Stanford Research Communication Program
  Home   Researchers Professionals  About
 
Archive by Major Area

Engineering
Humanities

Social Science

Natural Science

Archive by Year

Fall 1999 - Spring 2000

Fall 2000 - Summer 2001

Fall 2001 - Spring 2002

Fall 2002 - Summer 2003


 

 

 



Why Are Jet Airplanes So Loud?

Daniel Bodony
Aeronautics & Astronautics
Stanford University
May 2001

People living near a major airport know that when an airplane flies overhead, the noise created is loud enough to rattle dishes and wake them up. My research attempts to develop a method to predict the noise so that quieter engines can be designed.

A big problem in reducing airplane noise is that it is very expensive and time consuming to experimentally test an airplane, determine its noise, and correct the design if necessary. Computers are beginning to show promise in predicting airplane noise by simulating some air motion around an airplane and/or its engines, but they do not yet have enough capability to simulate the entire airplane and its engines. Instead, individual components of the airplane are simulated, such as the jet engine exhaust, and examined in detail. Even at this simplified level, today's computers are not fast enough and big enough to simulate realistic conditions. To account for this, computer models, similar to those used in meteorology, are used to simplify the calculation and make it feasible to solve relatively simple problems. My research focuses on creating a model that can help predict the noise generated by jet engine exhaust, making it easier to incorporate design changes, thus saving time and money and allowing quieter jets to be produced.

Since the 1950s, the introduction of jet airplanes capable of carrying paying passengers across large distances quickly and in comfort has dramatically changed the way people think about travel. There has been a steadily increasing demand for inexpensive air travel to which the airlines and airplane manufacturers have met by purchasing and producing more and more airplanes. The influx of more aircraft flying each year has put stress on the world's air traffic control centers and encouraged airports to become more efficient, squeezing as many airplanes onto and around the field as possible.

To suspend the corresponding noise pollution increase caused by the growing number of airplanes, the United States government, through the Federal Aviation Administration (FAA), has implemented increasingly stringent noise restrictions on airplanes. Usually these restrictions state something like "aircraft XYZ cannot create more than 100 decibels of sound while taking off and flying over a house at 1,000 feet." The aircraft manufacturer is burdened with designing airplanes that meet this noise requirement or else no airline may buy the new planes. The difficulty of the design process lies in that it is very hard to predict the noise coming from an airplane.

The airplane manufacturer will usually build a small test model of the airplane and engine and perform wind tunnel tests, measuring the sound generated by using microphones and digital processing techniques. In this manner there is considerable cost in building the model, in taking and analyzing the measurements, and in implementing changes to the airplane design. To find a better approach, there is a desire to develop predictive techniques so that models do not need to be built and design changes can be more easily incorporated. One such technique that is just becoming viable is the use of computers to simulate the airflow around an airplane, or a component of it, and then calculate the noise.

To predict the noise using a computer, the equations of motion for air must be solved in a region containing the noise-producing component, say the jet exhaust, in great detail. The computer solution is then processed and the sound extracted from the overall solution is converted into decibels, which are then compared to the FAA regulations.

There is no free lunch, as the cliché goes, and the problem with solving for the motion of the air behind a jet engine in great detail is that there is an incredible amount of information that must be used and processed, meaning that very large and fast computers must be used. Current simulations need nearly 50 million points around an air jet at which information is stored to provide enough detail for the sound to be captured and are run on computers with sixty to six hundred processors for one or two months continuously. On computers this size, the monetary cost for one of these simulations can reach $1,000 per hour, which adds up to a lot of money over a month's time.

In helping to alleviate the extraordinary costs, it is hoped that if models can be developed that mimic the motion of air on a very small scale, say less than one millimeter, then the overall number of points needed can be dropped from 50 million to 10 million, or less, translating into a simulation run time drop from two months to two weeks or less. Unfortunately, no models like this exist that also predict the sound created by these small scales. That's where my research comes in: I will attempt to develop, or at least to begin the developmental path, of a model that predicts the sound generated by the smallest scales of motion. Such a model is called an LES (large eddy simulation) acoustic model, where the "large eddy" portion means that the “small eddies”, or scales, are modeled and not simulated, while the large eddies are simulated. By using this model, together with the airplane geometry, and by solving the equations of motion on a very large computer, the noise from a flying airplane can be predicted in a reasonably short period of time.

The process of developing a noise model for computer simulations is long and involves a wide variety of tools that must be used. First, a way must be developed to extract the sound predicted in computer simulations that have already been completed so that a noise database can be created. With the help of mathematics and physics, this database must be explored and analyzed to find the connection between the motion of air at the smallest scales and the sound produced. This step is the most crucial, and most difficult, and represents the bulk of the work. Once a connection is found, the mathematical model can be constructed and tested against the database. It is expected that several generations of model development will be necessary before a suitable description is found.

When completed, my research will help in allowing engine and airplane manufacturers to predict the noise created by their products more cheaply, thereby lowering the cost of these airplanes. More importantly, however, the noise generated by commercial aircraft will be reduced, removing some of the adverse environmental impact created by modern jet transports.