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Relevant bibliographies by topics / Differential analysis of the functioning of the item

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Academic literature on the topic 'Differential analysis of the functioning of the item'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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Journal articles on the topic "Differential analysis of the functioning of the item"

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Penfield, Randall D. "DIFAS: Differential Item Functioning Analysis System." Applied Psychological Measurement 29, no. 2 (2005): 150–51. http://dx.doi.org/10.1177/0146621603260686.

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Wyse, Adam E., and Raymond Mapuranga. "Differential Item Functioning Analysis Using Rasch Item Information Functions." International Journal of Testing 9, no. 4 (2009): 333–57. http://dx.doi.org/10.1080/15305050903352040.

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Brodersen, J., and H. Thorsen. "PCN64 DIFFERENTIAL ITEM FUNCTIONING USING RASCH ANALYSIS." Value in Health 9, no. 6 (2006): A295. http://dx.doi.org/10.1016/s1098-3015(10)63493-6.

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Cohen, Allan S., and Daniel M. Bolt. "A Mixture Model Analysis of Differential Item Functioning." Journal of Educational Measurement 42, no. 2 (2005): 133–48. http://dx.doi.org/10.1111/j.1745-3984.2005.00007.

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Hao, Shiqi. "Two SAS Macros for Differential Item Functioning Analysis." Applied Psychological Measurement 38, no. 1 (2013): 81–82. http://dx.doi.org/10.1177/0146621613493164.

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Guilera, Georgina, Juana Gómez-Benito, and M. Dolores Hidalgo. "Citation analysis in research on differential item functioning." Quality & Quantity 44, no. 6 (2009): 1249–55. http://dx.doi.org/10.1007/s11135-009-9274-3.

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Swanson, David B., Brian E. Clauser, Susan M. Case, Ronald J. Nungester, and Carol Featherman. "Analysis of Differential Item Functioning (DIF) Using Hierarchical Logistic Regression Models." Journal of Educational and Behavioral Statistics 27, no. 1 (2002): 53–75. http://dx.doi.org/10.3102/10769986027001053.

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Over the past 25 years a range of parametric and nonparametric methods have been developed for analyzing Differential Item Functioning (DIF). These procedures are typically performed for each item individually or for small numbers of related items. Because the analytic procedures focus on individual items, it has been difficult to pool information across items to identify potential sources of DIF analytically. In this article, we outline an approach to DIF analysis using hierarchical logistic regression that makes it possible to combine results of logistic regression analyses across items to identify consistent sources of DIF, to quantify the proportion of explained variation in DIF coefficients, and to compare the predictive accuracy of alternate explanations for DIF. The approach can also be used to improve the accuracy of DIF estimates for individual items by applying empirical Bayes techniques, with DIF-related item characteristics serving as collateral information. To illustrate the hierarchical logistic regression procedure, we use a large data set derived from recent computer-based administrations of Step 2, the clinical science component of the United States Medical Licensing Examination (USMLE®). Results of a small Monte Carlo study of the accuracy of the DIF estimates are also reported.

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Walker, Cindy M., Bo Zhang, Kathleen Banks, and Kevin Cappaert. "Establishing Effect Size Guidelines for Interpreting the Results of Differential Bundle Functioning Analyses Using SIBTEST." Educational and Psychological Measurement 72, no. 3 (2011): 415–34. http://dx.doi.org/10.1177/0013164411422250.

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The purpose of this simulation study was to establish general effect size guidelines for interpreting the results of differential bundle functioning (DBF) analyses using simultaneous item bias test (SIBTEST). Three factors were manipulated: number of items in a bundle, test length, and magnitude of uniform differential item functioning (DIF) against the focal group in each item in a bundle. A secondary purpose was to validate the current effect size guidelines for interpreting the results of single-item DIF analyses using SIBTEST. The results of this study clearly demonstrate that ability estimation bias can only be attributed to DIF or DBF when a large number of items in a bundle are functioning differentially against focal examinees in a small way or a small number of items are functioning differentially against focal examinees in a large way. In either of these situations, the presence of DIF or DBF should be a cause for concern because it would lead one to erroneously believe that distinct groups differ in ability when in fact they do not.

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Wu, Johnny, Kevin M. King, Katie Witkiewitz, Sarah Jensen Racz, and Robert J. McMahon. "Item analysis and differential item functioning of a brief conduct problem screen." Psychological Assessment 24, no. 2 (2012): 444–54. http://dx.doi.org/10.1037/a0025831.

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Zwick, Rebecca, and Dorothy T. Thayer. "Evaluating the Magnitude of Differential Item Functioning in Polytomous Items." Journal of Educational and Behavioral Statistics 21, no. 3 (1996): 187–201. http://dx.doi.org/10.3102/10769986021003187.

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Several recent studies have investigated the application of statistical inference procedures to the analysis of differential item functioning (DIF) in polytomous test items that are scored on an ordinal scale. Mantel’s extension of the Mantel-Haenszel test is one of several hypothesis-testing methods for this purpose. The development of descriptive statistics for characterizing DIF in polytomous test items has received less attention. As a step in this direction, two possible standard error formulas for the polytomous DIF index proposed by Dorans and Schmitt were derived. These standard errors, as well as associated hypothesis-testing procedures, were evaluated though application to simulated data. The standard error that performed better is based on Mantel’s hypergeometric model. The alternative standard error, based on a multinomial model, tended to yield values that were too small.

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Dissertations / Theses on the topic "Differential analysis of the functioning of the item"

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Lees, Jared Andrew. "Differential Item Functioning Analysis of the Herrmann Brain Dominance Instrument." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2103.pdf.

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Chen, Dong Qi Kayla. "Gender-related differential item functioning analysis on the GEPT-kids." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3953512.

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Yildirim, Huseyin Husnu. "The Differential Item Functioning (dif) Analysis Of Mathematics Items In The International Assessment Programs." Phd thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607135/index.pdf.

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Cross-cultural studies, like TIMSS and PISA 2003, are being conducted since 1960s with an idea that these assessments can provide a broad perspective for evaluating and improving education. In addition countries can assess their relative positions in mathematics achievement among their competitors in the global world. However, because of the different cultural and language settings of different countries, these international tests may not be functioning as expected across all the countries. Thus, tests may not be equivalent, or fair, linguistically and culturally across the participating countries. In this conte! ! xt, the present study aimed at assessing the equivalence of mathematics items of TIMSS 1999 and PISA 2003 across cultures and languages, to fin! d out if mathematics achievement possesses any culture specifi! c aspect s. For this purpose, the present study assessed Turkish and English versions of TIMSS 1999 and PISA 2003 mathematics items with respect to, (a) psychometric characteristics of items, and (b) possible sources of Differential Item Functioning (DIF) between these two versions. The study used Restricted Factor Analysis, Mantel-Haenzsel Statistics and Item Response Theory Likelihood Ratio methodologies to determine DIF items. The results revealed that there were adaptation problems in both TIMSS and PISA studies. However it was still possible to determine a subtest of items functioning fairly between cultures, to form a basis for a cross-cultural comparison. In PISA, there was a high rate of agreement among the DIF methodologies used. However, in TIMSS, the agree! ment ra! te decreased considerably possibly because the rate o! f differ e! ntially functioning items within TIMSS was higher, and differential guessing and differential discriminating were also issues in the test. The study! also revealed that items requiring competencies of reproduction of practiced knowledge, knowledge of facts, performance of routine procedures, application of technical skills were less likely to be biased against Turkish students with respect to American students at the same ability level. On the other hand, items requiring students to communicate mathematically, items where various results must be compared, and items that had real-world context were less likely to be in favor of Turkish students.

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Zhang, Mo. "Gender related differential item functioning in mathematics tests a meta-analysis /." Pullman, Wash. : Washington State University, 2009. http://www.dissertations.wsu.edu/Thesis/Summer2009/m_zhang_072109.pdf.

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Stephens-Bonty, Torie Amelia. "Using Three Different Categorical Data Analysis Techniques to Detect Differential Item Functioning." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/eps_diss/24.

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Diversity in the population along with the diversity of testing usage has resulted in smaller identified groups of test takers. In addition, computer adaptive testing sometimes results in a relatively small number of items being used for a particular assessment. The need and use for statistical techniques that are able to effectively detect differential item functioning (DIF) when the population is small and or the assessment is short is necessary. Identification of empirically biased items is a crucial step in creating equitable and construct-valid assessments. Parshall and Miller (1995) compared the conventional asymptotic Mantel-Haenszel (MH) with the exact test (ET) for the detection of DIF with small sample sizes. Several studies have since compared the performance of MH to logistic regression (LR) under a variety of conditions. Both Swaminathan and Rogers (1990), and Hildalgo and López-Pina (2004) demonstrated that MH and LR were comparable in their detection of items with DIF. This study followed by comparing the performance of the MH, the ET, and LR performance when both the sample size is small and test length is short. The purpose of this Monte Carlo simulation study was to expand on the research done by Parshall and Miller (1995) by examining power and power with effect size measures for each of the three DIF detection procedures. The following variables were manipulated in this study: focal group sample size, percent of items with DIF, and magnitude of DIF. For each condition, a small reference group size of 200 was utilized as well as a short, 10-item test. The results demonstrated that in general, LR was slightly more powerful in detecting items with DIF. In most conditions, however, power was well below the acceptable rate of 80%. As the size of the focal group and the magnitude of DIF increased, the three procedures were more likely to reach acceptable power. Also, all three procedures demonstrated the highest power for the most discriminating item. Collectively, the results from this research provide information in the area of small sample size and DIF detection.

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Mehta, Vandhana. "Structural Validity and Item Functioning of the LoTi Digital-Age Survey." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc68014/.

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The present study examined the structural construct validity of the LoTi Digital-Age Survey, a measure of teacher instructional practices with technology in the classroom. Teacher responses (N = 2840) from across the United States were used to assess factor structure of the instrument using both exploratory and confirmatory analyses. Parallel analysis suggests retaining a five-factor solution compared to the MAP test that suggests retaining a three-factor solution. Both analyses (EFA and CFA) indicate that changes need to be made to the current factor structure of the survey. The last two factors were composed of items that did not cover or accurately measure the content of the latent trait. Problematic items, such as items with crossloadings, were discussed. Suggestions were provided to improve the factor structure, items, and scale of the survey.

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Asil, Mustafa. "Differential item functioning (DIF) analysis of the verbal section of the 2003 student selection examination (SSE)." The Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=osu1399553097.

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Whitmore, Marjorie Lee Threet. "A Comparison of Two Differential Item Functioning Detection Methods: Logistic Regression and an Analysis of Variance Approach Using Rasch Estimation." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc278366/.

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Differential item functioning (DIF) detection rates were examined for the logistic regression and analysis of variance (ANOVA) DIF detection methods. The methods were applied to simulated data sets of varying test length (20, 40, and 60 items) and sample size (200, 400, and 600 examinees) for both equal and unequal underlying ability between groups as well as for both fixed and varying item discrimination parameters. Each test contained 5% uniform DIF items, 5% non-uniform DIF items, and 5% combination DIF (simultaneous uniform and non-uniform DIF) items. The factors were completely crossed, and each experiment was replicated 100 times. For both methods and all DIF types, a test length of 20 was sufficient for satisfactory DIF detection. The detection rate increased significantly with sample size for each method. With the ANOVA DIF method and uniform DIF, there was a difference in detection rates between discrimination parameter types, which favored varying discrimination and decreased with increased sample size. The detection rate of non-uniform DIF using the ANOVA DIF method was higher with fixed discrimination parameters than with varying discrimination parameters when relative underlying ability was unequal. In the combination DIF case, there was a three-way interaction among the experimental factors discrimination type, relative ability, and sample size for both detection methods. The error rate for the ANOVA DIF detection method decreased as test length increased and increased as sample size increased. For both methods, the error rate was slightly higher with varying discrimination parameters than with fixed. For logistic regression, the error rate increased with sample size when relative underlying ability was unequal between groups. The logistic regression method detected uniform and non-uniform DIF at a higher rate than the ANOVA DIF method. Because the type of DIF present in real data is rarely known, the logistic regression method is recommended for most cases.

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Ing, Pamela Grace. "An Investigation of the 'White Male Effect' from a Psychometric Perspective." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338312146.

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Liu, Mingyang Liu. "Differential Item Functioning in Large-scale Mathematics Assessments: Comparing the Capabilities of the Rasch Trees Model to Traditional Approaches." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1513266587329066.

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Books on the topic "Differential analysis of the functioning of the item"

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T, Everson Howard, and Osterlind Steven J, eds. Differential item functioning. 2nd ed. SAGE, 2009.

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Osterlind, Steven, and Howard Everson. Differential Item Functioning. SAGE Publications, Inc., 2009. http://dx.doi.org/10.4135/9781412993913.

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Hamilton, Laura S. Exploring differential item functioning on science achievement tests. Center for the Study of Evaluation, National Center for Research on Evaluation, Standards, and Student Testing, Graduate School of Education & Information Studies, University of California, Los Angeles, 1998.

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Schnipke, Deborah L. A comparison of Mantel-Haenszel differential item functioning parameters. Law School Admission Council, 2000.

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McLeod, Lori Davis. A polynomial logistic regression approach to graphical differential item functioning. Law School Admission Council, 2006.

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Le, Vi-Nhuan. Identifying differential item functioning on the NELS:88 history achievement test. Center for the Study of Evaluation, National Center for Research on Evaluation, Standards, and Student Testing, Graduate School of Education & Information Studies, University of California, Los Angeles, 1999.

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Roussos, Louis A. A generalized formula for the Mantel-Haenszel differential item functioning parameter. Law School Admission Council, 1998.

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Roussos, Louis A. A formulation of the Mantel-Haenszel differential item functioning parameter with practical implications. Law School Admission Council, 2000.

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Lawrence, Ida M. Differential item functioning for males and females on SAT-verbal reading subscore items. College Entrance Examination Board, 1988.

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Nandakumar, Ratna. CATSIB: A modified SIBTEST procedure to detect differential item functioning in computerized adaptive tests. Law School Admission Council, 2001.

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Book chapters on the topic "Differential analysis of the functioning of the item"

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Boone, William J., John R. Staver, and Melissa S. Yale. "Differential Item Functioning." In Rasch Analysis in the Human Sciences. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6857-4_13.

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Kite, Benjamin A., Terrence D. Jorgensen, and Po-Yi Chen. "Random Permutation Tests of Nonuniform Differential Item Functioning in Multigroup Item Factor Analysis." In Springer Proceedings in Mathematics & Statistics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77249-3_24.

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Wetzel, Eunike, and Jan R. Böhnke. "Differential Item Functioning." In Encyclopedia of Personality and Individual Differences. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1297.

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Wetzel, Eunike, and Jan R. Böhnke. "Differential Item Functioning." In Encyclopedia of Personality and Individual Differences. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28099-8_1297-1.

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Chen, Wen-Hung, and Dennis Revicki. "Differential Item Functioning (DIF)." In Encyclopedia of Quality of Life and Well-Being Research. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_728.

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Kok, Frank. "9. Differential item functioning." In The Construct of Language Proficiency. John Benjamins Publishing Company, 1992. http://dx.doi.org/10.1075/z.62.13kok.

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Drasgow, Fritz, Christopher D. Nye, Stephen Stark, and Oleksandr S. Chernyshenko. "Differential Item and Test Functioning." In The Wiley Handbook of Psychometric Testing. John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781118489772.ch27.

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Desjardins, Christopher D., and Okan Bulut. "Measurement Invariance and Differential Item Functioning." In Handbook of Educational Measurement and Psychometrics Using R. Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/b20498-11.

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Glas, Cees A. W. "Differential Item Functioning Depending on General Covariates." In Essays on Item Response Theory. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0169-1_7.

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Qiu, Xue-Lan, Xiaomin Li, and Wen-Chung Wang. "Differential Item Functioning in Diagnostic Classification Models." In Handbook of Diagnostic Classification Models. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05584-4_18.

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Conference papers on the topic "Differential analysis of the functioning of the item"

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Sadak, Musa. "THE PERFORMANCE OF TURKISH AND US STUDENTS ON PISA 2012 MATHEMATICS ITEMS: A DIFFERENTIAL ITEM FUNCTIONING ANALYSIS." In International Technology, Education and Development Conference. IATED, 2016. http://dx.doi.org/10.21125/iceri.2016.1746.

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Lan, Tian, Zhongxuan Lin, and Tour Liu. "Differential Item Functioning Analysis for Repeated Measures Design Social Survey Data: A Method for Detecting Social Demands Difference in Big-Data Era." In 2018 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC). IEEE, 2018. http://dx.doi.org/10.1109/besc.2018.8697289.

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Davidson, Matt J., Brett Wortzman, Amy J. Ko, and Min Li. "Investigating Item Bias in a CS1 Exam with Differential Item Functioning." In SIGCSE '21: The 52nd ACM Technical Symposium on Computer Science Education. ACM, 2021. http://dx.doi.org/10.1145/3408877.3432397.

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Hadi, Samsul, Basukiyatno Basukiyatno, and Purwo Susongko. "Differential Item Functioning National Examination on Device Test Mathematics High School in Central Java." In Proceedings of the 1st International Conference on Social Science, Humanities, Education and Society Development, ICONS 2020, 30 November, Tegal, Indonesia. EAI, 2021. http://dx.doi.org/10.4108/eai.30-11-2020.2303726.

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Panthong, Aweeporn, and Pairatana Wongnam. "A Comparison of the Efficiency of Likelihood Ratio Test and Bayesian Procedures in the Detection Differential Item Functioning for Polytomous Scored Items." In Annual International Conference on Cognitive and Behavioral Psychology. Global Science & Technology Forum (GSTF), 2015. http://dx.doi.org/10.5176/2251-1865_cbp15.58.

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Altman, Brianna, Maha Mian, Luna Ueno, and Mitch Earleywine. "Cannabis’s Link to Schizotypy: Phenomenon, Measurement Bias, or Delusion?" In 2020 Virtual Scientific Meeting of the Research Society on Marijuana. Research Society on Marijuana, 2021. http://dx.doi.org/10.26828/cannabis.2021.01.000.5.

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Links between cannabis use and psychosis continue to generate research and media attention. Cannabis users have outscored non-users on the Schizotypal Personality Questionnaire-Brief (SPQ-B) by a small amount in multiple studies, but previous work on biased items suggests that the groups do not differ if these items are removed. The present study examined links between schizotypal personality, as measured by the SPQ-B, and cannabis use in a large sample recruited from Amazon’s MTurk platform. Over 500 participants (72.5%) reported lifetime cannabis exposure, 259 participants (36.7%) reported current cannabis use, and on average, used 3.5 days per week. Users and non-users failed to differ significantly on total SPQ-B scores or any of the three established subscales, with effect sizes all lower than d = .20. The null results inspired a re-examination of the SPQ-B’s factor structure, which identified a novel 3-factor solution (difficulty opening up to others, hyperawareness, and odd or unusual behavior). Only the “odd or unusual behavior” factor showed cannabis-related differences (g = .234), but a differential item functioning test revealed that one item on that subscale showed potential bias against users. Removing this item dropped the group differences to a non-significant g = 0.149. These results suggest that links between schizotypy and cannabis require cautious interpretation with careful attention to potential measurement bias. In addition, the Schizotypal Personality Questionnaire-Brief might have an alternative factor structure that could help answer important questions in psychopathology.

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Huang Rui, Jin Wenlong, Han Longxi, Peng Hui, Pan Manman, and Zhang Hong. "Transient source two-dimensional source item inverse problem research and accuracy impact analysis based on the differential evolution algorithm in the wide/shallow watercourse." In 2012 First National Conference for Engineering Sciences (FNCES). IEEE, 2012. http://dx.doi.org/10.1109/nces.2012.6543976.

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Weber, Anton, Christian Morsbach, Edmund Kügeler, Christoph Rube, and Matthias Wedeking. "Flow Analysis of a High Flowrate Centrifugal Compressor Stage and Comparison With Test Rig Data." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56551.

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The flow field inside a single-stage centrifugal compressor characterized by a high flowrate of Φ = 0.15 and a design total pressure ratio of approximately 1.4 is analysed numerically. The stage geometry consists of a radially oriented inlet duct with uniform inflow without swirl, a 90 deg inlet bend in front of the impeller, the shrouded impeller itself followed by a large radial vaneless diffuser, a 180 deg U-turn, a radially oriented turning vane, a subsequent 90 deg bend, and as the last item a long axial exit duct. The impeller blades have large fillets at hub and tip and thick blunt trailing edges. Due to the rotating shroud, a labyrinth seal is placed above the impeller with 5 seal tips. The complete leakage region is also included in the CFD analysis. The blade numbers for the impeller and vane are 15 and 14, respectively. The test rig has recently been built at the Institute of Propulsion and Turbomachinery at RWTH Aachen University (Germany). The first part of the CFD work presented was carried out before the first experimental data were available. Using the k-ω turbulence model of Wilcox (1988), a number of principal steady RANS calculations were performed to investigate the following: Impact of near wall grid resolution and turbulence model wall boundary condition treatment, impact of impeller fillets, and the influence of leakage flow. This part is completed by a comparison of steady RANS simulations with the time-mean results of unsteady RANS analyses of one blade passage. For the calculations presented in the second part, experimental data are available at the inflow and outflow planes. At these planes overall mean values were deduced. Additionally, 3- and 5-hole probe data are available at spanwise traverse planes located at the zenith of the U-turn and in the exit plane. For part two a finer grid with y+ values of approximately unity for all solid walls was used. In addition to the Wilcox k-ω model and the Menter SST k-ω model, two higher level turbulence models — the explicit algebraic Reynolds stress model Hellsten EARSM k-ω and the differential Reynolds stress model SSG/LRR-ω — have been tested and compared with the experiments. The agreement in terms of overall performance (total pressure ratio, isentropic efficiency) is satisfactory for all turbulence models used, but there are some differences: the k-ω model is shown to be the most stable one towards stall. On the other hand, it is shown that details of the flow field in terms of the two spanwise traverses can be better represented by the more advanced turbulence models. All CFD simulations have been performed at 100% shaft speed.

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Rozzia, Davide, Alessio Pesetti, Alessandro Del Nevo, Mariano Tarantino, and Nicola Forgione. "HERO Test Section for Experimental Investigation of Steam Generator Bayonet Tube of ALFRED." In 2017 25th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icone25-67422.

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In the framework of Gen IV Heavy Liquid Metal Fast Reactors (HLMFRs) development, research activities are carried out for improving the Advanced Lead Fast Reactor European Demonstrator (ALFRED) project. In particular, the functioning and safety of the Steam Generator Bayonet Tube (SGBT) of ALFRED reactor (developed by ANSALDO Nucleare) needs to be experimentally investigated and numerical tools have to be verified and validated against reliable high quality data of SGBT stationary and accidental transient conditions. At the ENEA CR Brasimone, a full scale portion of the SGBT of ALFRED, composed by seven bayonet tubes arranged as triangular pitch inside a hexagonal shroud, was designed and assembled. It is called Heavy liquid mEtal-pRessurized water cOoled tube (HERO) and it was implemented as heat exchanger in the Integral Circulation Experiment (ICE) test section. The ICE-HERO test section is presently ready to be set in the large pool CIRCE facility for carrying out integral tests in Lead Bismuth Eutectic alloy (LBE) pool at about 400°C. ICE test section is equipped with a fuel pin simulator (FPS) of 37 electrically heated pin for an overall maximum thermal source of 1 MW and an argon injector above FPS for performing enhanced circulation (gas lift). The hot LBE (about 480°C) exiting from FPS moves upwards passing through the thermally insulated riser pipe and reaches an upper small tank, isolated from the outer colder LBE pool, called separator, from which descends shell side of the HERO heat exchanger and returns to the LBE pool, closing the integral circulation. The secondary side of HERO component (7 bayonet tubes) is fed by about 0.35 kg/s of water at 180 bar and 335°C. Each bayonet tube is composed by three concentric tubes. In the first (inner) tube, liquid water flows downwards in subcooled conditions and thermally insulated from outer parts. Between the first and second tube (annular cross-sectional area) water moves upwards and it is heated up to superheated steam condition. The annular gap between the second and third tube is filled by helium at 5 bar and steel powder for monitoring the possible rupture of the third or second tube and do not reduce excessively the heat transfer coefficient. The HERO component is highly instrumented for characterising the heat exchanger capabilities of the bayonet tubes in stationary and transient conditions. An overall number of 65 thermocouples are implemented, acquiring water, LBE and helium temperatures. Two pressure transducers monitor the feed water and steam line pressure. Each bayonet tube has four differential pressure transducers for measuring the pressure drops on the descending, ascending, and total water path and computing the water mass flow rate of each tube by a calibrated orifice. A Coriolis flowmeter is adopted to precisely determine the feed water mass flow rate. Moreover the signals of thermocouples, pressure transducers and bubble tubes implemented in the ICE test section will be acquired for an exhaustive analysis of the tests. A sensitivity analysis performed by RELAP5 code was carried out for defining the geometry and material to be adopted for the bayonet tube construction. The materials foreseen to be implemented have undergone modifications, AISI powder instead of SiC, air gap in place of the thermal insulating paint and AISI pipe instead of T91. The RELAP5 thermodynamic analysis predicted that the bayonet tube in updated configuration is able to provide superheated steam at about 400°C. The expected performance of HERO-TS is retained acceptable for the application to a prototypic unit and can be scaled to ALFRED.

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Reports on the topic "Differential analysis of the functioning of the item"

1

Welsh, John R., Androlewicz Jr., and Thomas R. Armed Services Vocational Aptitude Battery (ASVAB): Analyses of Differential Item Functioning on Forms 15, 16 and 17. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada227183.

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2

Truhon, Stephen A. Comparing Two Versions of the MEOCS Using Differential Item Functioning. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada417193.

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