Table Of ContentBALLISTIC MISSILE and
AEROSPACE TECHNOLOGY
Edited by C. T. MORROW, L. D. ELY, and M. R. SMITH
VOLUME I
Design and Reliability,
and Invited Addresses
VOLUME II
Ballistic Missile and
Space Electronics
VOLUME III
Propulsion, Space Science
and Space Exploration
VOLUME IV
Re-entry
PROPULSION,
S P A CE SCIENCE
and S P A CE
EXPLORATION
VOLUME III of
Ballistic Missile
and Aerospace
Technology
Proceedings of the Sixth Sym
posium on Ballistic Missile and
Aerospace Technology, held in
Los Angeles, California, in Au
gust 1961.
Sponsored by Headquarters, Of
fice of the Deputy Commander,
Air Force Systems Command, for
Aerospace Systems, and Aero
space Corporation
EDITORS
C. T. Morrow, L. D. Ely, and M. R. Smith
Aerospace Corporation, Los Angeles, California
ACADEMIC PRESS
New York and London · 1961
COPYRIGHT © 1961, BY ACADEMIC PRESS INC.
ALL RIGHTS RESERVED
NO PART OF THIS BOOK MAY BE REPRODUCED IN ANY FORM
BY PHOTOSTAT, MICROFILM, OR ANY OTHER MEANS,
WITHOUT WRITTEN PERMISSION FROM THE PUBLISHERS.
ACADEMIC PRESS INC.
Ill FIFTH AVENUE
NEW YORK 3, Ν. Y.
United Kingdom Edition
Published by
ACADEMIC PRESS INC. (LONDON) LTD.
17 OLD QUEEN STREET, LONDON S.W. 1
Library of Congress Catalog Card Number 60-16987
PRINTED IN THE UNITED STATES OF AMERICA
CONTRIBUTORS
J. R. Apel, The Johns Hopkins University, Applied Hiysics
Laboratory, Silver Spring, Maryland.
E. P. Bartlett, Aeronutronic, A Division of Ford Motor
Company, Research Laboratories, Newport Beach, California.
A. J. Beck, The Martin Company, Baltimore, Maryland.
D. I. Caplan, Nortronics, A Division of Northrop Corporation,
Electronic Systems and Equipaient Department, Palo s Verdes
Estates, California.
R. W. Clapp, Hughes Aircraft Company, Space Systems Division,
Culver City, California.
A. C. Diana, Rome Air Development Center, Griffiss Air Force
Base, New York.
E. Divita, The Martin Company, Baltimore, Maryland.
J. Elias, Aerojet-General Corporation, Solid Rocket Plant,
Sacramento, California.
G. A. Ellis, Rome Air Development Center, Griffiss Air Force
Base, New York.
V· Ilsen, Aerojet-General Corporation, Liquid Rocket Plant,
Sacramento, California.
M. H. Johnson, Hughes Aircraft Company, Systems Laboratory,
Fullerton, California.
M. M. Koshar, The Martin Company, Denver, Colorado.
R. D. Leonard, Allison Division, General Motors Corporation,
Research Department, Indianapolis, Indiana.
D. W. Liechty, Thompson Ramo Wooldridge Inc., New Devices
Laboratories, Cleveland, Ohio.
T. F. Morey, The Martin Company, Denver, Colorado.
C. A. OfMalley, Aerojet-General Corporation, Liquid Rocket
Plant, Sacramento, California.
A. T. Owens, Hughes Aircraft Company, Space Systems Division,
Culver City, California.
ν
SIXTH SYMPOSIUM ON BALLISTIC MISSILE AND AEROSPACE TECHNOLOGY
J. A. Rudy, Thompson Ramo Wooldridge, Inc., New Devices
Laboratory, Cleveland, Ohio.
S. L. Russak, The Martin Company, Baltimore, Maryland.
R. L. Sax, Hughes Aircraft Company, Space Systems Division,
Culver City, California.
J. W. Salisbury, Air Force Cambridge Research Laboratories,
Geophysics Research Directorate, Bedford, Massachusetts.
C C. Silverstein, Cornell Aeronautical Laboratory, Inc.,
Buffalo, New York.
S. F. Singer, University of Maryland, College Park, Maryland.
J. E. Taylor, Thompson Ramo Wooldridge, Inc., New Devices
Laboratories, Cleveland, Ohio.
C. Usiskin, Radio Corporation of America, Astro-Electronics
Division, Princeton, New Jersey.
R. Wilkes, Radio Corporation of America, Astro-Electronics
Division, Princeton, New Jersey.
vi
PREFACE
The 1961 Air Force/Aerospace Corporation Symposium on
Ballistic Missile and Aerospace Technology was held at the
University of Southern California, Los Angeles, on August 29-31·
This vas the sixth in a series of annual symposiums; the first
three were primarily concerned with ballistic missile tech
nology, but in 1959 the scope was enlarged to emphasize the
work being done in the field of space technology. The objec
tive has been to provide a means for the exchange of technical
information and ideas among aerospace engineers and scientists.
The program included invited introductory, keynote, and
luncheon addresses, in addition to 130 technical papers, both
classified and unclassified. Final selection from the large
number of papers submitted was made by the Program Committee
after a detailed review by many members of the technical staffs
of the Aerospace Corporation and the Air Force Systems Command.
The members of the Program Committee were:
R. A. Becker C. T. Morrow
Maj. V. J. Bracha Lt. Col. C. N. Nelson
L. D. Ely (Chairman) T. R. Parkin
J. G. Logan C. J. Wang
D. Willens
TJie Proceedings contain the unclassified papers, organ
ized into four volumes, as follows:
Vol. I Invited Addresses, Design and Reliability
Vol. II Ballistic Missile and Space Electronics
Vol. Ill Propulsion, Space Science and Space
Exploration
Vol. IV Re-entry
T he Transactions contain primarily the classified papers,
also organized into four volumes. These are available to
appropriately cleared organizations that have a justified need
to know upon request to Hq, Office of the Deputy Commander
AFSC for Aerospace Systems (DCIMT), Air Force Unit Post Office,
Los Angeles ^5, California
Aerospace Corporation C T. Morrow
October 1961 L. D. Ely
M. R. Smith
vii
SIXTH SYMPOSIUM ON BALLISTIC MISSILE AND AEROSPACE TECHNOLOGY
THE USE OF STATISTICAL DESIGN IN
MISSILE PROPULSION STUDIES
C. A. O'Malley
Aerojet-General Corporation
Liquid Rocket Plant
Preliminary Design Department
Sacramento, California
Abstract
It has been said by Dr. Hafstead, Vice President for
Research, General Motors, that one of the most powerful
tools in the hands of the engineer today is statistical design.
Many industrial organizations are becoming increasingly
aware of the usefulness of this tool and are taking steps to
promote its use. Large corporations in every field have es
tablished special sections to aid in the establishment and
evaluation of design work and experimentation. Others are
providing training for their engineers and scientists to enable
them to more intelligently plan their work, and many are
employing the services of consultants in this field.
Introduction
We are greatly indebted to the agricultural experimen
ters for much of the background development in experimental
design. The application of statistical principles to industrial
design and experimentation is a very recent development;
hence, few other than those specializing in the field have any
great understanding of the techniques available and their
power. The statistical courses given as part of mathematics
programs in most schools provide useful background for the
evaluation of results, but give little actual help in the initial
designs; yet this is where most knowledge is needed.
Emphasis on Skill
It is frequently said that all the emphasis on skill
needed to use statistical methods is ridiculous; that any good
engineer with common sense can plan a program and get
meaningful data. Yet the literature is filled with examples
of poorly planned and poorly evaluated design and research,
and hours are spent trying to bring sense to a hodge-podge
5
SIXTH SYMPOSIUM ON BALLISTIC MISSILE AND AEROSPACE TECHNOLOGY
of engineering calculations and experimental data.
To use an example specifically directed toward labora
tory researchers, in a 1957 talk before the Detroit section of
the American Chemical Society, Dr. W. J. Youden of the
U.S. Bureau of Standards indicated the six steps that must be
followed if you expect to get along without the use of statisti
cal design.
1. Take more care--If the data collected will not
correlate, probably it means bad technique and poor record
taking.
2. Obtain new ins truments --If more care will not
yield the results expected, the instruments must be at fault.
3. Samples must be bad--Obtain new samples and
check and recheck.
4. Obtain many measurements to reduce chance of
error (very quickly dropped as too laborious and time con
suming).
5. Measure another property--This permits a fresh
start and repetition of the preceding steps.
6. If these steps fail, work on some other problem.
Obviously, such a course would be very wasteful of both
time and money and it would be better to plan in advance a
program which would acquire a maximum of useful informa
tion with less effort.
Requirements of Statistical Designs
What then are the requirements for such a program?
First, it should avoid bias. A good program must be com
pletely objective. Second, errors should be minimized, and
at the same time a realistic estimate of those errors should
be provided within the data collected. In research work,
checks on the operation of the equipment used should be built
into the program, and, specifically in design work, the num
ber of calculations should be reduced to the minimum needed
to satisfy these requirements.
Characteristics of Good Designs
A good design will meet these requirements and sim
plify the entire program. It will face in advance the problem
of data interpretation and present it in a usable form. The
order of trial runs will be random to avoid bias and negate
variations that may occur with time variations due to obso
lescence of available data. Sufficient replication will be in
cluded to permit error estimation, and the design work will
be programed.
The investigation of the effects of varying a single fac
tor or making simple neither-orn choices is relatively simple.
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SIXTH SYMPOSIUM ON BALLISTIC MISSILE AND AEROSPACE TECHNOLOGY
However, in industrial work we frequently wish to investigate
more complex relationships. There may be a relatively
large number of independent variables. The effects of the
variables that we are able to control may not be independent
of each other. Or there may be any number of variables over
which we have little or no control and no way of even measur
ing. Variables may be controlled, but only within a narrow
range that will not significantly lower the criterion chosen
for the evaluation of a given missile design. Because of these
restraints, the magnitudes of effects observed will usually be
very small and may well be completely obscured by the errors
involved in setting conditions and observing results and the
effects produced by variations in conditions that are not con
trolled.
We can usually anticipate that the error of observations
in industrial design or experimental work will be very large,
and statistical tests of significance must be applied to each
result to determine if it is real or caused by error. Also, if
we are to ensure that any result be significant (i. e. , the ap
parent effect significantly greater than the error in its deter
mination) we must either run a great number of tests (which
may be expensive or too time consuming) or resort to special
statistical designs that will permit us to derive the maximum
of useful information from a minimum of actual tests.
These are the problems that have lead the engineer to
adopt methods originally developed by agricultural workers
(who were unable to control variations in weather, soil fer
tility, and other factors) and to develop other methods more
suited to his problem.
Probably the most commonly used scheme of design,
where more than one variable is involved, is the factorial
experiment originally developed during the 1920s and 1930s
by R. A. Fisher and his colleagues at the Rothamstad Exper
iment Station. Since it is from this technique that other tech
niques have evolved, it would be well to discuss it in some
detail.
The Classical Method and Factorial Design
The classical method for design or experimental work
is to hold all the independent variables constant but one. Un
fortunately, this fails to detect any possible interactions be
tween variables. Thus, changing the value of factor A from
a value, Αχ, to some other value, A2> might produce a given
change in the criterion of evaluation with factor Β fixed at a
value, B,, but a different change when factor Β is at B^.
Factorial design can detect this type and at the same time
give the maximum amount of information about the problem
under investigation for a given amount of work. In his
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SIXTH SYMPOSIUM ON BALLISTIC MISSILE AND AEROSPACE TECHNOLOGY
approach to experimentation, Fisher differed in two funda
mental aspects from the classical "one variable at a time"
technique. First, he stressed the importance not necessarily
of minimizing the magnitude of the experimental or design
error, but rather of obtaining a reliable estimate of the exact
magnitude of error. This knowledge is needed if exact tests
of significance are to be applied. Secondly, he emphasized
the advantages to be gained if as many as possible of the fac
tors under investigation can be included in the same design or
experimental trial. These advantages are indicated as fol
lows :
Comparison of Classical and Factorial Design Methods
Classical Factorial
1. Each variable studied 1, All variables of inter-
individually, all others est studied simultane-
held constant ously
2. A separate portion of the 2. All of the data used for
data used for each con- all conclusions
elusion
3. No indication of inter- 3. Effect of interactions
actions detectable
4. No estimate of design 4. Estimate of design or
or experimental error experimental error
possible unless indivi- possible without repe-
dual tests are repeated tition of tests
several times
5. Conclusions drawn with- 5. Conclusions drawn
out a known degree of within a known degree
confidence of certainty
Factorial Design
Let us assume that we wish to make a factorial design
study involving five variables at two levels. The design
trial would be set up as shown in Table 1. The plus and mi
nus signs indicate the upper and lower levels of the variables,
respectively. The treatment combination indicates the pro
duct of all variables at their upper levels, and the effect ob
tained, in the case of a complete factorial design trial, is
synonymous with the grouping indicated for the treatment
combination. Treatment combination (1) indicates all vari
ables at their lower level.
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