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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>FUNDAMENTALS AND PROBLEMS IN COLOR' II. ANALYTICAL ASPECTS OF COLOR SPECTROPHOTOMETRY FOR THE ANALYSIS AND DESCRIPTION OF COLOR</title>
      <link>https://trid.trb.org/View/134378</link>
      <description><![CDATA[A SPECTROPHOTOMETRIC CURVE IS, IN ITSELF, NOT A DESCRIPTION OF COLOR. COLOR DEPENDS ON THE NATURE OF THE LIGHT INCIDENT ON THE OBJECT, ON THE NATURE OF THE OBJECT, AND ON THE CHARACTERISTICS OF THE OBSERVER RESPONSE. SPECTROPHOTOMETRY SERVES TO DESCRIBE EACH OF THESE CONTRIBUTING FACTORS IN TERMS OF NARROW SPECTRAL REGIONS, SO THAT CHANGES IN THE TOTAL COLOR CAN BE COMPUTED, PREDICTED, OR ANALYZED. THIS PAPER WILL BE CONCERNED ONLY WITH THE SPECTRAL CURVE OF THE OBJECT AND HOW THIS INFORMATION CAN BE HELPFUL AND USEFUL FOR SOLVING PROBLEMS ENCOUNTERED IN THE PAINT INDUSTRY. THE APPLICATION OF SPECTROPHOTOMETRIC CURVE INFORMATION IS VALUABLE FOR TWO PURPOSES' /1/ THE DESCRIPTION OF COLOR, AND /2/ THE ANALYSIS OF THE NATURE OF THE OBJECT. BOTH ARE ANALYTICAL IN NATURE. A SERIES OF EXAMPLES OF THE APPLICATION OF SPECTROPHOTOMETRIC TECHNIQUE TO SPECIFIC PROBLEMS ENCOUNTERED IN THE PAINT INDUSTRY ARE GIVEN. /AUTHOR/]]></description>
      <pubDate>Thu, 15 Sep 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/134378</guid>
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    <item>
      <title>RANDOM LOAD FATIGUE TESTING: A STATE OF THE ART SURVEY</title>
      <link>https://trid.trb.org/View/106783</link>
      <description><![CDATA[NEW TECHNIQUES FOR THE EVALUATION OF FATIGUE LIFE FOR METAL STRUCTURES ARE ANALYZED. THE TECHNIQUE FOR CONTINUOUS LOAD ANALYSIS, REFERRED TO AS PSD ANALYSIS (AFTER THE POWER SPECTRAL DENSITY PLOT WHICH RESULTS) IS BECOMING RECOGNIZED AS A VALID APPROACH TO THE DELINEATION OF FATIGUE LOADS. THE PSD PROFILE IS THE RESPONSE IN STRESS OF A STUCTURE TO UNIT ENERGY SINEWAVE EXCITATION AT EACH FREQUENCY, OVER THE FREQUENCY RANGE OF INTEREST IN SERVICE LOADING. ONCE THE SERVICE LOADS HAVE BEEN ANALYZED, THE FATIGUE ENGINEER USES ONE OF THE FOLLOWING FOUR DIFFERENT METHODS TO FIND A STATISTICALLY-DEFINED LOAD SPECTRUM FOR THE VEHICLE IN QUESTION: (1) CUMULATIVE DAMAGE THEORY WITH CONSTANT AMPLITUDE S/N CURVES FROM TESTS, OR FROM THE LITERATURE, (2) REPEATED BLOCKS OF A PROGRAM OF CONSTANT AMPLITUDE CYCLES AT STRATIFIED STRESS LEVELS IN ARBITRARY SEQUENCE IN APPROXIMATE CONFORMITY TO THE RELATIVE FREQUENCY OF SERVICE LOADS FROM THE LOAD SPECTRUM, (3) A TEST LOADING INVOLVING GROUPS OF CONSTANT AMPLITUDE CYCLES OR INDIVIDUAL CYCLES USUALLY CALLED UP IN A COMPUTER-RANDOMIZED SEQUENCE OF VARYING LOAD LEVEL, BUT WHOSE NUMBERS AT A GIVEN LOAD LEVEL ARE PRESELECTED TO RESULT IN THE FINAL RELATVIE FREQUENCY DICTATED BY THE SERVICE LOAD SPECTRUM, AND (4) USING EITHER THE ACTUAL RANDOM PROCESS, AS WITH ACOUSTIC FATIGUE, OR WITH SAMPLES FROM SERVICE, OR AN ANALOGOUS RANDOM PROCESS WITH SIMILAR GENERAL CYCLE CORRELATION CHARACTERISTICS TO THE PROCESS IN SERVICE, EITHER AS A STATIONARY PROCESS, OR WITH THE RMS PROGRAMMED TO RESULT IN THE SAME LOAD FREQUENCY AS GIVEN BY THE LOAD SPECTRUM. THE GROWTH OF TEST DATA IN THE LAST TWO CATEGORIES IS SPECIFICALLY DESCRIBED. LITERATURE AVAILABLE IN TWO OTHER RANDOM LOAD TEST AREAS ARE DESCRIBED: ACOUSTIC FATIGUE AND RANDOM LOAD CRACK PROPAGATION. A FEW EXAMPLES ARE PRESENTED OF TESTING PRACTICAL STRUCTURES WITH BOTH STATIONARY AND PROGRAMMED RMS STRESS LEVELS. THE UNIVERSALITY OF ENDURANCES OBTAINED FOR A GIVEN MATERIAL TESTED WITH A STANDARD FREQUENCY DENSITY PROFILE (PRESENTED IN THE FORM OF AN RMS-STRESS LIFE CURVE) IS NO LESS THAN THE CORRESPONDING S-N DATA FOR THE SAME CONDITIONS. TABLES ARE INCLUDED CONCISELY, LISTING MUCH OF THE AVAILABLE RANDOM FATIGUE ENDURANCE DATA, WITH SOURCES, FOR SIMPLE SPECIMENS. NINETY PAPERS WERE FOUND TO CONTAIN RELEVANT TEST DATA, AND THE RESULTS OF APPROXIMATELY 3,000 TESTS OF VARIOUS TYPES ARE TABULATED WITH CROSS REFERENCES.]]></description>
      <pubDate>Fri, 19 Aug 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/106783</guid>
    </item>
    <item>
      <title>ANALYSIS OF ROAD ROUGHNESS RECORDS BY POWER SPECTRAL DENSITY TECHNIQUES</title>
      <link>https://trid.trb.org/View/100514</link>
      <description><![CDATA[DURING RECENT YEARS, THE ROUGHNESS CHARACTERISTICS OF A LARGE NUMBER OF AIRPORT RUNWAYS HAVE BEEN MEASURED. ROUGHNESS CONTENT WAS DEFINED BY THE POWER DENSITY FUNCTION, WHICH SHOWS THE CONTRIBUTION TO THE ROUGHNESS VARIANCE OF THE ROUGHNESS AT EACH WAVE LENGTH. THIS INVESTIGATION WAS CONDUCTED TO EXAMINE THE FEASIBILITY OF USING SIMILAR MATHEMATICAL TECHNIQUE TO DEFINE THE ROUGHNESS CONTENT OF HIGHWAY PAVEMENTS. THE MOST FUNDAMENTAL METHOD OF MEASURING PAVEMENT ROUGHNESS IS TO RECORD THE PAVEMENT ELEVATION AT SMALL INTERVALS RELATIVE TO AN ARBITRARY DATUM. THIS ELEVATION PROFILE CONSISTS OF TWO COMPONENTS' A/ A CHANGE IN ELEVATION DUE TO PAVEMENT ROUGHNESS. THE LARGE DEVIATIONS IN ELEVATION DUE TO PAVEMENT GEOMETRY TEND TO MASK THE INFORMATION ON ROUGHNESS CONTENT CONTAINED IN THE PROFILE. TO OVERCOME THIS, THE ELEVATION PROFILES MUST BE FILTERED SO THAT THE TRANSFORMED PROFILE CONTAINS THE INFORMATION ONLY ON ROUGHNESS. OF THREE FILTERING PROCEDURES EXAMINED, THE MOST FEASIBLE APPEARS TO BE THAT BASED ON THE SUBTRACTION OF THE MOVING AVERAGE. HOWEVER, THE FULL IMPLICATIONS OF THIS TYPE OF PROCEDURE ARE NOT CLEARLY UNDERSTOOD. THE TECHNIQUES EXAMINED IN THIS INVESTIGATION AND THE ASSOCIATED COMPUTER PROGRAMS PROVIDED A SYSTEMATIC FRAMEWORK FOR THE EXAMINATION OF THE LONGITUDINAL ROUGHNESS CHARACTERISTICS OF HIGHWAY PAVEMENTS TO DETERMINE PAVEMENT SERVICEABILITY AND EVALUATE ROUGHNESS MEASURING DEVICES.]]></description>
      <pubDate>Tue, 16 Aug 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/100514</guid>
    </item>
    <item>
      <title>USE OF ULTRAVIOLET SPECTROSCOPY TO DETECT ADULTERATION OF TRAFFIC PAINT VEHICLES</title>
      <link>https://trid.trb.org/View/106561</link>
      <description><![CDATA[BASED ON THE MATERIALS INVESTIGATED, AN ULTRAVIOLET SPECTROSCOPIC METHOD FOR DETECTING ADULTERATION OF TRAFFIC PAINT VEHICLES IN AMOUNTS AS LOW AS 2 TO 5 PER CENT BY WEIGHT OF THE VEHICLE SOLIDS IS REPORTED. THE METHOD IS APPLICABLE TO THE MONITORING OF PURCHASED LOTS OF TRAFFIC PAINT AFTER A REFERENCE SAMPLE HAS BEEN ROAD TESTED AND FOUND ACCEPTABLE FOR USE. THE PAINT PIGMENT IS REMOVED BY CENTRIFUGING, A SEPARATE DETERMINATION OF NON-VOLATILE SOLIDS IS MADE, AND THE ORIGINAL SOLVENTS ARE THEN REMOVED FROM A WEIGHED SAMPLE OF THE VEHICLE. USING A SPECTRAL GRADE OF CYCLOHEXANE AS A SOLVENT, SOLUTIONS OF THE VEHICLE SOLIDS ARE QUANTITATIVELY PREPARED AND THEIR ABSORBANCES ARE MEASURED IN A DOUBLE-BEAM RECORDING ULTRAVIOLET SPECTROPHOTOMETER. THE SPECTRAL CURVES AND CHARACTERISTICS OF BOTH THE REFERENCE AND PURCHASED PAINTS /VEHICLE SOLIDS/ ARE THEN COMPARED FOR UNIFORMITY OR EVIDENCE OF ADULTERATION. AN ALKYD RESIN WAS USED IN THE STUDY SINCE IT IS MOST REPRESENTATIVE OF TRAFFIC PAINT VEHICLES IN USE TODAY. PLOTS OF PERCENTAGE ADULTERANT /WOOD RESIN, HYDROCARBON RESIN, FISH OIL, AND TALL OIL/ VERSUS SPECTRAL ABSORBANCE AT 264 HANOMETERS /MILLIMICRONS/ SHOW THE EFFECT OF THE ADULTERANT. ABOUT 4 HR ARE REQUIRED FOR A SINGLE DETERMINATION. /AUTHOR/]]></description>
      <pubDate>Sun, 01 May 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/106561</guid>
    </item>
    <item>
      <title>SPECTRAL MAPPING OF SHOTGRASS PRAIRIE BIOMASS</title>
      <link>https://trid.trb.org/View/45748</link>
      <description><![CDATA[Multispectral scanner data have been processed to yield biomass maps of imagery from shortgrass prairie vegetation. The results of the image processing of these data were compared to actual biomass values measured at the time the aircraft data were acquired. The comparison demonstrated that image processing predicted 1.15 times the actual biomass present with a correlation coefficient of 0.98 for biomass ground-truth areas sampled from a flight line containing a large range of biomass values. A simple, hand-held device has been constructed which utilizes a spectral ratio between two specific wavelengths, 0.68 and 0.80 micrometers, to accurately estimate grass biomass. Several field experiments have demonstrated correlation coefficients between 0.95 to 0.98 for the hand-held device in estimating undisturbed grass canopy biomass. The hand-held device has been shown to be an accurate and expedient method for estimating grass canopy biomass. This type of device could be used to gather greater amounts of ground-truth information from overflight areas and thus would add greater statistical significance to image processing results.]]></description>
      <pubDate>Wed, 11 Aug 1976 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/45748</guid>
    </item>
    <item>
      <title>GEOLOGY AND FORESTRY CLASSIFICATION FROM ERTS-1 DIGITAL DATA</title>
      <link>https://trid.trb.org/View/35733</link>
      <description><![CDATA[Computer classifications into seven and ten classes of two areas in central Oregon of interest to geology and forestry demonstrate the extraction of information from ERTS-1 data. The area around Newberry Caldera was classified into basalt, rhyolite obsidian, pumice flats, Newberry pumice, ponderosa pine, lodgepole pine and water classes. The area around Mt. Washington was classified into two basalts, three forest, two clearcut, burn, snow, and water classes. Both also include an unclassified category. Significant details that cannot be extracted from photographic reconstitutions of the data emerge from these classifications, such as moraine locations and paleo-wind directions. Spectral signatures for the various rocks are comparable to those published elsewhere.]]></description>
      <pubDate>Fri, 14 May 1976 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/35733</guid>
    </item>
    <item>
      <title>SPECIAL COLOR ANALYSIS OF RUNWAY CONDITIONS</title>
      <link>https://trid.trb.org/View/35735</link>
      <description><![CDATA[An investigation of the condition of the runway and taxiways at Thule Air Base has been conducted by interpretation of aerial color imagery. The aerial imagery was analyzed by using a photointerpretation console that has been designed to enhance subtle spectral differences caused by phenomena such as moisture and surface cracking. The results of the analysis indicate extensive cracking and possible runway deterioration. The aerial data delineate regions of cracking or depressions over the entire runway. These data agree well with the ground survey information available, and extend definition of deterioration regions to the entire runway surgace. In addition, the aerial data indicate subsurface moisture flow patterns across the runway area that correlate well with the regions of runway cracking.]]></description>
      <pubDate>Fri, 14 May 1976 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/35735</guid>
    </item>
    <item>
      <title>X-RAY PHOTOELECTRON SPECTRA OF C(1S ORBITAL) AND O(1S ORBITAL) IN CARBONATE MINERALS</title>
      <link>https://trid.trb.org/View/39781</link>
      <description><![CDATA[X-ray photoelectron spectra of C(1S orbital) and O(1S orbital) lines in various carbonate minerals illustrate that, as covalency increases, the O (1S orbital) binding energies also increase in calcite, magnesite, and otavite, but decrease in aragonite, strontianite, and witherite.  No increase in binding energy could be detected for possible 2P-2P, pi bonding in aragonites and no increase in line-width was detected for O or C from the two sites in dolomite. /AUTHOR/]]></description>
      <pubDate>Tue, 29 Jul 1975 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/39781</guid>
    </item>
    <item>
      <title>IN SITU ROCK REFLECTANCE</title>
      <link>https://trid.trb.org/View/38935</link>
      <description><![CDATA[The purposes of this paper are to summarize, generalize and give a statistical model of sedimentary rock reflectance data measured in situ.  The data consist of more than 8600 measurements along the Front Range of Colorado.  The typical spectral reflectance curve for a geologic formation shows a gradual increase of spectral reflectance with increasing wavelength.  Extrapolation of measured values from one area to another is valid; however, the geologic exposure may change and must be considered for best filter selection.  Statistically, band reflectance measurements can be considered to be from a normally distributed population with a minimum standard deviation of 0.042. From a statistical consideration of the observed differences in contrast-ratio and the number of reflectance measurements per band per formation necessary to discriminate these differences, it is concluded that "best" spectral bands cannot be selected with sufficient confidence in a practical manner with current techniques and equipment.  /Author/]]></description>
      <pubDate>Wed, 02 Jul 1975 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/38935</guid>
    </item>
    <item>
      <title>MULTISECTRAL SENSING OF FOREST TREE SPECIES</title>
      <link>https://trid.trb.org/View/92575</link>
      <description><![CDATA[COMPUTER RECOGNITION OF FOREST TREE SPECIES AT THE NASA-ANN ARBOR FORESTRY TEST SITE HAS BEEN ACCOMPLISHED USING DATA COLLECTED IN SIX SPECTRAL REGIONS BETWEEN 0.4 AND 1.0 MICROMETERS. THE SIX WAVELENGTH BANDS USED WERE SELECTED ON THE BASIS OF LABORATORY REFLECTANCE DATA PREVIOUSLY COLLECTED BY THE AUTHORS. DATA OBTAINED WITH THE UNIVERSITY OF MICHIGAN C-47 AIRCRAFT AND PROCESSED WITH THE UNIVERSITY OF MICHIGAN SPECTRAL ANALYSIS AND RECOGNITION COMPUTER (SPARC), PROVIDED SUCCESSFUL SEPARATION OF CONIFEROUS AND BROADLEAVE TREES. SPECIFIC RECOGNITION AND SEPARATION OF SUGAR MAPLE, BLACK WALNUT, BLACK LOCUST, RED OAK, AND WHITE OAK WERE ALSO SUCCESSFUL. DISCRIMINATION AMONG CONIFERS WAS NOT SO SUCCESSFUL AS FOR BROADLEAVED SPECIES, BUT SPRUCE WERE CONSISTENTLY SEPARATED FROM PINE.]]></description>
      <pubDate>Wed, 15 Aug 1973 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/92575</guid>
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