty, the methodology is ap
21、plicable all experimental test processes. The members of the AGARD Working Group were (affiliation shown as of the publication date of the AGARD document): Mr. Robin D. Galway (NRC, Institute for Aerospace Mr. Claude Armand (ONERA, Centre de Modane Mr. Claude Quemard (ONERA, Centre de Modane Dr. Gun
22、ter Viehweger (DLR, Kln, Germany) Mr. Jan H. A. te Boekhorst (NLR, Amsterdam, Dr. David S. Woodward (DRA, Farnborough, UK) Mr. Keith Pallister (ARA, Bedford, UK) The members of the Standards Subcommittee of the AIAA Ground Test Technical Committee who have reviewed and revised this document have for
23、 some time been collaborating with the AGARD working group and deliberating themselves on how best to present this methodology as a consensus document. The AIAA, as an accredited non-government standards developer, was deemed to be ideal for this pur- pose. This standard will be complimented by a re
24、commended practice on its use. The AIAA Standards Procedures provide that all approved Standards, Recommended Practices, and Guides are advisory only. Their use by anyone engaged in industry or trade is entirely voluntary. There is no agreement to adhere to any AIAA standards publication and no comm
25、itment to conform to or be guided by a standards report. In formulating, revising, and approving standards publications, the Committees on Standards will not consider patents which may apply to the subject matter. Prospective users of the publi- cations are responsible for protecting themselves agai
26、nst liability for infringement of patents or copyrights, or both. Mr. Travis W. Binion (Micro Craft Technology, Mr. David M. Cahill (Micro Craft Technology, Dr. Hugh W. Coleman (University of Alabama in Dr. Keith L. Kushman, Chairman (USAF-AEDC, Dr. Frank Steinle (NASA Ames Research Research,Ottawa,
27、 Canada) Avrieux, France) Avrieux, France) Huntsville, AL, USA) Arnold AFB, TN, USA) Arnold AFB, TN, USA) Arnold AFB, TN, USA) Center, CA, USA) Netherlands) V AIAA S-O71 A-1999 The AIAA Ground Test Technical Committee (Dr. A. George Havener, Chairman) and Standards Sub- committee approved the origin
28、al version of the document in June 1994. The AIAA Standards Technical Council (Ali M. Ghovanlou, Chairman) approved the original version of the document in May 1995. The Standards Subcommittee of the AIAA Ground Test Technical Committee (Ms. Laura J. McGill, Chair- person) consisted of the following
29、 individuals at the time Revision A of the document was approved in June 1999: Mr. David M. Cahill (Sverdrup Tech., AEDC) Mr. Daniel Cresci (GASL) Dr. Susan T. Hudson (NASA Marshall Space Mr. Wayne Kalliomaa (Air Force Research Lab.) Mr. Daniel E. Marren (AEDC/White Oak) Mr. Mathew L. Rueger (Boeing
30、) Mr. William A. Straka (Applied Research Lab., Flight Center) Penn State University) Dr. James C. Yu (NASA Langley Research Center) The AIAA Standards Executive Council accepted the document for publication in August 1999. The Stan- dards Subcommittee would like to thank the following individuals f
31、or their review of this document. Ap- proval of the document was unanimous. Dr. Hugh W Coleman (University of Alabama in Hunstville) Dr. Frank W. Steinle Jr. (Sverdrup Tech., AEDC) Mr. Robin D. Galway (NRC Institute for Aerospace Research, Canada, Retired) The AIAA and the GTTC would like to thank M
32、r. David M. Cahill for his outstanding efforts to develop the revisions, edit the document, and coordinate the revision process to produce Revision A of the Standard. Summary of the major revisions and corrections made in Revision A: Chapter 1 - Included the rational for retaining the Bias Limit and
33、 Precision Limit nomenclature Chapter 2.5 - Included statement concerning the traceability of uncertainty to a primary standards organi- zation such as the National Institute of Standards and Technology (NET). Chapter 4.3.3 - Clarification of transducer drift in final paragraph in the section. Chapt
34、er 4.4.3 - Revision in the methodology used to estimate the correlated bias of W,. Also, clarification of the method used to determine the measured gross forces and moments. Chapter 4.4.5 - Correction for the way the bias and precision limits for the reference pressure, P, were propagated and the ca
35、lculation of the partial derivatives taken with respect to P, (thanks to Larry Meyn for pointing out this error). Revision to include a second correlated bias resulting from the bias limit asso- ciated with the drift in the transducers caused by a change in operating temperature. vi AIAA S-O71 A-199
36、9 1. Introduction Wind tunnel data are often presented without reference to the quality of the results. When data uncertainty is considered, it is normally in the form of repeatability from a few supposedly identical tests. Only rarely are estimates of uncertainty based on professional calibrations
37、of facilities and instrumentation, a thorough review of the process producing the data, and comprehensive accounting of significant biases inherent in the experiment. The development of new and modified aircraft is frequently compromised by inadequate consideration of experimental error. References
38、1.1 through 1.4 are some of the AGARD publications that have reported important problems over the past 20+ years. An AGARD Symposium in 1987 (Ref. 1.5) entitled “Aerody- namic Data Accuracy and Quality: Requirements and Capabilities in Wind Tunnel Testing” highlighted continuing problems. Two import
39、ant improvements in data quality assessment practices are clearly needed. The first is to adopt a consistent approach for integrating uncertainty analyses into all phases of a test. The second is to provide a complete professional analysis and documentation of uncertainty for each test. This report
40、describes an engineering approach to wind tunnel data quality assessment that can alle- viate many of the problems documented in Ref. 1.5. The method developed in this report is general. Air- craft aerodynamic testing was selected as a specific example application to provide a focus for describing a
41、nd applying the method. An important concern of an aircraft developer is the risk inherent in predicting the flight performance of a full-scale system. There are numerous contributors to the uncertainty of flight predictions, as shown in Fig. 1 .l. Note that some of the contributions occur as the re
42、sult of analyses that use wind tunnel data as the starting point. Model protuberance, propulsion temperature effects, and extrapolation from refer- ence conditions are ex- amples of such analyses. Other contributions to data uncertainty are directly related to the wind tunnel test. While the method
43、INCREMENTS TO CALIBRATION AERODYNAMIC THEORETICAL REFERENCE DATA PREDICTIONS EXTRAPOLATION EFFECTS PREDICTED ACQUISITION AND I FLIGHT PERFORMANCE 1 I INCFRTAINTV MODEL ENVIRONMENT TECHNIQUES Figure 1 .I Contributions to predicted flight performance uncertainty presented applies to any contribution,
44、the scope of this report is limited to those associated with the wind tunnel test. The discussion is pointed toward providing the uncertainty of data for an unsupported rigid model in free air at the wind tunnel test conditions (Mach number, Reynolds number, boundary-layer state.), commonly known as
45、 the aerodynamic reference condition. Figure 1.2 illustrates typical contribu- tors to uncertainty within the scope of this report. A well-defined, useful reference condition and related uncertainty analysis should be reported by wind tunnel facilities for all tests, regardless of type. The terms “d
46、ata quality” and “uncertainty” are used interchangeably throughout this report to reinforce the concept that intelligent design, execution, and documentation of a test adds great value to the results and must be done in a structured, consistent framework to gain the greatest benefit. It is clear tha
47、t the risk in- volved in predicting flight performance is directly related to how well tests are designed to provide useful simulations of flight and suitably accurate data. Risk is managed by careful objective and subjective rea- soning about the primary sources of error in the prediction processes
48、. Experimentalists know that a 1 AIAA S-O71 A-1 999 comprehensive uncertainty analysis uses quantitative estimates that are developed in a structured manner with as much rigor as is appropriate and possible. An assessment of the system development and test proc- esses involves judgments about the “q
49、uality” of the results to be pro- duced. A major component of such judgments must be an uncertainty est i mate. Data quality assessment should be a key part of the entire wind tunnel testing process. A simple schematic of the process (Fig. 1.3) shows con- siderations for uncertainty influenc- ing the decision whether to test or not, the design of the experiment, and the conduct of the test. Figure 1.3 also shows the important step of proper analysis and documentation AERODYNAMIC REFERENCE UNCERTAINTY MODEL FIDELITY SIMULATION TECHNIQUES AS-BUILT GEOMETRY AERO-ELASTIC REYNOLDS NUMBER
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