{"id":495,"date":"2009-04-17T13:29:42","date_gmt":"2009-04-17T17:29:42","guid":{"rendered":"http:\/\/testing.coalpetrography.com\/wordpress\/?page_id=495"},"modified":"2013-02-05T14:32:26","modified_gmt":"2013-02-05T18:32:26","slug":"steam-coal-calorific-value-vitrinite-reflectance","status":"publish","type":"page","link":"https:\/\/www.coalpetrography.com\/blog1\/steam-coal-calorific-value-vitrinite-reflectance\/","title":{"rendered":"Steam Coal"},"content":{"rendered":"<p>Steam coals cover a broad range of coal ranks, calorific values, and geological ages, as shown in the graph below (Figure 1),<\/p>\n<div id=\"attachment_963\" style=\"width: 557px\" class=\"wp-caption alignright\"><a href=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvvsran2.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-963\" src=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvvsran2.jpg\" alt=\"Fig. (1) Calorific Value Versus Vitrinite Reflectance\" title=\"cvvsran2\" width=\"547\" height=\"424\" class=\"size-full wp-image-963\" srcset=\"https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvvsran2.jpg 547w, https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvvsran2-300x232.jpg 300w\" sizes=\"auto, (max-width: 547px) 100vw, 547px\" \/><\/a><p id=\"caption-attachment-963\" class=\"wp-caption-text\">Fig. (1) Calorific Value Versus Vitrinite Reflectance<\/p><\/div>\n<p>which is a compilation plot of about 470 individual coals, of wide geographic- and age-distribution from the United States, plotted in terms of their random Vitrinite reflectance, calorific value (in BTU&#8217;s\/lb), and ASTM coal-rank category.\u00a0 (From Penn. State University coal database, courtesy of\u00a0 Gary Mitchell).<\/p>\n<div id=\"attachment_965\" style=\"width: 638px\" class=\"wp-caption alignright\"><a href=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/fuelrat1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-965\" src=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/fuelrat1.jpg\" alt=\"Fig. (2) Fuel Ratio versus Vitrinite reflectance\" title=\"fuelrat1\" width=\"628\" height=\"478\" class=\"size-full wp-image-965\" srcset=\"https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/fuelrat1.jpg 628w, https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/fuelrat1-300x228.jpg 300w\" sizes=\"auto, (max-width: 628px) 100vw, 628px\" \/><\/a><p id=\"caption-attachment-965\" class=\"wp-caption-text\">Fuel Ratio versus Vitrinite reflectance<\/p><\/div>\n<p>Steam coals with different properties are often mixed together, leveraging the high reactivity of the lower coal ranks with the higher fuel ratio of the higher ranks, and what is delivered to the boiler is a blend.<\/p>\n<p>Figure 2 illustrates the two sets of participants in this blending route. Coals with random reflectances below 0.60% have higher reactivities than would be expected from the linear regression of random Vitrinite reflectance versus Fuel Ratio shown for the higher ranks of coals.<\/p>\n<p>Our on-line brochure, <a href=\"http:\/\/www.coalpetrography.com\/library\/pdf\/SteamCoal.pdf\">Fingerprinting Coals &amp; Blends<\/a>, shows how automated Reflectance Profiling is used to characterize the inbound train- or barge-cargoes, and confirm the consistency of delivered fuel. Fingerprinting is also used to determine blend proportions, from which the calorific value of the boiler-charge can be predicted, as shown in Figure 3.<\/p>\n<div id=\"attachment_966\" style=\"width: 575px\" class=\"wp-caption alignright\"><a href=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvprediction1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-966\" src=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvprediction1.jpg\" alt=\"Fig. (3) Prediction of a Blend Calorific Value\" title=\"cvprediction1\" width=\"565\" height=\"447\" class=\"size-full wp-image-966\" srcset=\"https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvprediction1.jpg 565w, https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/cvprediction1-300x237.jpg 300w\" sizes=\"auto, (max-width: 565px) 100vw, 565px\" \/><\/a><p id=\"caption-attachment-966\" class=\"wp-caption-text\">Fig. (3) Prediction of a Blend Calorific Value<\/p><\/div>\n<p>A simple estimate of coal reactivity and carbon burnout of coals can be made from the fuel ratio, but another, for the individual component coals in a blend, is given by the proportion of each coal with greater than 1.65% reflectance. This is determined from Probability plots, as shown in Figure 4. As noted by others, burnout among bituminous coals increases with rank.<\/p>\n<div id=\"attachment_967\" style=\"width: 486px\" class=\"wp-caption alignright\"><a href=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/burnoutpredict1.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-967\" src=\"http:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/burnoutpredict1.jpg\" alt=\"Fig. (4) Burnout Prediction using probability plots\" title=\"burnoutpredict1\" width=\"476\" height=\"377\" class=\"size-full wp-image-967\" srcset=\"https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/burnoutpredict1.jpg 476w, https:\/\/www.coalpetrography.com\/blog1\/wp-content\/uploads\/2009\/04\/burnoutpredict1-300x237.jpg 300w\" sizes=\"auto, (max-width: 476px) 100vw, 476px\" \/><\/a><p id=\"caption-attachment-967\" class=\"wp-caption-text\">Fig. (4) Burnout Prediction <\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Steam coals cover a broad range of coal ranks, calorific values, and geological ages, as shown in the graph below (Figure 1), which is a compilation plot o<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-495","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/pages\/495","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/comments?post=495"}],"version-history":[{"count":11,"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/pages\/495\/revisions"}],"predecessor-version":[{"id":1420,"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/pages\/495\/revisions\/1420"}],"wp:attachment":[{"href":"https:\/\/www.coalpetrography.com\/blog1\/wp-json\/wp\/v2\/media?parent=495"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}