Home » RDBMS Server » Server Utilities » creating control file to load data from a text file
creating control file to load data from a text file [message #124531] Sun, 19 June 2005 20:40 Go to next message
sikyala
Messages: 33
Registered: May 2005
Member
I have a text file that I need to load into an Oracle database.

Below is a sample of the text in the text file.

File Format: backslash delimited ("\"), followed by a number in brackets.
The number indicates the field number; a legend of all possible fields follows.
Actual data begins after the line of '='.
(1) IAC Assigned Accession Number\(2) Citation Status\(3) Report Classification\(4) Citation Classification\(5) Distribution Limitation(s)\(6) Abstract Classification\(7) Title Classification\(8) Distribution Statement\(9) Creation Date\(10) Unclassified Title\(11) Report Date\(12) Document Location\(13) IAC Document Type Code\(14) IAC Document Type\(15) Media Count\(16) Pagination Code\(17) Descriptor Classification\(18) TAB Year\(19) TAB Issue Number\(20) Personal Author(s)\(21) Abstract\(22) IAC Subject Terms\(23) Accession Number\(24) Supplementary Note\(25) Identifiers\(26) Descriptors\(27) Field(s) & Group(s)\(28) Organization Type Code\(29) Organization Type\(30) Geo-Political Code\(31) Monitor Series\(32) Monitor Acronym\(33) Contract Number\(34) Report Number(s)\(35) Corporate Author\(36) Source Code\(37) Identifier Classification\(38) Copyright Status\(39) Name of Responsible Person
===================================================================================================================================== ===================================================================================================================================== ===================================================================================================================================== ===================================================================================================================================== ===================================================================================================================================== ===================================================================================================================================== ============================================================================================================
\(1) NT-53556 NT53556\(10) Radar Signal Interpretation Using Neural Network for Defect Detection in Concrete,\(20) Shoukry, Samir N. Martinelli, David Varadarajan, Srinivas T. Halabe, Udaya B. \(11) 01 Mar 1996\(15) 5 Page(s) \(22) N--(U) ISSN 0025-5327, BRIDGES, CONCRETE, GROUND PENETRATING RADAR, INFRASTRUCTURE, NEURAL NETWORKS.; \(27) na\(14) JOURNAL ARTICLES \(12) NTIAC \(3) Unclassified \(5) 01 - APPROVED FOR PUBLIC RELEASE 21 - JOURNAL ARTICLES ANNOUNCEMENT ONLY \(8) Availability: Published in 'Materials Evaluation'; 54,3; March 1996; 393-397; 10 refs. (Copies not available from NTIAC/DTIC).\(21) A neural network based on the learning vector quantization (LVQ) technique is applied for the classification of radar echo waveforms obtained from concrete bridge deck specimens with varying internal defects. A randomly chosen set of as measured (raw) time-domain echo-signals was used in training the network to classify waveforms into those representing defective and nondefective conditions in the concrete specimens. The same set of waveforms as preprocessed by subtracting the reference noise signal and was again separately used to train the networks. Different versions of LVQ algorithms were used independently in training, and the best results in terms of the recognition accuracy were obtained by training using the OLVQ (optimized LVQ) algorithm. The OVLQ trained neural network was able to classify an independent set of test waveforms with a higher degree of accuracy than those trained with other variants of LVQ algorithms. It has been observed that the subtraction of the reference noise component (preprocessing of the time domain signal) had no effect on the performance of the correct recognition of the OVLQ network. The performance of the network indicates its high potential for use in the analysis and interpretation of raw radar echo waveforms. This technique also holds promise for successful classification of radar waveforms into classes that represent specific kind of internal defects in concrete specimens such as cracks, delaminations, voids, etc. (Author).\(24) Published by American Society for Nondestructive Testing, 1711 Arlingate Lane, P.O. Box 28518, Columbus, OH 43228-0518.\(9) na\(23) ADD339501 \(38) yes\(39) George Matzkanin
\(1) NT-53555 NT53555\(10) Optimal Pultrusion Process Conditions for Improving the Dynamic Properties of Graphite-Epoxy Composite Beams, \(20) Kowsika, Murthy V. Mantena, P. Raju \(11) 01 Mar 1996\(15) 7 Page(s) \(22) N--(U) ISSN 0025-5327, COMPOSITES, DAMPING, FLEXURE, GRAPHITE EPOXY, PULTRUSION, REGRESSION ANALYSIS, VIBRATION ANALYSIS, MATHEMATICAL MODELS.; \(27) na\(14) JOURNAL ARTICLES \(12) NTIAC \(3) Unclassified \(5) 01 - APPROVED FOR PUBLIC RELEASE 21 - JOURNAL ARTICLES ANNOUNCEMENT ONLY \(8) Availability: Published in 'Materials Evaluation'; 54,3; March 1996; 386-392; 16 refs. (Copies not available from NTIAC/DTIC).\(21) The manufacturing process variables significantly influence the mechanical properties of pultruded composites. In this study, a statistical central composite design (CCD) test pattern has been used to manufacture unidirectional graphite-epoxy pultruded composite beams under carefully controlled process conditions.


There are over 4000 records formatted like this. I can not figure out how to write a control file that would load these records in a table because of the way the fields are labeled. There are fields that have no value.

If there is someone who knows how I can get this data loaded I would appreciate your help.

Thanks!
Re: creating control file to load data from a text file [message #124533 is a reply to message #124531] Sun, 19 June 2005 20:53 Go to previous messageGo to next message
DMcG
Messages: 51
Registered: May 2005
Location: Auckland, New Zealand
Member
Yuck !

I think you'll struggle to get SQL Loader to handle that - it'd be easier to load the whole thing as a series of strings and write a parsing routine to make sene out of it.

Dougie McGibbon
Re: creating control file to load data from a text file [message #124535 is a reply to message #124531] Sun, 19 June 2005 21:18 Go to previous messageGo to next message
sikyala
Messages: 33
Registered: May 2005
Member
Could you tell me how I could load the data as strings and parse it?
Re: creating control file to load data from a text file [message #124536 is a reply to message #124535] Sun, 19 June 2005 21:32 Go to previous messageGo to next message
Mahesh Rajendran
Messages: 10707
Registered: March 2002
Location: oracleDocoVille
Senior Member
Account Moderator
or
try external tables? Consider this text file as an oracle table.
apply oracle native methods to get data out from the external table.
http://www.dbazine.com/oracle/or-articles/still1
Re: creating control file to load data from a text file [message #124549 is a reply to message #124531] Mon, 20 June 2005 02:45 Go to previous message
Barbara Boehmer
Messages: 9097
Registered: November 2002
Location: California, USA
Senior Member
scott@ORA92> CREATE TABLE your_table
  2    (col1  varchar2(4000),
  3  	col2  varchar2(4000),
  4  	col3  varchar2(4000),
  5  	col4  varchar2(4000),
  6  	col5  varchar2(4000),
  7  	col6  varchar2(4000),
  8  	col7  varchar2(4000),
  9  	col8  varchar2(4000),
 10  	col9  varchar2(4000),
 11  	col10 varchar2(4000),
 12  	col11 varchar2(4000),
 13  	col12 varchar2(4000),
 14  	col13 varchar2(4000),
 15  	col14 varchar2(4000),
 16  	col15 varchar2(4000),
 17  	col16 varchar2(4000),
 18  	col17 varchar2(4000),
 19  	col18 varchar2(4000),
 20  	col19 varchar2(4000),
 21  	col20 varchar2(4000),
 22  	col21 varchar2(4000),
 23  	col22 varchar2(4000),
 24  	col23 varchar2(4000),
 25  	col24 varchar2(4000),
 26  	col25 varchar2(4000),
 27  	col26 varchar2(4000),
 28  	col27 varchar2(4000),
 29  	col28 varchar2(4000),
 30  	col29 varchar2(4000),
 31  	col30 varchar2(4000),
 32  	col31 varchar2(4000),
 33  	col32 varchar2(4000),
 34  	col33 varchar2(4000),
 35  	col34 varchar2(4000),
 36  	col35 varchar2(4000),
 37  	col36 varchar2(4000),
 38  	col37 varchar2(4000),
 39  	col38 varchar2(4000),
 40  	col39 varchar2(4000))
 41  /

Table created.

scott@ORA92> CREATE OR REPLACE DIRECTORY my_dir AS 'c:\oracle'
  2  /

Directory created.

scott@ORA92> DECLARE
  2    v_bfile	      BFILE   := BFILENAME ('MY_DIR', 'your_text_file.txt');
  3    v_clob	      CLOB;
  4    v_dest_offset  INTEGER := 1;
  5    v_src_offset   INTEGER := 1;
  6    v_src_csid     NUMBER  := NLS_CHARSET_ID ('US7ASCII');
  7    v_lang_context INTEGER := DBMS_LOB.DEFAULT_LANG_CTX;
  8    v_warning      INTEGER;
  9    v_string       VARCHAR2(32767);
 10    v_col	      VARCHAR2(30);
 11    v_col1	      VARCHAR2(32767);
 12    v_col2	      VARCHAR2(32767);
 13    v_col3	      VARCHAR2(32767);
 14    v_col4	      VARCHAR2(32767);
 15    v_col5	      VARCHAR2(32767);
 16    v_col6	      VARCHAR2(32767);
 17    v_col7	      VARCHAR2(32767);
 18    v_col8	      VARCHAR2(32767);
 19    v_col9	      VARCHAR2(32767);
 20    v_col10	      VARCHAR2(32767);
 21    v_col11	      VARCHAR2(32767);
 22    v_col12	      VARCHAR2(32767);
 23    v_col13	      VARCHAR2(32767);
 24    v_col14	      VARCHAR2(32767);
 25    v_col15	      VARCHAR2(32767);
 26    v_col16	      VARCHAR2(32767);
 27    v_col17	      VARCHAR2(32767);
 28    v_col18	      VARCHAR2(32767);
 29    v_col19	      VARCHAR2(32767);
 30    v_col20	      VARCHAR2(32767);
 31    v_col21	      VARCHAR2(32767);
 32    v_col22	      VARCHAR2(32767);
 33    v_col23	      VARCHAR2(32767);
 34    v_col24	      VARCHAR2(32767);
 35    v_col25	      VARCHAR2(32767);
 36    v_col26	      VARCHAR2(32767);
 37    v_col27	      VARCHAR2(32767);
 38    v_col28	      VARCHAR2(32767);
 39    v_col29	      VARCHAR2(32767);
 40    v_col30	      VARCHAR2(32767);
 41    v_col31	      VARCHAR2(32767);
 42    v_col32	      VARCHAR2(32767);
 43    v_col33	      VARCHAR2(32767);
 44    v_col34	      VARCHAR2(32767);
 45    v_col35	      VARCHAR2(32767);
 46    v_col36	      VARCHAR2(32767);
 47    v_col37	      VARCHAR2(32767);
 48    v_col38	      VARCHAR2(32767);
 49    v_col39	      VARCHAR2(32767);
 50  BEGIN
 51    DBMS_LOB.FILEOPEN (v_bfile);
 52    DBMS_LOB.CREATETEMPORARY (v_clob, TRUE);
 53    DBMS_LOB.LOADCLOBFROMFILE
 54  	 (v_clob,
 55  	  v_bfile,
 56  	  DBMS_LOB.GETLENGTH (v_bfile),
 57  	  v_dest_offset,
 58  	  v_src_offset,
 59  	  v_src_csid,
 60  	  v_lang_context,
 61  	  v_warning);
 62    DBMS_LOB.FILECLOSE (v_bfile);
 63    v_clob := SUBSTR (v_clob, INSTR (v_clob, '=')) || '\(1)\ ';
 64    v_clob := SUBSTR (v_clob, INSTR (v_clob, '\') + 1);
 65    WHILE DBMS_LOB.GETLENGTH (v_clob) > 3 LOOP
 66  	 v_string := SUBSTR (v_clob, 1, INSTR (v_clob, '\') - 1);
 67  	 v_col := SUBSTR (v_string, 2, INSTR (v_string, ')') - 2);
 68  	 v_string := LTRIM (SUBSTR (v_string, INSTR (v_string, ')') + 1));
 69  	 IF v_col = '1' THEN
 70  	   IF v_col1 IS NOT NULL THEN
 71  	     INSERT INTO your_table
 72  	     VALUES (v_col1, v_col2, v_col3, v_col4, v_col5, v_col6, v_col7, v_col8, v_col9, v_col10,
 73  		     v_col11, v_col12, v_col13, v_col14, v_col15, v_col16, v_col17, v_col18, v_col19, v_col20,
 74  		     v_col21, v_col22, v_col23, v_col24, v_col25, v_col26, v_col27, v_col28, v_col29, v_col30,
 75  		     v_col31, v_col32, v_col33, v_col34, v_col35, v_col36, v_col37, v_col38, v_col39);
 76  	     v_col1  := NULL;
 77  	     v_col2  := NULL;
 78  	     v_col3  := NULL;
 79  	     v_col4  := NULL;
 80  	     v_col5  := NULL;
 81  	     v_col6  := NULL;
 82  	     v_col7  := NULL;
 83  	     v_col8  := NULL;
 84  	     v_col9  := NULL;
 85  	     v_col10 := NULL;
 86  	     v_col11 := NULL;
 87  	     v_col12 := NULL;
 88  	     v_col13 := NULL;
 89  	     v_col14 := NULL;
 90  	     v_col15 := NULL;
 91  	     v_col16 := NULL;
 92  	     v_col17 := NULL;
 93  	     v_col18 := NULL;
 94  	     v_col19 := NULL;
 95  	     v_col20 := NULL;
 96  	     v_col21 := NULL;
 97  	     v_col22 := NULL;
 98  	     v_col23 := NULL;
 99  	     v_col24 := NULL;
100  	     v_col25 := NULL;
101  	     v_col26 := NULL;
102  	     v_col27 := NULL;
103  	     v_col28 := NULL;
104  	     v_col29 := NULL;
105  	     v_col30 := NULL;
106  	     v_col31 := NULL;
107  	     v_col32 := NULL;
108  	     v_col33 := NULL;
109  	     v_col34 := NULL;
110  	     v_col35 := NULL;
111  	     v_col36 := NULL;
112  	     v_col37 := NULL;
113  	     v_col38 := NULL;
114  	     v_col39 := NULL;
115  	   END IF;
116  	   v_col1 := v_string;
117  	 ELSIF v_col = '2' THEN v_col2 := v_string;
118  	 ELSIF v_col = '3' THEN v_col3 := v_string;
119  	 ELSIF v_col = '4' THEN v_col4 := v_string;
120  	 ELSIF v_col = '5' THEN v_col5 := v_string;
121  	 ELSIF v_col = '6' THEN v_col6 := v_string;
122  	 ELSIF v_col = '7' THEN v_col7 := v_string;
123  	 ELSIF v_col = '8' THEN v_col8 := v_string;
124  	 ELSIF v_col = '9' THEN v_col9 := v_string;
125  	 ELSIF v_col = '10' THEN v_col10 := v_string;
126  	 ELSIF v_col = '11' THEN v_col11 := v_string;
127  	 ELSIF v_col = '12' THEN v_col12 := v_string;
128  	 ELSIF v_col = '13' THEN v_col13 := v_string;
129  	 ELSIF v_col = '14' THEN v_col14 := v_string;
130  	 ELSIF v_col = '15' THEN v_col15 := v_string;
131  	 ELSIF v_col = '16' THEN v_col16 := v_string;
132  	 ELSIF v_col = '17' THEN v_col17 := v_string;
133  	 ELSIF v_col = '18' THEN v_col18 := v_string;
134  	 ELSIF v_col = '19' THEN v_col19 := v_string;
135  	 ELSIF v_col = '20' THEN v_col20 := v_string;
136  	 ELSIF v_col = '21' THEN v_col21 := v_string;
137  	 ELSIF v_col = '22' THEN v_col22 := v_string;
138  	 ELSIF v_col = '23' THEN v_col23 := v_string;
139  	 ELSIF v_col = '24' THEN v_col24 := v_string;
140  	 ELSIF v_col = '25' THEN v_col25 := v_string;
141  	 ELSIF v_col = '26' THEN v_col26 := v_string;
142  	 ELSIF v_col = '27' THEN v_col27 := v_string;
143  	 ELSIF v_col = '28' THEN v_col28 := v_string;
144  	 ELSIF v_col = '29' THEN v_col29 := v_string;
145  	 ELSIF v_col = '30' THEN v_col30 := v_string;
146  	 ELSIF v_col = '31' THEN v_col31 := v_string;
147  	 ELSIF v_col = '32' THEN v_col32 := v_string;
148  	 ELSIF v_col = '33' THEN v_col33 := v_string;
149  	 ELSIF v_col = '34' THEN v_col34 := v_string;
150  	 ELSIF v_col = '35' THEN v_col35 := v_string;
151  	 ELSIF v_col = '36' THEN v_col36 := v_string;
152  	 ELSIF v_col = '37' THEN v_col37 := v_string;
153  	 ELSIF v_col = '38' THEN v_col38 := v_string;
154  	 ELSIF v_col = '39' THEN v_col39 := v_string;
155  	 END IF;
156  	 v_clob := SUBSTR (v_clob, INSTR (v_clob, '\') + 1);
157    END LOOP;
158  END;
159  /

PL/SQL procedure successfully completed.

scott@ORA92> COLUMN col1  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col2  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col3  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col4  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col5  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col6  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col7  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col8  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col9  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col10 FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col11  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col12  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col13  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col14  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col15  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col16  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col17  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col18  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col19  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col20 FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col21  FORMAT A50 WORD_WRAPPED
scott@ORA92> COLUMN col22  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col23  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col24  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col25  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col26  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col27  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col28  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col29  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col30 FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col31  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col32  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col33  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col34  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col35  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col36  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col37  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col38  FORMAT A10 WORD_WRAPPED
scott@ORA92> COLUMN col39  FORMAT A10 WORD_WRAPPED
scott@ORA92> SET LINESIZE 500
scott@ORA92> SELECT * FROM your_table
  2  /

COL1       COL2       COL3       COL4       COL5       COL6       COL7       COL8       COL9       COL10      COL11      COL12      COL13      COL14      COL15      COL16      COL17      COL18      COL19      COL20      COL21                                              COL22      COL23      COL24      COL25      COL26      COL27      COL28      COL29      COL30      COL31      COL32      COL33      COL34      COL35      COL36      COL37      COL38      COL39
---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- -------------------------------------------------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
NT-53556              Unclassifi            01 -                             Availabili na         Radar      01 Mar     NTIAC                 JOURNAL    5 Page(s)                                              Shoukry,   A neural network based on the learning vector      N--(U)     ADD339501  Published                        na                                                                                                                       yes        George
NT53556               ed                    APPROVED                         ty:                   Signal     1996                             ARTICLES                                                          Samir N.   quantization (LVQ) technique is applied for the    ISSN                  by                                                                                                                                                                   Matzkanin

                                            FOR PUBLIC                       Published             Interpreta                                                                                                    Martinelli classification of radar echo waveforms obtained    0025-5327,            American
                                            RELEASE 21                       in                    tion Using                                                                                                    , David    from concrete bridge deck specimens with varying   BRIDGES,              Society
                                            - JOURNAL                        'Materials            Neural                                                                                                        Varadaraja internal defects. A randomly chosen set of as      CONCRETE,             for
                                            ARTICLES                         Evaluation            Network                                                                                                       n,         measured (raw) time-domain echo-signals was used   GROUND                Nondestruc
                                            ANNOUNCEME                       '; 54,3;              for Defect                                                                                                    Srinivas   in training the network to classify waveforms into PENETRATIN            tive
                                            NT ONLY                          March                 Detection                                                                                                     T. Halabe, those representing defective and nondefective      G RADAR,              Testing,
                                                                             1996;                 in                                                                                                            Udaya B.   conditions in the concreprompt te specimens. The   INFRASTRUC            1711
                                                                             393-397;              Concrete,                                                                                                                same set of waveforms as preprocessed by           TURE,                 Arlingate
                                                                             10 refs.                                                                                                                                       subtracting the reference noise signal and was     NEURAL                Lane, P.O.
                                                                             (Copies                                                                                                                                        again separately used to train the networks.       NETWORKS.;            Box 28518,
                                                                             not                                                                                                                                            Different versions of LVQ algorithms were used                           Columbus,
                                                                             available                                                                                                                                      independently in training, and the best results in                       OH
                                                                             from                                                                                                                                           terms of the recognition accuracy were obtained by                       43228-0518
                                                                             NTIAC/DTIC                                                                                                                                     training using the OLVQ (optimized LVQ) algorithm.                       .
                                                                             ).                                                                                                                                             The OVLQ trained neural network was able to
                                                                                                                                                                                                                            classify an independent set of test waveforms with
                                                                                                                                                                                                                            a higher degree of accuracy than those trained
                                                                                                                                                                                                                            with other variants of LVQ algorithms. It has been
                                                                                                                                                                                                                            observed that the subtraction of the reference
                                                                                                                                                                                                                            noise component (preprocessing of the time domain
                                                                                                                                                                                                                            signal) had no effect on the performance of the
                                                                                                                                                                                                                            correct recognition of the OVLQ network. The
                                                                                                                                                                                                                            performance of the network indicates its high
                                                                                                                                                                                                                            potential for use in the analysis and
                                                                                                                                                                                                                            interpretation of raw radar echo waveforms. This
                                                                                                                                                                                                                            technique also holds promise for successful
                                                                                                                                                                                                                            classification of radar waveforms into classes
                                                                                                                                                                                                                            that represent specific kind of internal defects
                                                                                                                                                                                                                            in concretprompt e specimens such as cracks,
                                                                                                                                                                                                                            delaminations, voids, etc. (Author).

NT-53555              Unclassifi            01 -                             Availabili            Optimal    01 Mar     NTIAC                 JOURNAL    7 Page(s)                                              Kowsika,   The manufacturing process variables significantly  N--(U)                                                 na
NT53555               ed                    APPROVED                         ty:                   Pultrusion 1996                             ARTICLES                                                          Murthy V.  influence the mechanical properties of pultruded   ISSN
                                            FOR PUBLIC                       Published             Process                                                                                                       Mantena,   composites. In this study, a statistical central   0025-5327,
                                            RELEASE 21                       in                    Conditions                                                                                                    P. Raju    composite design (CCD) test pattern has been used  COMPOSITES
                                            - JOURNAL                        'Materials            for                                                                                                                      to manufacture unidirectional graphite-epoxy       , DAMPING,
                                            ARTICLES                         Evaluation            Improving                                                                                                                pultruded composite beams under carefully          FLEXURE,
                                            ANNOUNCEME                       '; 54,3;              the                                                                                                                      controlled process conditions.
                    GRAPHITE
                                            NT ONLY                          March                 Dynamic                                                                                                                                                                     EPOXY,
                                                                             1996;                 Properties                                                                                                                                                                  PULTRUSION
                                                                             386-392;              of                                                                                                                                                                          ,
                                                                             16 refs.              Graphite-E                                                                                                                                                                  REGRESSION
                                                                             (Copies               poxy                                                                                                                                                                        ANALYSIS,
                                                                             not                   Composite                                                                                                                                                                   VIBRATION
                                                                             available             Beams,                                                                                                                                                                      ANALYSIS,
                                                                             from                                                                                                                                                                                              MATHEMATIC
                                                                             NTIAC/DTIC                                                                                                                                                                                        AL
                                                                             ).                                                                                                                                                                                                MODELS.;


scott@ORA92> 


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