High Temperature Erosion Modeling in Particle Based CSP Systems Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.2172/1677501
1. Introduction. Wear and erosion damage of materials from solid particle and surface interactions is a major issue in various industries. Although more common in mining and oil and gas production, erosion is becoming a critical issue in renewable technologies as well such as particle based concentrated solar thermal power (CSP) systems. In particle based CSP systems, solid particles are used to absorb solar energy and as thermal storage. However, these particles may cause significant amount of wear to system components while through the system at high temperatures. This damage can be costly, and therefore, requires a greater understanding of solid particle erosion in CSP systems. Throughout the years, models and tools have been developed to predict and control erosion in industries such as oil and gas production. However, these erosion models and erosion prediction tools have been mainly developed based on erosion data for much higher velocities and lower temperatures, i.e. the operating conditions for which the existing models have been built are not pertinent to those expected in CSP system. It is known that erosion depends on many factors such as material properties, erodent particle properties, and particle impact speed and angle. However, the effect of temperature on erosion is not vastly investigated. In this work, a temperature-based correlation is introduced that will be used to modify the existing erosion models to predict erosion rates at velocities and temperatures relevant to Gen3 CSP systems. The existing models are first validated against erosion experiments run at low temperatures and low velocities. Subsequently, a temperature correction term is developed that can extend the existing models to high temperatures, based on the available experimental data showing the effect of temperature on impact erosion. 2. Erosion Models. Continuing sequence of impacts from solid particles on surfaces would result in loss of material due to mechanical interaction between solid surface and particles. Erosion equations have been developed to predict erosion under different conditions and erosion mechanism, including cutting and deformation erosion. These models are mainly either mechanistic, empirical, and semi-mechanistic models, when the latter combine the theory of the erosion mechanism and particle motion with the available experimental data. One of the first empirical correlation was introduced by American Petroleum Institute (API) Recommended Practice (RP) 14E [1]. This correlation was very conservative, and several improved empirical and semi-mechanistic equations were developed in the years following. More recently, the models introduced by Erosion/Corrosion Research Center (E/CRC) at the University of Tulsa and Arabnejad. et al. [2] are frequently used in the literature and industry, as they account for many parameters affecting erosion including particle impact speed and angle, material density and hardness, and particle size and shape. However, both these models were developed based on data at relatively high velocities and also do not take into account any mechanical changes in material associated with thermal cycling at high temperatures. 3. Erosion Prediction at High Temperatures. In this work, the accuracy of Arabnejad et al. model and E/CRC model is investigated to predict impact erosion at conditions relevant to Gen3 CSP systems. Two significant deviations expected in Gen3 systems compared to operating conditions used to build these models are particle impact velocities and system temperature. As a first step, the performance of these models was validated at low velocities and temperatures. Impact erosion experiments were conducted on SS316 coupons using HSP 40/70 ceramic particles. Assuming particle rate of 1 kg/s/m, 0.0254 m of particle curtain thickness, and particle velocity of 1.5 m/s in the system, an overall erosion of 0.59 mm/year was calculated. The experimental results were subsequently compared to those from computational simulations and erosion of 0.47 mm/year was obtained using the Arabnejad et al. model. The results indicated that the models work well at low velocities and low temperature conditions. To account for temperature effect, a mathematical correlation was developed using data published by DUCOM [3] for Inconel 600 eroded by alumina particles at high velocities. The correlation was applied to both Arabnejad et. al model and the E/CRC model. The prediction results from these modified models were within 20% of this experimental data. Predictions of of erosion by the modified E/CRC model at three different temperatures are made. Similar to the calculation at low temperature, a typical CSP system with 1 kg/s/m of particle flow rate per unit length of the particle curtain and a curtain thickness of 0.0254 m is assumed. The annual thickness loss calculations were run for different particle impact velocities, assuming a uniform particle impact area equal to the cross-sectional area of the curtain (particle-particle interactions and dispersion of particles are not considered in obtaining the results). It is observed that erosion increases exponentially as temperature increases. Furthermore, it is also noted that, erosion changes non-linearly with impact velocity. Currently, experiments are also being conducted to measure erosion of SS316 at 800 ºC with HSP 40/70 particles at low impact velocities. We expect to use the results from high temperature testing to further improve the temperature correlation function. Similar models are also being developed for abrasion erosion resulting from particle sliding along the surfaces as well as attrition from particle to particle and particle to surface interactions. References. [1] Institute, A. P. (1991). API Recommended Practice for Design and Installation of Offshore Production Platform Piping System, API RP 14E. [2] Arabnejad, H., Mansouri, A., Shirazi, S. A., and McLaury, B. S. (2015a). Development of mechanistic erosion equation for solid particles. Wear, 332–333, 1044–1050. http://doi.org/10.1016/j.wear.2015.01.031. [3] https://ducom.com/high-temperature-erosion-evaluating-sample-wear/
Related Topics
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.2172/1677501
- OA Status
- green
- Cited By
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- OpenAlex ID
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4390600532Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2172/1677501Digital Object Identifier
- Title
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High Temperature Erosion Modeling in Particle Based CSP SystemsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-09-29Full publication date if available
- Authors
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Soroor Karimi, Evan Gietzen, Nipun Goel, Siamack A. Shirazi, Michael W. Keller, Todd OtanicarList of authors in order
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https://doi.org/10.2172/1677501Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/1677501Direct OA link when available
- Concepts
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Erosion, Computer science, Particle (ecology), Environmental science, Geology, Geomorphology, OceanographyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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| abstract_inverted_index.on | 141, 178, 199, 269, 279, 292, 450, 551 |
| abstract_inverted_index.to | 61, 78, 115, 166, 217, 223, 232, 265, 301, 314, 496, 503, 515, 519, 594, 657, 697, 749, 797, 815, 823, 852, 856 |
| abstract_inverted_index.1.5 | 575 |
| abstract_inverted_index.14E | 372 |
| abstract_inverted_index.20% | 676 |
| abstract_inverted_index.600 | 645 |
| abstract_inverted_index.800 | 803 |
| abstract_inverted_index.A., | 885, 888 |
| abstract_inverted_index.API | 865, 878 |
| abstract_inverted_index.CSP | 55, 104, 170, 234, 505, 705 |
| abstract_inverted_index.H., | 883 |
| abstract_inverted_index.HSP | 555, 806 |
| abstract_inverted_index.One | 356 |
| abstract_inverted_index.The | 236, 588, 612, 653, 667, 730 |
| abstract_inverted_index.Two | 507 |
| abstract_inverted_index.[1] | 860 |
| abstract_inverted_index.[2] | 411, 881 |
| abstract_inverted_index.[3] | 642, 906 |
| abstract_inverted_index.al. | 410, 489, 610 |
| abstract_inverted_index.and | 3, 11, 26, 28, 65, 93, 110, 117, 125, 132, 148, 188, 192, 229, 249, 307, 320, 325, 335, 348, 379, 383, 407, 418, 432, 436, 438, 441, 456, 491, 527, 544, 571, 599, 623, 663, 721, 758, 854, 870, 889 |
| abstract_inverted_index.any | 463 |
| abstract_inverted_index.are | 59, 163, 239, 330, 412, 523, 694, 762, 793, 832 |
| abstract_inverted_index.can | 90, 260 |
| abstract_inverted_index.due | 300 |
| abstract_inverted_index.et. | 660 |
| abstract_inverted_index.for | 144, 155, 423, 629, 643, 737, 836, 868, 899 |
| abstract_inverted_index.gas | 29, 126 |
| abstract_inverted_index.low | 247, 250, 542, 621, 624, 701, 810 |
| abstract_inverted_index.m/s | 576 |
| abstract_inverted_index.may | 72 |
| abstract_inverted_index.not | 164, 202, 459, 763 |
| abstract_inverted_index.oil | 27, 124 |
| abstract_inverted_index.per | 714 |
| abstract_inverted_index.run | 245, 736 |
| abstract_inverted_index.the | 83, 107, 152, 157, 195, 219, 262, 270, 275, 339, 342, 345, 352, 358, 389, 394, 403, 416, 484, 534, 578, 607, 616, 664, 686, 698, 718, 750, 754, 767, 817, 826, 844 |
| abstract_inverted_index.use | 816 |
| abstract_inverted_index.was | 362, 376, 539, 586, 604, 635, 655 |
| abstract_inverted_index.ºC | 804 |
| abstract_inverted_index.(RP) | 371 |
| abstract_inverted_index.0.47 | 602 |
| abstract_inverted_index.0.59 | 584 |
| abstract_inverted_index.14E. | 880 |
| abstract_inverted_index.Gen3 | 233, 504, 512 |
| abstract_inverted_index.High | 479 |
| abstract_inverted_index.More | 392 |
| abstract_inverted_index.This | 88, 374 |
| abstract_inverted_index.Wear | 2 |
| abstract_inverted_index.[1]. | 373 |
| abstract_inverted_index.also | 457, 782, 794, 833 |
| abstract_inverted_index.area | 747, 752 |
| abstract_inverted_index.been | 113, 137, 161, 312 |
| abstract_inverted_index.both | 444, 658 |
| abstract_inverted_index.data | 143, 273, 451, 638 |
| abstract_inverted_index.flow | 712 |
| abstract_inverted_index.from | 8, 289, 596, 670, 819, 840, 850 |
| abstract_inverted_index.have | 112, 136, 160, 311 |
| abstract_inverted_index.high | 86, 266, 454, 473, 651, 820 |
| abstract_inverted_index.i.e. | 151 |
| abstract_inverted_index.into | 461 |
| abstract_inverted_index.loss | 297, 733 |
| abstract_inverted_index.many | 179, 424 |
| abstract_inverted_index.more | 22 |
| abstract_inverted_index.much | 145 |
| abstract_inverted_index.rate | 561, 713 |
| abstract_inverted_index.size | 440 |
| abstract_inverted_index.such | 42, 122, 181 |
| abstract_inverted_index.take | 460 |
| abstract_inverted_index.term | 256 |
| abstract_inverted_index.that | 175, 213, 259, 615, 772 |
| abstract_inverted_index.they | 421 |
| abstract_inverted_index.this | 206, 482, 678 |
| abstract_inverted_index.unit | 715 |
| abstract_inverted_index.used | 60, 216, 414, 518 |
| abstract_inverted_index.very | 377 |
| abstract_inverted_index.wear | 77 |
| abstract_inverted_index.well | 41, 619, 847 |
| abstract_inverted_index.were | 386, 447, 549, 591, 674, 735 |
| abstract_inverted_index.when | 338 |
| abstract_inverted_index.will | 214 |
| abstract_inverted_index.with | 351, 469, 707, 788, 805 |
| abstract_inverted_index.work | 618 |
| abstract_inverted_index.(API) | 368 |
| abstract_inverted_index.(CSP) | 50 |
| abstract_inverted_index.40/70 | 556, 807 |
| abstract_inverted_index.DUCOM | 641 |
| abstract_inverted_index.E/CRC | 492, 665, 688 |
| abstract_inverted_index.SS316 | 552, 801 |
| abstract_inverted_index.These | 328 |
| abstract_inverted_index.Tulsa | 406 |
| abstract_inverted_index.Wear, | 902 |
| abstract_inverted_index.along | 843 |
| abstract_inverted_index.based | 45, 54, 140, 268, 449 |
| abstract_inverted_index.being | 795, 834 |
| abstract_inverted_index.build | 520 |
| abstract_inverted_index.built | 162 |
| abstract_inverted_index.cause | 73 |
| abstract_inverted_index.data. | 355, 680 |
| abstract_inverted_index.equal | 748 |
| abstract_inverted_index.first | 240, 359, 532 |
| abstract_inverted_index.issue | 17, 36 |
| abstract_inverted_index.known | 174 |
| abstract_inverted_index.lower | 149 |
| abstract_inverted_index.made. | 695 |
| abstract_inverted_index.major | 16 |
| abstract_inverted_index.model | 490, 493, 662, 689 |
| abstract_inverted_index.noted | 783 |
| abstract_inverted_index.power | 49 |
| abstract_inverted_index.rates | 226 |
| abstract_inverted_index.solar | 47, 63 |
| abstract_inverted_index.solid | 9, 57, 100, 290, 305, 900 |
| abstract_inverted_index.speed | 191, 431 |
| abstract_inverted_index.step, | 533 |
| abstract_inverted_index.that, | 784 |
| abstract_inverted_index.these | 70, 129, 445, 521, 537, 671 |
| abstract_inverted_index.those | 167, 595 |
| abstract_inverted_index.three | 691 |
| abstract_inverted_index.tools | 111, 135 |
| abstract_inverted_index.under | 317 |
| abstract_inverted_index.using | 554, 606, 637 |
| abstract_inverted_index.which | 156 |
| abstract_inverted_index.while | 81 |
| abstract_inverted_index.work, | 207, 483 |
| abstract_inverted_index.would | 294 |
| abstract_inverted_index.years | 390 |
| abstract_inverted_index.0.0254 | 565, 726 |
| abstract_inverted_index.Center | 400 |
| abstract_inverted_index.Design | 869 |
| abstract_inverted_index.Impact | 546 |
| abstract_inverted_index.Piping | 876 |
| abstract_inverted_index.absorb | 62 |
| abstract_inverted_index.amount | 75 |
| abstract_inverted_index.angle, | 433 |
| abstract_inverted_index.angle. | 193 |
| abstract_inverted_index.annual | 731 |
| abstract_inverted_index.common | 23 |
| abstract_inverted_index.damage | 5, 89 |
| abstract_inverted_index.effect | 196, 276 |
| abstract_inverted_index.either | 332 |
| abstract_inverted_index.energy | 64 |
| abstract_inverted_index.eroded | 646 |
| abstract_inverted_index.expect | 814 |
| abstract_inverted_index.extend | 261 |
| abstract_inverted_index.higher | 146 |
| abstract_inverted_index.impact | 190, 280, 430, 498, 525, 740, 746, 789, 811 |
| abstract_inverted_index.kg/s/m | 709 |
| abstract_inverted_index.latter | 340 |
| abstract_inverted_index.length | 716 |
| abstract_inverted_index.mainly | 138, 331 |
| abstract_inverted_index.mining | 25 |
| abstract_inverted_index.model. | 611, 666 |
| abstract_inverted_index.models | 109, 131, 159, 222, 238, 264, 329, 395, 446, 522, 538, 617, 673, 831 |
| abstract_inverted_index.modify | 218 |
| abstract_inverted_index.motion | 350 |
| abstract_inverted_index.result | 295 |
| abstract_inverted_index.shape. | 442 |
| abstract_inverted_index.system | 79, 84, 528, 706 |
| abstract_inverted_index.theory | 343 |
| abstract_inverted_index.vastly | 203 |
| abstract_inverted_index.within | 675 |
| abstract_inverted_index.years, | 108 |
| abstract_inverted_index.(1991). | 864 |
| abstract_inverted_index.(E/CRC) | 401 |
| abstract_inverted_index.Erosion | 283, 309, 476 |
| abstract_inverted_index.Inconel | 644 |
| abstract_inverted_index.Models. | 284 |
| abstract_inverted_index.Similar | 696, 830 |
| abstract_inverted_index.System, | 877 |
| abstract_inverted_index.account | 422, 462, 628 |
| abstract_inverted_index.against | 242 |
| abstract_inverted_index.alumina | 648 |
| abstract_inverted_index.applied | 656 |
| abstract_inverted_index.between | 304 |
| abstract_inverted_index.ceramic | 557 |
| abstract_inverted_index.changes | 465, 786 |
| abstract_inverted_index.combine | 341 |
| abstract_inverted_index.control | 118 |
| abstract_inverted_index.costly, | 92 |
| abstract_inverted_index.coupons | 553 |
| abstract_inverted_index.curtain | 569, 720, 723, 755 |
| abstract_inverted_index.cutting | 324 |
| abstract_inverted_index.cycling | 471 |
| abstract_inverted_index.density | 435 |
| abstract_inverted_index.depends | 177 |
| abstract_inverted_index.effect, | 631 |
| abstract_inverted_index.erodent | 185 |
| abstract_inverted_index.erosion | 4, 31, 102, 119, 130, 133, 142, 176, 200, 221, 225, 243, 316, 321, 346, 427, 499, 547, 582, 600, 684, 773, 785, 799, 838, 897 |
| abstract_inverted_index.factors | 180 |
| abstract_inverted_index.further | 824 |
| abstract_inverted_index.greater | 97 |
| abstract_inverted_index.impacts | 288 |
| abstract_inverted_index.improve | 825 |
| abstract_inverted_index.kg/s/m, | 564 |
| abstract_inverted_index.measure | 798 |
| abstract_inverted_index.mm/year | 585, 603 |
| abstract_inverted_index.models, | 337 |
| abstract_inverted_index.overall | 581 |
| abstract_inverted_index.predict | 116, 224, 315, 497 |
| abstract_inverted_index.results | 590, 613, 669, 818 |
| abstract_inverted_index.several | 380 |
| abstract_inverted_index.showing | 274 |
| abstract_inverted_index.sliding | 842 |
| abstract_inverted_index.surface | 12, 306, 857 |
| abstract_inverted_index.system, | 579 |
| abstract_inverted_index.system. | 171 |
| abstract_inverted_index.systems | 513 |
| abstract_inverted_index.testing | 822 |
| abstract_inverted_index.thermal | 48, 67, 470 |
| abstract_inverted_index.through | 82 |
| abstract_inverted_index.typical | 704 |
| abstract_inverted_index.uniform | 744 |
| abstract_inverted_index.various | 19 |
| abstract_inverted_index.(2015a). | 893 |
| abstract_inverted_index.Although | 21 |
| abstract_inverted_index.American | 365 |
| abstract_inverted_index.Assuming | 559 |
| abstract_inverted_index.However, | 69, 128, 194, 443 |
| abstract_inverted_index.McLaury, | 890 |
| abstract_inverted_index.Offshore | 873 |
| abstract_inverted_index.Platform | 875 |
| abstract_inverted_index.Practice | 370, 867 |
| abstract_inverted_index.Research | 399 |
| abstract_inverted_index.Shirazi, | 886 |
| abstract_inverted_index.abrasion | 837 |
| abstract_inverted_index.accuracy | 485 |
| abstract_inverted_index.assumed. | 729 |
| abstract_inverted_index.assuming | 742 |
| abstract_inverted_index.becoming | 33 |
| abstract_inverted_index.compared | 514, 593 |
| abstract_inverted_index.critical | 35 |
| abstract_inverted_index.equation | 898 |
| abstract_inverted_index.erosion. | 281, 327 |
| abstract_inverted_index.existing | 158, 220, 237, 263 |
| abstract_inverted_index.expected | 168, 510 |
| abstract_inverted_index.improved | 381 |
| abstract_inverted_index.material | 183, 299, 434, 467 |
| abstract_inverted_index.modified | 672, 687 |
| abstract_inverted_index.observed | 771 |
| abstract_inverted_index.obtained | 605 |
| abstract_inverted_index.particle | 10, 44, 53, 101, 186, 189, 349, 429, 439, 524, 560, 568, 572, 711, 719, 739, 745, 841, 851, 853, 855 |
| abstract_inverted_index.relevant | 231, 502 |
| abstract_inverted_index.requires | 95 |
| abstract_inverted_index.sequence | 286 |
| abstract_inverted_index.storage. | 68 |
| abstract_inverted_index.surfaces | 293, 845 |
| abstract_inverted_index.systems, | 56 |
| abstract_inverted_index.systems. | 51, 105, 235, 506 |
| abstract_inverted_index.velocity | 573 |
| abstract_inverted_index.Arabnejad | 487, 608, 659 |
| abstract_inverted_index.Institute | 367 |
| abstract_inverted_index.Mansouri, | 884 |
| abstract_inverted_index.Petroleum | 366 |
| abstract_inverted_index.affecting | 426 |
| abstract_inverted_index.attrition | 849 |
| abstract_inverted_index.available | 271, 353 |
| abstract_inverted_index.conducted | 550, 796 |
| abstract_inverted_index.developed | 114, 139, 258, 313, 387, 448, 636, 835 |
| abstract_inverted_index.different | 318, 692, 738 |
| abstract_inverted_index.empirical | 360, 382 |
| abstract_inverted_index.equations | 310, 385 |
| abstract_inverted_index.function. | 829 |
| abstract_inverted_index.hardness, | 437 |
| abstract_inverted_index.including | 323, 428 |
| abstract_inverted_index.increases | 774 |
| abstract_inverted_index.indicated | 614 |
| abstract_inverted_index.industry, | 419 |
| abstract_inverted_index.materials | 7 |
| abstract_inverted_index.mechanism | 347 |
| abstract_inverted_index.obtaining | 766 |
| abstract_inverted_index.operating | 153, 516 |
| abstract_inverted_index.particles | 58, 71, 291, 649, 761, 808 |
| abstract_inverted_index.pertinent | 165 |
| abstract_inverted_index.published | 639 |
| abstract_inverted_index.recently, | 393 |
| abstract_inverted_index.renewable | 38 |
| abstract_inverted_index.resulting | 839 |
| abstract_inverted_index.results). | 768 |
| abstract_inverted_index.thickness | 724, 732 |
| abstract_inverted_index.validated | 241, 540 |
| abstract_inverted_index.velocity. | 790 |
| abstract_inverted_index.332–333, | 903 |
| abstract_inverted_index.Arabnejad, | 882 |
| abstract_inverted_index.Arabnejad. | 408 |
| abstract_inverted_index.Continuing | 285 |
| abstract_inverted_index.Currently, | 791 |
| abstract_inverted_index.Institute, | 861 |
| abstract_inverted_index.Prediction | 477 |
| abstract_inverted_index.Production | 874 |
| abstract_inverted_index.Throughout | 106 |
| abstract_inverted_index.University | 404 |
| abstract_inverted_index.associated | 468 |
| abstract_inverted_index.components | 80 |
| abstract_inverted_index.conditions | 154, 319, 501, 517 |
| abstract_inverted_index.considered | 764 |
| abstract_inverted_index.correction | 255 |
| abstract_inverted_index.deviations | 509 |
| abstract_inverted_index.dispersion | 759 |
| abstract_inverted_index.empirical, | 334 |
| abstract_inverted_index.following. | 391 |
| abstract_inverted_index.frequently | 413 |
| abstract_inverted_index.increases. | 778 |
| abstract_inverted_index.industries | 121 |
| abstract_inverted_index.introduced | 212, 363, 396 |
| abstract_inverted_index.literature | 417 |
| abstract_inverted_index.mechanical | 302, 464 |
| abstract_inverted_index.mechanism, | 322 |
| abstract_inverted_index.parameters | 425 |
| abstract_inverted_index.particles. | 308, 558, 901 |
| abstract_inverted_index.prediction | 134, 668 |
| abstract_inverted_index.relatively | 453 |
| abstract_inverted_index.therefore, | 94 |
| abstract_inverted_index.thickness, | 570 |
| abstract_inverted_index.velocities | 147, 228, 455, 526, 543, 622 |
| abstract_inverted_index.Development | 894 |
| abstract_inverted_index.Predictions | 681 |
| abstract_inverted_index.Recommended | 369, 866 |
| abstract_inverted_index.References. | 859 |
| abstract_inverted_index.calculated. | 587 |
| abstract_inverted_index.calculation | 699 |
| abstract_inverted_index.conditions. | 626 |
| abstract_inverted_index.correlation | 210, 361, 375, 634, 654, 828 |
| abstract_inverted_index.deformation | 326 |
| abstract_inverted_index.experiments | 244, 548, 792 |
| abstract_inverted_index.industries. | 20 |
| abstract_inverted_index.interaction | 303 |
| abstract_inverted_index.mechanistic | 896 |
| abstract_inverted_index.performance | 535 |
| abstract_inverted_index.production, | 30 |
| abstract_inverted_index.production. | 127 |
| abstract_inverted_index.properties, | 184, 187 |
| abstract_inverted_index.significant | 74, 508 |
| abstract_inverted_index.simulations | 598 |
| abstract_inverted_index.temperature | 198, 254, 278, 625, 630, 777, 821, 827 |
| abstract_inverted_index.velocities, | 741 |
| abstract_inverted_index.velocities. | 251, 652, 812 |
| abstract_inverted_index.1044–1050. | 904 |
| abstract_inverted_index.Furthermore, | 779 |
| abstract_inverted_index.Installation | 871 |
| abstract_inverted_index.calculations | 734 |
| abstract_inverted_index.concentrated | 46 |
| abstract_inverted_index.experimental | 272, 354, 589, 679 |
| abstract_inverted_index.interactions | 13, 757 |
| abstract_inverted_index.investigated | 495 |
| abstract_inverted_index.mathematical | 633 |
| abstract_inverted_index.mechanistic, | 333 |
| abstract_inverted_index.non-linearly | 787 |
| abstract_inverted_index.subsequently | 592 |
| abstract_inverted_index.technologies | 39 |
| abstract_inverted_index.temperature, | 702 |
| abstract_inverted_index.temperature. | 529 |
| abstract_inverted_index.temperatures | 230, 248, 693 |
| abstract_inverted_index.Introduction. | 1 |
| abstract_inverted_index.Subsequently, | 252 |
| abstract_inverted_index.Temperatures. | 480 |
| abstract_inverted_index.computational | 597 |
| abstract_inverted_index.conservative, | 378 |
| abstract_inverted_index.exponentially | 775 |
| abstract_inverted_index.interactions. | 858 |
| abstract_inverted_index.investigated. | 204 |
| abstract_inverted_index.temperatures, | 150, 267 |
| abstract_inverted_index.temperatures. | 87, 474, 545 |
| abstract_inverted_index.understanding | 98 |
| abstract_inverted_index.cross-sectional | 751 |
| abstract_inverted_index.semi-mechanistic | 336, 384 |
| abstract_inverted_index.Erosion/Corrosion | 398 |
| abstract_inverted_index.temperature-based | 209 |
| abstract_inverted_index.(particle-particle | 756 |
| abstract_inverted_index.http://doi.org/10.1016/j.wear.2015.01.031. | 905 |
| abstract_inverted_index.https://ducom.com/high-temperature-erosion-evaluating-sample-wear/ | 907 |
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| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
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