README NOTE ON DMAP ALTER PACAKGE FOR REPEATABLE RIGID BODY MODES USING LANCZOS METHOD, rnormal.v707 M. A. Gockel, January 14, 2000 1. BACKGROUND. The LAN and AHOU methods both start with random numbers when generating eigenvectors. Rigid body modes are a special case of repeated roots. Eigenvectors for repeated roots are not unique. They tend to change for small changes in the model, or even for changing solution parameters such as the number of initial vectors ("blocksize" on the eigrl entry). The AHOU method allows the user to make the rigid body roots repeatable by use of the SUPORT entry. The SUPORT entry is not used for this purpose in the LAN method at present. The alter allows the LAN method to also provide repeatable eigenvectors, using the same equations as the AHOU method in DMAP steps made after the eigensolution. 2. INPUT. Place "include 'rnormal.v707'" before the cend entry. Any eigensolution method requested will be replaced by the LAN method. PARAM, RNRATIO, [real] is used to distinguish zero roots with computational zero values from low frequency roots. Its default value of 1.E6 is perhaps too tolerant when you expect modeling errors to cause spurious low frequency roots. A larger value makes it less tolerant. 3. OUTPUT. Output is conventional. New messages list the number of rigid body modes found in the eigensolver. A fatal message is produced when the number, as determined from inspecting eigenvalues, is not the same listed on SUPORTi entries. The theory used is described in a TAN, in preparation. 4. EXAMPLE PROBLEM. File rnormal1.dat is the input file for a small straight shaft whose mass has been tuned such that all 6 diagonal terms of the rigid body mass are unity. This is the most difficult type of problem for which to generate repeatable rigid body eigenvectors. It is a modal frequency response model. If you compare its results with the same model when the alter package is removed you will find that the physical results (ACCELERATION) are identical, but that the modal results (SDISPL) differ greatly. If the same small change is made to both models the results without the alter will change greatly, but the results with the alter should change only a small amount.