Relevant bibliographies by topics / Two stage sampling design

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Two stage sampling design'

Author: Grafiati
Published: 8 September 2023

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Journal articles on the topic "Two stage sampling design"

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Skinner, C. J. "Design Effects of Two-Stage Sampling." Journal of the Royal Statistical Society: Series B (Methodological) 48, no. 1 (September 1986): 89–99. http://dx.doi.org/10.1111/j.2517-6161.1986.tb01393.x.

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Rodrigues, Josemar. "Asymptotically design-unbiased predictors for two-stage sampling." Statistics & Probability Letters 17, no. 5 (August 1993): 411–14. http://dx.doi.org/10.1016/0167-7152(93)90263-i.

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Ugwu, Michael C., and Mbanefo S. Madukaife. "Two-stage cluster sampling with unequal probability sampling in the first stage and ranked set sampling in the second stage." Statistics in Transition New Series 23, no. 3 (September 1, 2022): 199–214. http://dx.doi.org/10.2478/stattrans-2022-0038.

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Abstract In this research work we introduce a new sampling design, namely a two-stage cluster sampling, where probability proportional to size with replacement is used in the first stage unit and ranked set sampling in the second in order to address the issue of marked variability in the sizes of population units concerned with first stage sampling. We obtained an unbiased estimator of the population mean and total, as well as the variance of the mean estimator. We calculated the relative efficiency of the new sampling design to the two-stage cluster sampling with simple random sampling in the first stage and ranked set sampling in the second stage. The results demonstrated that the new sampling design is more efficient than the competing design when a significant variation is observed in the first stage units.
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Chauvet, Guillaume, and Audrey-Anne Vallée. "Inference for two-stage sampling designs." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 82, no. 3 (May 6, 2020): 797–815. http://dx.doi.org/10.1111/rssb.12368.

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Raju, C., and R. Vidya. "DESIGN OF TWO-STAGE CHAIN SAMPLING PLANS WITH KULLBACK-LEIBLER INFORMATION." Advances and Applications in Statistics 73 (January 10, 2022): 47–74. http://dx.doi.org/10.17654/0972361722010.

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Valliant, Richard, Jill A. Dever, and Frauke Kreuter. "Effects of Cluster Sizes on Variance Components in Two-Stage Sampling." Journal of Official Statistics 31, no. 4 (December 1, 2015): 763–82. http://dx.doi.org/10.1515/jos-2015-0044.

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Abstract Determining sample sizes in multistage samples requires variance components for each stage of selection. The relative sizes of the variance components in a cluster sample are dramatically affected by how much the clusters vary in size, by the type of sample design, and by the form of estimator used. Measures of the homogeneity of survey variables within clusters are related to the variance components and affect the numbers of sample units that should be selected at each stage to achieve the desired precision levels. Measures of homogeneity can be estimated using standard software for random-effects models but the model-based intracluster correlations may need to be transformed to be appropriate for use with the sample design. We illustrate these points and implications for sample size calculation for two-stage sample designs using a realistic population derived from household surveys and the decennial census in the U.S.
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Taconeli, Cesar Augusto, and Angelo da Silva Cabral. "New two-stage sampling designs based on neoteric ranked set sampling." Journal of Statistical Computation and Simulation 89, no. 2 (November 15, 2018): 232–48. http://dx.doi.org/10.1080/00949655.2018.1541990.

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Molefe, Wilford. "Optimal allocation for equal probability two-stage design." Statistics in Transition New Series 23, no. 4 (December 1, 2022): 129–48. http://dx.doi.org/10.2478/stattrans-2022-0046.

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Abstract This paper develops optimal designs when it is not feasible for every cluster to be represented in a sample as in stratified design, by assuming equal probability two-stage sampling where clusters are small areas. The paper develops allocation methods for two-stage sample surveys where small-area estimates are a priority. We seek efficient allocations where the aim is to minimize the linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. We suggest some alternative allocations with a view to minimizing the same objective. Several alternatives, including the area-only stratified design, are found to perform nearly as well as the optimal allocation but with better practical properties. Designs are evaluated numerically using Switzerland canton data as well as Botswana administrative districts data.
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Hsu, Lie-Fern, and Jia-Tzer Hsu. "Economic Design of Acceptance Sampling Plans in a Two-Stage Supply Chain." Advances in Decision Sciences 2012 (February 29, 2012): 1–14. http://dx.doi.org/10.1155/2012/359082.

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Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer's and consumer's quality and risk requirements. However, all the available QC tables and computer software determine the sampling plan on a noneconomic basis. In this paper, we design an economic model to determine the optimal sampling plan in a two-stage supply chain that minimizes the producer's and the consumer's total quality cost while satisfying both the producer's and consumer's quality and risk requirements. Numerical examples show that the optimal sampling plan is quite sensitive to the producer's product quality. The product's inspection, internal failure, and postsale failure costs also have an effect on the optimal sampling plan.
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Waters, James R., and Alexander J. Chester. "Optimal Allocation in Multivariate, Two-Stage Sampling Designs." American Statistician 41, no. 1 (February 1987): 46. http://dx.doi.org/10.2307/2684319.

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Dissertations / Theses on the topic "Two stage sampling design"

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Kim, Kyong Ryun. "Second order accurate variance estimation in poststratified two-stage sampling." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5895.

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We proposed new variance estimators for the poststratified estimator of the population total in two-stage sampling. The linearization or Taylor series variance estimator and the jackknife linearization variance estimator are popular for the poststratified estimator. The jackknife linearization variance estimator utilizes the ratio, ^Rc, which balances the weights for the poststrata while the linearization or Taylor series estimator does not. The jackknife linearization variance estimator is equivalent to Rao's (1985) adjusted variance estimator. Our proposed estimator makes use of the ratio, ^R c, in a different shape which is naturally derived from the process of expanding to the second-order Taylor series linearization, while the standard linearization variance estimator is only expanded to the first-order. We investigated the properties and performance of the linearization variance estimator, the jackknife linearization estimator, the proposed variance estimator and its modified version analytically and through simulation study. The simulation study was carried out on both artificially generated data and real data. The result showed that the second order accurate variance estimator and its modified version could be very good candidates for the variance estimation of poststratified estimator of population total.
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Neff, Angela R. "Bayesian Two Stage Design Under Model Uncertainty." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30303.

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Traditional single stage design optimality procedures can be used to efficiently generate data for an assumed model y = f(x(m),b) + ε. The model assumptions include the form of f, the set of regressors, x(m) , and the distribution of ε. The nature of the response, y, often provides information about the model form (f) and the error distribution. It is more difficult to know, apriori, the specific set of regressors which will best explain the relationship between the response and a set of design (control) variables x. Misspecification of x(m) will result in a design which is efficient, but for the wrong model. A Bayesian two stage design approach makes it possible to efficiently design experiments when initial knowledge of x(m) is poor. This is accomplished by using a Bayesian optimality criterion in the first stage which is robust to model uncertainty. Bayesian analysis of first stage data reduces uncertainty associated with x(m), enabling the remaining design points (second stage design) to be chosen with greater efficiency. The second stage design is then generated from an optimality procedure which incorporates the improved model knowledge. Using this approach, numerous two stage design procedures have been developed for the normal linear model. Extending this concept, a Bayesian design augmentation procedure has been developed for the purpose of efficiently obtaining data for variance modeling, when initial knowledge of the variance model is poor.
Ph. D.
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Montes, Diez Raquel. "Optimal design of two-stage screens : a Bayesian approach." Thesis, University of Nottingham, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.342027.

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Baran, Gary Steven. "A two-stage experimental design procedure under dispersion effects." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/37246.

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Under heterogeneous variance, conventional optimal response surface experimental designs for estimating location models are no longer optimal. To address this deficiency. D and Q criteria appropriate under heterogeneous variance are developed. These criteria are then applied to demonstrate the improved efficiency of a proposed two-stage experimental design procedure. In the proposed procedure the first stage estimates the heterogeneous variance structure and the second stage augments the first stage to produce a total design that is Q or D-optimal for the estimated variance structure. The Q and 0 criteria not only direct the total design, but also suggest optimal designs for estimating dispersion effects in the first stage. The efficiency of the proposed two-stage procedure is further enhanced if certain mild assumptions concerning variance structure are valid. These assumptions are formulated as a prior distribution and effectively stabilize the variance estimation in the first stage through a Bayes estimator.
Ph. D.
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Ninov, Valentin. "Two-dimensional zero-phase FIR filter design with nonuniform frequency sampling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0002/MQ43655.pdf.

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Yahya, Samir Ghazi. "Design and evaluation of two-stage travelling wave thermoacoustic cooler." Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/15541/.

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The overall aim of this research is to investigate the underpinning science behind constructing a practical travelling-wave thermoacoustic refrigerator. At the outset, this was defined as a demonstrator that could be further developed into a means of thermal management of various enclosures – for example weather proof enclosures containing heat generating electronics, popular across the process industries. The practical requirements were set as 400 to 500 W of cooling power at 25 K temperature difference between the inside of the enclosure and the ambient. The initial research addressed issues of coupling the linear motors to such a refrigerator. This included analytical solutions of equations governing the electrodynamic behaviour of the motors, which lead to obtaining preferred acoustic conditions for their optimum performance. Meanwhile, a series of DeltaEC simulations was conducted to investigate possible configurations of the acoustic network that provide the required acoustic impedance matching. The project had the practical limitations of using two existing Q-drive linear motors. As a result, a refrigerator network has been developed which required a compliance and inertance matching a twin-alternator excitation and a two-stage looped-tube travelling-wave refrigerator. The second part of the research was concerned with engineering a practical demonstrator of the above refrigerator concept. DeltaEC simulations have been used to design a practical build and predict its performance characteristics. A prototype, based on helium pressurised at 40 bar and operating frequency of 60 Hz, has been subsequently built and commissioned. A number of experiments have been conducted to evaluate its performance “as built” followed by improvements including, in particular, the use of elastic membranes to supress Gedeon streaming. The prototype achieved a maximum temperature difference of 40ºC, minimum cold temperature of -7.5ºC, maximum COP of 2.05, highest COPR of 21.72% and total cooling power of 283W. Good overall agreement was found between modelling and experiments.
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Stampfli, John J. "Design of a two-stage multi-state experimental biogas reactor." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127871.

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Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 23-25).
Anaerobic digestion is a process that breaks down waste and other feed materials and produces biogas. A biogas reactor, or anaerobic digester, is designed to conduct anaerobic digestion in a closed environment and to collect the produced biogas. This is an important field of study because biogas is a renewable energy source. If it can be produced more efficiently, it may become a feasible alternative source of green energy. This thesis outlines the design of a lab-scale experimental reactor with a large range of functionality. The design permits many different environmental conditions, allowing anaerobic digestion to be thoroughly studied with one setup.
by John J. Stampfli.
S.B.
S.B. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Vatkar, Shirish Talia Jorge E. "Design of a two stage epicyclic gearbox in sintered metal gears." Diss., A link to full text of this thesis in SOAR, 2007. http://soar.wichita.edu/dspace/handle/10057/1183.

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Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Mechanical Engineering..
"May 2007." Title from PDF title page (viewed on Dec. 29, 2007). Thesis adviser: George Talia. Includes bibliographic references (leaves 100-101).
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Hu, Bing, and 胡冰. "Feedback-based two stage switch architecture for high speed router design." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43278693.

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Zhao, Chao. "Design fully-integrated dual-band two-stage class-E CMOS PA." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804916/.

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In retrospect we can see that from the last century, wireless electronic technology has been in a rapid state of development. With the popularity of wireless communication, the power amplifier demand is rising. In general, magnitude, maximum noise figure, minimum noise figure, efficiency, and output power are important indicators of the amplifier. The IC industry is exploring how to reduce the additional cost and improve the high-frequency performance. Therefore, designing a strong adaptability and high cost performance of the PA has become a priority. As these technologies advance, the power amplifiers need to have better integration, lower cost, and lower power dissipation. Also, some special requirements are being asked in some areas, such as multi-mode and multi-band. In general, people have to use several power amplifiers parallel to frame a multifunction chip. Each of them working at different frequencies of interest has to have separate matching network, design, and area; also, the diversity amplifier prices will increase with the number of amplifiers, and its cost is also changed. In this thesis, because Class E power amplifier has lower power dissipation, 100% ideal efficiency, simple circuit structure, and strong applicability, the Class E is used as power amplifier in main stage. Moreover, in order to decrease input power and increase output power, the class A power amplifier is used as driver stage. It can use very small amount of power to provide a larger power. Moreover, we use a switched variable inductor and capacitor to constitute a dual band matching network which can let the PA work at more than one frequency. In fact, we design a Class A PA which is as a driver stage. Then, when we support 1 dBm input power, the driver stage can have 8 dBm output power. Also the output will be the input power for the main stage. When the Class E PA get 8dBm input power, it will export a 15dBm output power. Because the dual band matching network, the PA can work at 2.2 GHz and 2.6 GHz; also, the efficiency is 48% and 51%, and the both gains are 13 dB. In the future, in order to further improve the performance of the power amplifier and better multi-frequencies, more new designs with new structures should be investigated. Moreover, we need further research about design theory. In fact multi-frequencies power amplifier has a great potential in real application. It based on its special structure and design parameters.
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Books on the topic "Two stage sampling design"

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United States. National Aeronautics and Space Administration., ed. Two stage to orbit design. [Washington, DC: National Aeronautics and Space Administration, 1991.

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United States. National Aeronautics and Space Administration., ed. Conceptual design of two-stage-to-orbit hybrid launch vehicle. [Cleveland, Ohio]: Case Western Reserve University, 1991.

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United States. National Aeronautics and Space Administration., ed. Conceptual design of two-stage-to-orbit hybrid launch vehicle. [Cleveland, Ohio]: Case Western Reserve University, 1991.

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Property Advisers to the Civil Estate. Central Advice Unit., ed. GC/works/1 two stage design & build (1999): General conditions. London: Stationery Office, 1999.

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Reese, Lynda M. An evaluation of a two-stage testlet design for computerized testing. Newtown, PA: Law School Admission Council, 1999.

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United States. National Aeronautics and Space Administration., ed. Overview of the Beta II two-stage-to-orbit vehicle design. [Washington, DC]: National Aeronautics and Space Administration, 1991.

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Holliday, Timothy. The design and analysis of engine mapping experiments: A two-stage approach. Birmingham: University of Birmingham, 1995.

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Mehta, Unmeel B. A two-stage-to-orbit spaceplane concept with growth potential. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 2001.

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Mehta, Unmeel B. A two-stage-to-orbit spaceplane concept with growth potential. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 2001.

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Mehta, Unmeel B. A two-stage-to-orbit spaceplane concept with growth potential. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 2001.

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Book chapters on the topic "Two stage sampling design"

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Two-Stage Adaptive Cluster Sampling." In Advanced Sampling Methods, 157–69. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_11.

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Nahler, Gerhard. "two-stage design." In Dictionary of Pharmaceutical Medicine, 186. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_1423.

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Brus, Dick J. "Two-stage cluster random sampling." In Spatial Sampling with R, 109–22. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003258940-7.

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Two-Stage Negative Adaptive Cluster Sampling." In Advanced Sampling Methods, 241–55. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_18.

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Two-Stage Inverse Adaptive Cluster Sampling." In Advanced Sampling Methods, 193–202. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_14.

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Stamp, Mark. "Two-stage cluster random sampling." In Introduction to Machine Learning with Applications in Information Security, 109–22. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003264873-7.

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Castillo-Santiago, Miguel Ángel, Edith Mondragón-Vázquez, and Roberto Domínguez-Vera. "Sample Data for Thematic Accuracy Assessment in QGIS." In Land Use Cover Datasets and Validation Tools, 85–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90998-7_6.

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AbstractWe present an approach that is widely used in the field of remote sensing for the validation of single LUC maps. Unlike other chapters in this book, where maps are validated by comparison with other maps with better resolution and/or quality, this approach requires a ground sample dataset, i.e. a set of sites where LUC can be observed in the field or interpreted from high-resolution imagery. Map error is assessed using techniques based on statistical sampling. In general terms, in this approach, the accuracy of single LUC maps is assessed by comparing the thematic map against the reference data and measuring the agreement between the two. When assessing thematic accuracy, three stages can be identified: the design of the sample, the design of the response, and the estimation and analysis protocols. Sample design refers to the protocols used to define the characteristics of the sampling sites, including sample size and distribution, which can be random or systematic. Response design involves establishing the characteristics of the reference data, such as the size of the spatial assessment units, the sources from which the reference data will be obtained, and the criteria for assigning labels to spatial units. Finally, the estimation and analysis protocols include the procedures applied to the reference data to calculate accuracy indices, such as user’s and producer’s accuracy, the estimated areas covered by each category and their respective confidence intervals. This chapter has two sections in which we present a couple of exercises relating to sampling and response design; the sample size will be calculated, the distribution of sampling sites will be obtained using a stratified random scheme, and finally, a set of reference data will be obtained by photointerpretation at the sampling sites (spatial units). The accuracy statistics will be calculated later in Sect. 5 in chapter “Metrics Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps” as part of the cross-tabulation exercises. The exercises in this chapter use fine-scale LUC maps obtained for the municipality of Marqués de Comillas in Chiapas, Mexico.
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Chen, Jinzhuo, and Tao Hong. "Application of Two-Stage Sampling in Sampling Inspection." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 1152–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_125.

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Diestmann, Thomas, Nils Broedling, Benedict Götz, and Tobias Melz. "Surrogate Model-Based Uncertainty Quantification for a Helical Gear Pair." In Lecture Notes in Mechanical Engineering, 191–207. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77256-7_16.

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AbstractCompetitive industrial transmission systems must perform most efficiently with reference to complex requirements and conflicting key performance indicators. This design challenge translates into a high-dimensional multi-objective optimization problem that requires complex algorithms and evaluation of computationally expensive simulations to predict physical system behavior and design robustness. Crucial for the design decision-making process is the characterization, ranking, and quantification of relevant sources of uncertainties. However, due to the strict time limits of product development loops, the overall computational burden of uncertainty quantification (UQ) may even drive state-of-the-art parallel computing resources to their limits. Efficient machine learning (ML) tools and techniques emphasizing high-fidelity simulation data-driven training will play a fundamental role in enabling UQ in the early-stage development phase.This investigation surveys UQ methods with a focus on noise, vibration, and harshness (NVH) characteristics of transmission systems. Quasi-static 3D contact dynamic simulations are performed to evaluate the static transmission error (TE) of meshing gear pairs under different loading and boundary conditions. TE indicates NVH excitation and is typically used as an objective function in the early-stage design process. The limited system size allows large-scale design of experiments (DoE) and enables numerical studies of various UQ sampling and modeling techniques where the design parameters are treated as random variables associated with tolerances from manufacturing and assembly processes. The model accuracy of generalized polynomial chaos expansion (gPC) and Gaussian process regression (GPR) is evaluated and compared. The results of the methods are discussed to conclude efficient and scalable solution procedures for robust design optimization.
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Särndal, Carl-Erik, Bengt Swensson, and Jan Wretman. "Regression Estimators for Cluster Sampling and Two-Stage Sampling." In Model Assisted Survey Sampling, 303–39. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-4378-6_8.

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Conference papers on the topic "Two stage sampling design"

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Malik, Ariff Md Ab, Masri Ayob, and Abdul Razak Hamdan. "Stratified random sampling technique for integrated two-stage multi-neighbourhood tabu search for examination timetabling problem." In 10th International Conference on Intelligent Systems Design and Applications (ISDA 2010). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687093.

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Manjunatha, Hemanth, Jida Huang, Binbin Zhang, and Rahul Rai. "A Sequential Sampling Algorithm for Multi-Stage Static Coverage Problems." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60305.

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It is critical in many system-engineering problems (such as surveillance, environmental monitoring, and cooperative task performance) to optimally allocate resources in the presence of limited resources. Static coverage problem is an important class of the resource allocation problems that focuses on covering an area of interest so that the activities in the area of interest can be detected/monitored with higher probability. In many practical settings (primarily due to financial constraints) a system designer has to allocate resources in multiple stages. In each stage, the system designer can assign a fixed number of resources (agents). In the multi-stage formulation, the agents locations for the next stage are dependent on all the agents location in the previous stages. Such multi-stage static coverage problems are non-trivial to solve. In this paper, we propose a robust and efficient sequential sampling algorithm to solve the multi-stage static coverage problem in the presence of probabilistic resource intensity allocation maps (RIAMs). The agents locations are determined by formulating this problem as an optimization problem in the successive stage . Three different objective functions are compared and discussed from the aspects of decreasing L2 difference and Sequential Minimum Energy Design (SMED). It is shown that utilizing SMED objective function leads to a better approximation of the RIAMs. Two heuristic algorithms, i.e. cuckoo search, and pattern search, are used as optimization algorithms. Numerical functions and real-life applications are provided to demonstrate the robustness and efficiency of the proposed approach.
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van Beek, Anton, Siyu Tao, and Wei Chen. "Global Emulation Through Normative Decision Making and Thrifty Adaptive Batch Sampling." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98223.

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Abstract We consider the problem of adaptive sampling for global emulation (metamodeling) with a finite budget. Conventionally this problem is tackled through a greedy sampling strategy, which is optimal for taking either a single sample or a handful of samples at a single sampling stage but neglects the influence of future samples. This raises the question: “Can we optimize the number of sampling stages as well as the number of samples at each stage?” The proposed thrifty adaptive batch sampling (TABS) approach addresses this challenge by adopting a normative decision-making perspective to determine the total number of required samples and maximize a multistage reward function with respect to the total number of stages and the batch size at each stage. To amend TABS’ numerical complexity we propose two heuristic-based strategies that significantly reduce computational time with minimal reduction of reward optimality. Through numerical examples, TABS is shown to outperform or at least be comparable to conventional greedy sampling techniques. In this fashion, TABS provides modelers a flexible adaptive sampling tool for global emulation, effectively reducing computational cost while maintaining prediction accuracy.
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Ma, Sang-Bum, Arshad Afzal, Kwang-Yong Kim, Jaeho Choi, and Wonsuk Lee. "Optimization of a Two-Stage Transonic Axial Fan to Enhance Aerodynamic Stability." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56261.

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In this paper, a multi-objective optimization of a transonic axial fan to enhance aerodynamic stability has been conducted using three-dimensional Reynolds-Averaged Navier-Stokes equations, surrogate modeling and multi-objective genetic algorithm (MOGA). Hub radius and first rotor chord length of the axial fan were chosen as design variables for the optimization. Peak adiabatic efficiency of the axial fan and stall margin at 60% of the designed rotational speed, were used as objective functions. Latin Hypercube Sampling (LHS) method was used to select design points in the design space. The objective functions were formulated using the response surface approximation (RSA) model. Three LHS samples with different distributions of twelve design points were tested to study their effects on prediction accuracy of the RSA model and optimization results. MOGA with the RSA models based on the best LHS sample, was used to obtain the Pareto-optimal front. As a result of optimization, an improvement of 17.2% in the stall margin at 60% of the designed rotational speed and 2.96% in peak adiabatic efficiency were obtained compared to the reference design. It was also found that distribution of the design points generated by LHS affects the effectiveness of the surrogate-based optimization.
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Zhang, Siliang, Ping Zhu, Paul D. Arendt, and Wei Chen. "Extended Objective-Oriented Sequential Sampling Method for Robust Design of Complex Systems Against Design Uncertainty." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70799.

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In robust design of complex systems, metamodeling techniques are commonly used to replace expensive computer simulations. To improve the sampling efficiency, efforts have been made towards developing objective-oriented sequential sampling methods for deterministic problems. In this paper, an extended objective-oriented sequential sampling method is proposed for robust design, with an emphasis on those problems with uncertainty in design variables. The method involves quantitative assessment of the effects of metamodeling uncertainty on the robust responses, as well as a sequential strategy of choosing samples to adaptively improve the predicted robust response. To validate the benefits of the sequential strategy, two mathematical examples are illustrated first. This is followed by an automotive crashworthiness design example, a highly expensive and non-linear problem. Results show that the proposed method can mitigate the effect of both metamodeling uncertainty and design uncertainty, and more efficiently identify the robust solution compared to the one-stage sampling approach that is commonly used in practice.
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Yao, Yu-Ta, Yu-Wei Wu, and Po Ting Lin. "A Two-Stage Multi-Fidelity Design Optimization for K-mer-Based Pattern Recognition (KPR) in Image Processing." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22263.

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Abstract Pattern recognition has been widely used in various applications of image processing. It is used to extract meaningful image features from the given image samples and to build classification systems with the intelligence of human recognition. Convolutional Neural Network (CNN) [1] has been one of the most popular and widely used methods for image pattern recognition applications. However, CNN was known not to be rotation-invariant to image patterns. It usually required a larger amount of training image dataset with greater variations in positions and orientations, or additional numerical treatments of spatial transformations [2]. On the other hand, K-mer-based Pattern Recognition (KPR) [3] has been developed to apply an unique way of rotation-invariant sampling to the inspected image pattern and analyze the frequency of the captured pattern features. A classification system was then built based on the K-mer frequency for the desired pattern recognition. In this paper, a series of tests and verifications of the KPR was done. It was found that finding the appropriate design parameters of the KPR for a specific application of image pattern recognition could be costly. A two-stage multi-fidelity design optimization was utilized to improve the efficiency of finding the parameters of KPR. In each iteration of the multi-fidelity design optimization procedure, the first stage was to evaluate the accuracy and efficiency of the design parameters in the K-mer-based pattern classification based on a full set of the given images. The second stage was to find a newer set of design parameters that performed the best based on a smaller set of images, which provided a classification set with lower fidelity than the original one. As a result, the proposed strategy of the multi-fidelity design optimization was more efficient than finding the optimal design parameters based on the full set of the given images.
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Qiu, Hai, Huageng Luo, and Neil Eklund. "On-Board Aircraft Engine Bearing Prognostics: Enveloping or FFT Analysis?" In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86141.

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Roller bearing prognosis requires the detection of a bearing defect signature in the earliest possible stage in order to avoid a minor or catastrophic mechanical failure. Defects can occur in any of the bearing parts, inner and outer race, cage and rolling elements. It is possible to identify the defective component of the bearing based on the specific vibration frequencies that are excited. However, the pattern of vibration spectrum changes as the bearing deteriorates through different stages. Depending on which failure stage the bearing is in, different techniques are required to find fault signatures in different frequency ranges. Techniques such as enveloping analysis that works in the high frequency region require higher data sampling rates and therefore more expensive data acquisition hardware than techniques conducted in low frequency region. This paper compares two popular rolling element bearing diagnostics techniques — spectrum analysis in the bearing characteristic frequency range and enveloping analysis in the high frequency range — using aircraft engine test rig data. The techniques are compared both in terms of the time of detection and data sampling requirement; this analysis provides guidance for technology adoption in future field deployment. Results demonstrate that enveloping analysis is able to detect bearing defects much earlier than the spectrum analysis, but it requires a higher data sampling rate. The bearing defect characteristic frequency is detectable in low frequency spectrum only in the late stage of the failure and it is contaminated by other harmonics such as shaft unbalance. From a practical perspective, the final choice of the technology adopted for deployment should be based on an analysis of hardware requirements and tolerance of detection latency.
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Suresh, K. "Monte Carlo Analysis Techniques Revisited." In ASME 1998 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/detc97/dfm-4443.

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Abstract The predominant engineering analysis techniques are the finite element, finite difference and boundary element methods. These techniques are global in that they attempt to solve field problems over an entire domain. Global techniques are, however, an ‘over-kill’ in the early stages of engineering design, when design parameters are fuzzy, and the functional viability of options can be determined through quick check-point analysis. In this paper, we revisit two ‘discarded’ Monte Carlo (MC) analysis techniques: MC boundary sampling, and MC domain sampling, which can be employed for solving field problems at discrete points. These techniques can be (potentially) more effective than global techniques, especially in the early stages of engineering design, but are ignored in practice because they are computationally expensive if implemented conventionally. In this paper, we argue that an appropriate geometric representation (of the underlying domain) — specifically, ray-representations for boundary sampling, and Voronoi graphs for domain sampling — is critical for efficient implementation of each technique. Exemplary numerical results are also presented.
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Shintani, Kohei, Tomotaka Sugai, Keisuke Ishizaki, Nicolas Knudde, Ivo Couckuyt, and Tom Dhaene. "A Set Based Design Method Using Bayesian Active Learning." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22212.

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Abstract The purpose of this paper is to propose a new Set-based concurrent engineering method using Bayesian active learning and to show an application to a multi-disciplinary design optimization problem. In the early stages of the system design process, it is required to set a target value considering the uncertainty of design conditions. If any change of design condition occurs by an external factor in the later development process, the predefined target value cannot be held, and critical rework can be inevitable. To avoid this issue, it is important in the early design stage to solve not only a single target solution but also feasible design solutions that satisfy all multi-disciplinary requirements. In order to discover the feasible region with limited resources, an efficient sampling strategy using CAE simulation is necessary. In this study, a sampling strategy based on Bayesian active learning is proposed to discover a feasible region of multi-disciplinary constraints concurrently. In the proposed method, Gaussian Process models of the multi-disciplinary constraints are trained. Based on posterior distributions of trained Gaussian Processes, new acquisition function by combining two different types of acquisition functions, Probability of Feasibility and Entropy Search is proposed and maximized to generate new sampling points to improve the prediction accuracy of feasible region effectively. To show the effectiveness of the proposed Set-based concurrent engineering method to a multi-disciplinary design problem, a suspension design problem is demonstrated.
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Chen, Shuo, Chen Gong, Jian Yang, Xiang Li, Yang Wei, and Jun Li. "Adversarial Metric Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/279.

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In the past decades, intensive efforts have been put to design various loss functions and metric forms for metric learning problem. These improvements have shown promising results when the test data is similar to the training data. However, the trained models often fail to produce reliable distances on the ambiguous test pairs due to the different samplings between training set and test set. To address this problem, the Adversarial Metric Learning (AML) is proposed in this paper, which automatically generates adversarial pairs to remedy the sampling bias and facilitate robust metric learning. Specifically, AML consists of two adversarial stages, i.e. confusion and distinguishment. In confusion stage, the ambiguous but critical adversarial data pairs are adaptively generated to mislead the learned metric. In distinguishment stage, a metric is exhaustively learned to try its best to distinguish both adversarial pairs and original training pairs. Thanks to the challenges posed by the confusion stage in such competing process, the AML model is able to grasp plentiful difficult knowledge that has not been contained by the original training pairs, so the discriminability of AML can be significantly improved. The entire model is formulated into optimization framework, of which the global convergence is theoretically proved. The experimental results on toy data and practical datasets clearly demonstrate the superiority of AML to representative state-of-the-art metric learning models.
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Reports on the topic "Two stage sampling design"

1

Atwood, C. L., and M. F. Bryan. Two-stage sampling for acceptance testing. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/6899768.

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Atwood, C. L., and M. F. Bryan. Two-stage sampling for acceptance testing. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/10112785.

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Gouge, M. J., S. K. Combs, P. W. Fisher, and S. L. Milora. Design considerations for single-stage and two-stage pneumatic pellet injectors. Office of Scientific and Technical Information (OSTI), September 1988. http://dx.doi.org/10.2172/6729779.

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Calvano, Charles N., Gene Blaylock, Robert Burger, Eric Hoy, and Rick Thiel. A Two-Stage Littoral Warfare Ship System Design. Fort Belvoir, VA: Defense Technical Information Center, December 1995. http://dx.doi.org/10.21236/ada305328.

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Sniedze-Gregory, Shani, Rachel Felgate, Elizabeth O'Grady, Sarah Buckley, and Petra Lietz. What Australian students say about transition to secondary school. Final report. Australian Council for Educational Research, November 2021. http://dx.doi.org/10.37517/978-1-74286-644-4.

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Life Education Australia's Being Healthy Being Active project involved the collection of student voice related to the concept of school transition and the move from primary to secondary school. Students from around Australia participated in 82 focus groups, or student forums, to discuss their own positive experiences, as well as perceived needs and challenges related to their move to secondary school. Section One of this report is a literature review and environmental scan on student transition from primary to secondary school. Section Two describes the methods used to design and administer the Student Forums. This includes a description of the target population and sampling methods as well as the details of the achieved sample: 82 forums with 444 students across 15 schools. Section Three outlines the findings of the Student Forums. Section Four offers conclusions and recommendations to inform the next stage of the project, designing a suite of resources and training for teachers aimed at assisting students with the transition from primary to secondary school.
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Cruces, Guillermo, Dario Tortarolo, and Gonzalo Vazquez-Bare. Design of two-stage experiments with an application to spillovers in tax compliance. The IFS, August 2022. http://dx.doi.org/10.1920/wp.ifs.2022.3222.

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Abrams, L. M., A. G. Comolli, G. A. Popper, C. Wang, and G. Wilson. Low-severity catalytic two-stage liquefaction process: Illinois coal conceptual commercial plant design and economics. Office of Scientific and Technical Information (OSTI), September 1988. http://dx.doi.org/10.2172/6431773.

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Weissinger, Rebecca, Mary Moran, Steve Monroe, and Helen Thomas. Springs and seeps monitoring protocol for park units in the Northern Colorado Plateau Network, Version 1.1. National Park Service, June 2023. http://dx.doi.org/10.36967/2299467.

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Because of the scarcity of water on the Colorado Plateau and the disproportionately high use by flora and fauna, springs and seeps were quickly identified as an ecosystem of concern for the NCPN. Following the determination of network-wide vital signs, parks were asked to select their top priorities for monitoring. Four parks have implemented springs and seeps monitoring: Arches and Canyonlands national parks, and Hovenweep and Natural Bridges national monuments. This monitoring protocol consists of a protocol narrative and 11 standard operating procedures (SOPs) for monitoring springs, seeps, and hanging gardens (aka “springs”) in NCPN parks. The overall goal of the NCPN springs monitoring program is to determine long-term trends in hydrologic and vegetation properties in the context of changes in other ecological drivers, stressors, and processes. Specific objectives include describing the status and trends of water quantity (flow or stage as applicable), water quality (pH, specific conductance, temperature), and vegetation (endemic plant populations in hanging gardens, and vegetation species and cover). This protocol narrative describes the justification, sampling design, and field methods for NCPN springs monitoring. Details may be found in the SOPs, which are listed in Chapter 1 and available at irma.nps.gov. Other aspects of the protocol summarized in the narrative include procedures for data management, analysis, and reporting; personnel and operating requirements; and instructions for how to revise the protocol.
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Kaliuga, V. V., A. V. Trifanov, V. I. Bazykin, and E. A. Tikhonov. Substantiation of a two-phase stress-free way of keeping pigs at the stage of conceptual design of pig farms. Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования Ивановская государственная сельскохозяйственная академия им. акад. Д.К. Беляева, 2018. http://dx.doi.org/10.18411/0131-5226-2018-11994.

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George. PR-015-10600-R01 Proposed Sampling Methods for Supercritical Natural Gas Streams. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 2010. http://dx.doi.org/10.55274/r0010981.

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Deepwater natural gas production is a non-traditional operation that is very different than conventional shelf or onshore production, due to the extremely high pressures (2,000 psia, 13.8 MPa abs) and rich gases (1,300 Btu/scf, 48.4 MJ/Nm3) involved. Concerns have been raised about methods used to sample deepwater natural gas supplies in this supercritical state. Sampling methods accepted for natural gas at pipeline conditions have been used to sample gas from offshore platforms and supercritical onshore storage facilities. However, the sample analyses have later been found to overestimate the energy content of the gas by as much as 300 Btu/scf (11.2 MJ/Nm3). Analyses of these samples have also been found to incorrectly estimate other properties of the gas, such as sound speed and density. Due to the potential financial impact of such discrepancies, the need exists to understand their causes, and to identify alternative sampling procedures or methods that can minimize them. A literature search was performed to identify sampling methods with the potential to accurately sample natural gas streams in the supercritical region. The search included methods listed in existing natural gas sampling standards, such as API MPMS Chapter 14.1 and GPA 2166-05, variations and suggested improvements on these standard methods, and sampling methods applied in other sectors of the energy industry. No sampling methods were identified that are designed specifically for sampling supercritical natural gas. However, guidelines were found in various references that are useful in tailoring existing sampling methods or designing new sampling methods for supercritical gas service. These guidelines include means to avoid phase changes in the samples, methods of regulating pressure while maintaining sample temperatures, avoiding issues with adsorption and desorption on equipment, and recommendations for designing a sampling method for high-pressure service.
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