Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816335
R. J. Mulvihill, F.M. Safie
The current Space Shuttle external tank design is called the super light weight tank (SLWT). A weight reduction of approximately 30% was achieved relative to the prior design called the light weight tank (LWT). The new NASA risk assessment tool, the quantitative risk assessment system (QRAS), was used to compare the risk of the two designs. The comparison includes consideration of the apparent reduction of the design safety factor for SLWT welds when a weld repair is required. The risk models for the structural failure accident scenario include five initiating events (IEs): (1) liquid oxygen (LO2) tank component failure; (2) liquid hydrogen (LH2) tank component failure; (3) LO2 tank weld failure; (4) LH2 tank weld failure; and (5) intertank failure. Although the risk results for the LH2 and LO2 tank welds for IEs 2 and 4 are higher for the SLWT vs. the LWT, the reverse is true for tank components IEs 1, 3 and 5. The SLWT has a slightly lower risk of structural failure. The impact of this difference is not significant to the total risk when the other six scenarios are also included.
{"title":"Application of the NASA risk assessment tool to the evaluation of the Space Shuttle external tank re-welding process","authors":"R. J. Mulvihill, F.M. Safie","doi":"10.1109/RAMS.2000.816335","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816335","url":null,"abstract":"The current Space Shuttle external tank design is called the super light weight tank (SLWT). A weight reduction of approximately 30% was achieved relative to the prior design called the light weight tank (LWT). The new NASA risk assessment tool, the quantitative risk assessment system (QRAS), was used to compare the risk of the two designs. The comparison includes consideration of the apparent reduction of the design safety factor for SLWT welds when a weld repair is required. The risk models for the structural failure accident scenario include five initiating events (IEs): (1) liquid oxygen (LO2) tank component failure; (2) liquid hydrogen (LH2) tank component failure; (3) LO2 tank weld failure; (4) LH2 tank weld failure; and (5) intertank failure. Although the risk results for the LH2 and LO2 tank welds for IEs 2 and 4 are higher for the SLWT vs. the LWT, the reverse is true for tank components IEs 1, 3 and 5. The SLWT has a slightly lower risk of structural failure. The impact of this difference is not significant to the total risk when the other six scenarios are also included.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134457665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816333
L. M. Kaufman, S. Bhide, B.W. Johnson
This paper demonstrates how to accurately model the effects of common mode failures for digital embedded systems. By modeling the system's information flow, the integrated nature of the software and hardware components contained within such a system is represented. This modeling scheme allows for the system to be partitioned into error containment regions (ECRs), which are an extension of the fault containment region (FCR) concept. These ECRs are defined such that an error at their boundary results in system failure. If two or more ECRs produce errors at their boundaries and the underlying cause of these errors is identical, then the identification of common mode failures is achieved.
{"title":"Modeling of common-mode failures in digital embedded systems","authors":"L. M. Kaufman, S. Bhide, B.W. Johnson","doi":"10.1109/RAMS.2000.816333","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816333","url":null,"abstract":"This paper demonstrates how to accurately model the effects of common mode failures for digital embedded systems. By modeling the system's information flow, the integrated nature of the software and hardware components contained within such a system is represented. This modeling scheme allows for the system to be partitioned into error containment regions (ECRs), which are an extension of the fault containment region (FCR) concept. These ECRs are defined such that an error at their boundary results in system failure. If two or more ECRs produce errors at their boundaries and the underlying cause of these errors is identical, then the identification of common mode failures is achieved.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114991527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816292
P.A. Keiller, T. Mazzuchi
In this paper, enhancement of the performance of the Goel-Okumoto Reliability Growth model is investigated using various smoothing techniques. The method of parameter estimation for the model is the maximum likelihood method. The evaluation of the performance of the model is judged by the relative error of the predicted number of failures over future time intervals relative to the number of failures eventually observed during the interval. The use of data analysis procedures utilizing the Laplace trend test are investigated. These methods test for reliability growth throughout the data and establish "windows" that censor early failure data and provide better model fits. The research showed conclusively that the data analysis procedures resulted in improvement in the models' predictive performance for 41 different sets of software failure data collected from software development labs in the United States and Europe.
{"title":"Enhancing the predictive performance of the Goel-Okumoto software reliability growth model","authors":"P.A. Keiller, T. Mazzuchi","doi":"10.1109/RAMS.2000.816292","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816292","url":null,"abstract":"In this paper, enhancement of the performance of the Goel-Okumoto Reliability Growth model is investigated using various smoothing techniques. The method of parameter estimation for the model is the maximum likelihood method. The evaluation of the performance of the model is judged by the relative error of the predicted number of failures over future time intervals relative to the number of failures eventually observed during the interval. The use of data analysis procedures utilizing the Laplace trend test are investigated. These methods test for reliability growth throughout the data and establish \"windows\" that censor early failure data and provide better model fits. The research showed conclusively that the data analysis procedures resulted in improvement in the models' predictive performance for 41 different sets of software failure data collected from software development labs in the United States and Europe.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121397689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816297
A. Mettas
This paper describes a model for multiple stress-type accelerated life data. In addition, the use of an algorithm, which was specifically developed for this model is illustrated. The model is based on the widely known log-linear model (1990) and is formulated for the Weibull and lognormal distributions for a variety of censoring schemes using likelihood theory. An algorithm has been developed for the solution of this model, and implemented in a recently released software package, ALTA Pro/sup TM/, specific to accelerated life data analysis. The algorithm has been specifically designed to be very flexible and has the capability of simultaneously solving for up to eight different stress-types. The advantage of this formulation is that it combines in one model most of the known life-stress relationships for one or two types of stresses (such as the temperature-nonthermal model), as well as the multivariable proportional hazards model. This yields a single general likelihood function (for a given distribution) whose solution is independent of both the chosen life-stress relationship and the number of stress-types. In addition, this model allows for simultaneous analysis of continuous, categorical and indicator variables. The solution to this model provides the engineers with an opportunity to expand their selection of types of stresses and test conditions when testing products.
{"title":"Modeling and analysis for multiple stress-type accelerated life data","authors":"A. Mettas","doi":"10.1109/RAMS.2000.816297","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816297","url":null,"abstract":"This paper describes a model for multiple stress-type accelerated life data. In addition, the use of an algorithm, which was specifically developed for this model is illustrated. The model is based on the widely known log-linear model (1990) and is formulated for the Weibull and lognormal distributions for a variety of censoring schemes using likelihood theory. An algorithm has been developed for the solution of this model, and implemented in a recently released software package, ALTA Pro/sup TM/, specific to accelerated life data analysis. The algorithm has been specifically designed to be very flexible and has the capability of simultaneously solving for up to eight different stress-types. The advantage of this formulation is that it combines in one model most of the known life-stress relationships for one or two types of stresses (such as the temperature-nonthermal model), as well as the multivariable proportional hazards model. This yields a single general likelihood function (for a given distribution) whose solution is independent of both the chosen life-stress relationship and the number of stress-types. In addition, this model allows for simultaneous analysis of continuous, categorical and indicator variables. The solution to this model provides the engineers with an opportunity to expand their selection of types of stresses and test conditions when testing products.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123317813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816279
D. Crowe
Embarking on an extensive program of reliability science will provide a company with a long-term value add proposition, setting it apart from it competitors, returning many times over the value of that investment. It must be noted that this process requires having a long-term commitment to build and support a world-class reliability operation, the fruits of which are often not seen in real time. The operation can be extensive in cost but the gains can be great. Engineers must always understand the return on investment.
{"title":"Reliability in today's business environment","authors":"D. Crowe","doi":"10.1109/RAMS.2000.816279","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816279","url":null,"abstract":"Embarking on an extensive program of reliability science will provide a company with a long-term value add proposition, setting it apart from it competitors, returning many times over the value of that investment. It must be noted that this process requires having a long-term commitment to build and support a world-class reliability operation, the fruits of which are often not seen in real time. The operation can be extensive in cost but the gains can be great. Engineers must always understand the return on investment.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128624207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816331
A. Feinberg, A. Widom
Miner's rule of cumulative damage for materials undergoing stress-strain cycles allows for the prediction of the number of cycles of different strengths required before a material fails. Since Miner's rule has a thermodynamics basis, the rule should extend to thermodynamic work variables other than stress and strain. This point is illustrated in this work by applying the rule to chemical cells in a battery where the thermodynamic work variables are the electromotive force and the charge. Miner's rule of cumulative damage in chemical cells (undergoing voltage-charge and voltage-discharge cycles) allows for the prediction of the number of cycles of different strengths required before a battery fails.
{"title":"Thermodynamic extensions of Miner's rule to chemical cells","authors":"A. Feinberg, A. Widom","doi":"10.1109/RAMS.2000.816331","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816331","url":null,"abstract":"Miner's rule of cumulative damage for materials undergoing stress-strain cycles allows for the prediction of the number of cycles of different strengths required before a material fails. Since Miner's rule has a thermodynamics basis, the rule should extend to thermodynamic work variables other than stress and strain. This point is illustrated in this work by applying the rule to chemical cells in a battery where the thermodynamic work variables are the electromotive force and the charge. Miner's rule of cumulative damage in chemical cells (undergoing voltage-charge and voltage-discharge cycles) allows for the prediction of the number of cycles of different strengths required before a battery fails.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128276869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816322
Sang-Chin Yang, J. Kobza, J. A. Nachlas
Issues related to the construction of bivariate reliability models and their application to maintenance planning are discussed. The distinction between bivariate failure models and models of first passage time to a failure threshold clarifies the motivation for the development of bivariate models. The authors present a taxonomy of model classes and identify two classes as their focus. The model classes examined here are those in which the two variables are related by a stochastic function and those in which the variables are simply correlated. Examples of the models of each of the two classes are defined. The general approach to model formulation is explained so that the reader may construct alternate forms. The sometimes subtle aspects of model analysis are discussed with particular emphasis on the interpretation of bivariate failure probabilities and on the calculating of numerical results. Associated issues related to the construction of renewal models that can be used in maintenance planning are also discussed. For each of the topics addressed, example calculations are provided or else the technical roadblocks to continuing analysis are identified. In the authors' view, the types of bivariate models described here provide a new way to study the reliability of equipment for which univariate measures are incomplete. Thus, a new area of reliability research is identified. The definitions they offer may be modified, and the approach to model formulation they present may be used to define other models. They raise several open questions concerning the model construction and analysis. Both conceptual definitions and analytical methods warrant further exploration.
{"title":"Bivariate failure modeling","authors":"Sang-Chin Yang, J. Kobza, J. A. Nachlas","doi":"10.1109/RAMS.2000.816322","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816322","url":null,"abstract":"Issues related to the construction of bivariate reliability models and their application to maintenance planning are discussed. The distinction between bivariate failure models and models of first passage time to a failure threshold clarifies the motivation for the development of bivariate models. The authors present a taxonomy of model classes and identify two classes as their focus. The model classes examined here are those in which the two variables are related by a stochastic function and those in which the variables are simply correlated. Examples of the models of each of the two classes are defined. The general approach to model formulation is explained so that the reader may construct alternate forms. The sometimes subtle aspects of model analysis are discussed with particular emphasis on the interpretation of bivariate failure probabilities and on the calculating of numerical results. Associated issues related to the construction of renewal models that can be used in maintenance planning are also discussed. For each of the topics addressed, example calculations are provided or else the technical roadblocks to continuing analysis are identified. In the authors' view, the types of bivariate models described here provide a new way to study the reliability of equipment for which univariate measures are incomplete. Thus, a new area of reliability research is identified. The definitions they offer may be modified, and the approach to model formulation they present may be used to define other models. They raise several open questions concerning the model construction and analysis. Both conceptual definitions and analytical methods warrant further exploration.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"35 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129424139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816320
J. Rupe
The authors explore maintenance models for finite time missions. Motivated by real world applications, and models which are lacking in literature, they include exponential cost forms that allow for net present value analysis, and explore replacing obsolete equipment with new. In this paper, they demonstrate through mathematical modeling that: by using simple search methods, one can find optimal replacement intervals for systems under a general finite time mission; under Weibull hazard functions, one can express the optimal replacement rate simply; by allowing for special exponential cost function forms, one can find local cost minima for exponentially growing costs, or include the time value of money; for systems in use, one can monitor the marginal cost, and replace the system when this marginal cost equals the expected average cost for the replacing system; when replacing one technology with a new, there are conditions under which the optimal replacement cycles are completely interrelated, and other conditions where one can calculate one from an independent calculation of another; and in budget constrained times, use present value estimates such as the ones we provide. To apply optimal replacement planning in industry, one must consider finite time missions, net present value of costs, and replacing obsolete equipment with new technology.
{"title":"Optimal-maintenance modeling on finite time with technology replacement and changing repair costs","authors":"J. Rupe","doi":"10.1109/RAMS.2000.816320","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816320","url":null,"abstract":"The authors explore maintenance models for finite time missions. Motivated by real world applications, and models which are lacking in literature, they include exponential cost forms that allow for net present value analysis, and explore replacing obsolete equipment with new. In this paper, they demonstrate through mathematical modeling that: by using simple search methods, one can find optimal replacement intervals for systems under a general finite time mission; under Weibull hazard functions, one can express the optimal replacement rate simply; by allowing for special exponential cost function forms, one can find local cost minima for exponentially growing costs, or include the time value of money; for systems in use, one can monitor the marginal cost, and replace the system when this marginal cost equals the expected average cost for the replacing system; when replacing one technology with a new, there are conditions under which the optimal replacement cycles are completely interrelated, and other conditions where one can calculate one from an independent calculation of another; and in budget constrained times, use present value estimates such as the ones we provide. To apply optimal replacement planning in industry, one must consider finite time missions, net present value of costs, and replacing obsolete equipment with new technology.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129561132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816295
V. Loll
When large hardware-software systems are run-in or an acceptance testing is made, a problem is when to stop the test and deliver/accept the system. The same problem exists when a large software program is tested with simulated operations data. Based on two theses from the Technical University of Denmark, the paper describes and evaluates 7 possible algorithms. Of these algorithms, the three most promising are tested with simulated data. 27 different systems are simulated, and 50 Monte Carlo simulations made on each system. The stop times generated by the algorithm is compared with the known perfect stop time. Of the three algorithms two is selected as good. These two algorithms are then tested on 10 sets of real data. The algorithms are tested with three different levels of confidence. The number of correct and wrong stop decisions are counted. The conclusion is that the Weibull algorithm with 90% confidence level takes the right decision in every one of the 10 cases.
{"title":"Developing and testing algorithms for stopping testing, screening, run-in of large systems or programs","authors":"V. Loll","doi":"10.1109/RAMS.2000.816295","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816295","url":null,"abstract":"When large hardware-software systems are run-in or an acceptance testing is made, a problem is when to stop the test and deliver/accept the system. The same problem exists when a large software program is tested with simulated operations data. Based on two theses from the Technical University of Denmark, the paper describes and evaluates 7 possible algorithms. Of these algorithms, the three most promising are tested with simulated data. 27 different systems are simulated, and 50 Monte Carlo simulations made on each system. The stop times generated by the algorithm is compared with the known perfect stop time. Of the three algorithms two is selected as good. These two algorithms are then tested on 10 sets of real data. The algorithms are tested with three different levels of confidence. The number of correct and wrong stop decisions are counted. The conclusion is that the Weibull algorithm with 90% confidence level takes the right decision in every one of the 10 cases.","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130455370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-01-24DOI: 10.1109/RAMS.2000.816318
W. Kuo, C. S. Carlson, F. D. Gregory, T. Mitrou, M. Shooman, G. Vassiliades
{"title":"Advisory board - tools for reliability and maintainability practitioners","authors":"W. Kuo, C. S. Carlson, F. D. Gregory, T. Mitrou, M. Shooman, G. Vassiliades","doi":"10.1109/RAMS.2000.816318","DOIUrl":"https://doi.org/10.1109/RAMS.2000.816318","url":null,"abstract":"","PeriodicalId":178321,"journal":{"name":"Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055)","volume":"44 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113974664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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