Relevant bibliographies by topics / Response surface design

Contents

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

Academic literature on the topic 'Response surface design'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Response surface design"

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Donnelly, T. A. "Response-surface experimental design." IEEE Potentials 11, no. 1 (February 1992): 19–21. http://dx.doi.org/10.1109/45.127696.

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Fearn, Tom. "Design of Experiments 5: Response Surface Designs." NIR news 18, no. 7 (November 2007): 14–15. http://dx.doi.org/10.1255/nirn.1048.

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Anderson-Cook, Christine M., Connie M. Borror, and Douglas C. Montgomery. "Response surface design evaluation and comparison." Journal of Statistical Planning and Inference 139, no. 2 (February 2009): 629–41. http://dx.doi.org/10.1016/j.jspi.2008.04.004.

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Yoon, Jong-Hwan. "Optimum Design of Surface Aerator Using Response Surface Method." Journal of the Korean Society of Visualization 7, no. 2 (January 8, 2010): 47–55. http://dx.doi.org/10.5407/jksv.2010.7.2.047.

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Jeang, Angus. "Optimal tolerance design by response surface methodology." International Journal of Production Research 37, no. 14 (September 1999): 3275–88. http://dx.doi.org/10.1080/002075499190284.

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Morgenthaler, Stephan, and Martin M. Schumacher. "Robust analysis of a response surface design." Chemometrics and Intelligent Laboratory Systems 47, no. 1 (April 1999): 127–41. http://dx.doi.org/10.1016/s0169-7439(98)00199-3.

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Freek Huele, A., and Jan Engel. "A response surface approach to tolerance design." Statistica Neerlandica 60, no. 3 (August 2006): 379–95. http://dx.doi.org/10.1111/j.1467-9574.2006.00332.x.

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Vaughan, Timothy S. "Experimental design for response surface gradient estimation." Communications in Statistics - Theory and Methods 22, no. 6 (January 1993): 1535–55. http://dx.doi.org/10.1080/03610929308831102.

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Khattree, Ravindra. "Robust Parameter Design: A Response Surface Approach." Journal of Quality Technology 28, no. 2 (April 1996): 187–98. http://dx.doi.org/10.1080/00224065.1996.11979659.

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Ranade, Shruti Sunil, and Padma Thiagarajan. "Selection of a design for response surface." IOP Conference Series: Materials Science and Engineering 263 (November 2017): 022043. http://dx.doi.org/10.1088/1757-899x/263/2/022043.

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Dissertations / Theses on the topic "Response surface design"

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Pickle, Stephanie M. "Semiparametric Techniques for Response Surface Methodology." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/28517.

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Many industrial statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree of model misspecification may result in serious bias of the estimated response. Nonparametric methods have been suggested as an alternative as they can capture structure in the data that a misspecified parametric model cannot. Yet nonparametric fits may be highly variable especially in small sample settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem.
Ph. D.
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Parikh, Harshal. "Reservoir characterization using experimental design and response surface methodology." Texas A&M University, 2003. http://hdl.handle.net/1969/480.

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Hadjiilias, Hippokrates A. "The aerodynamic design and optimization of a wing-fuselage junction fillet as part of a multi-disciplinary optimization process during the early aircraft design stages." Thesis, Cranfield University, 1996. http://hdl.handle.net/1826/3443.

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An attempt to minimize interference drag in a wing-fuselage junction by means of inserting a fillet is presented in this thesis. The case of a low-wing com- mercial transport aicraft at cruise conditions is examined. Due to the highly three dimensional behaviour of the flow field around the junction, a thin-layer Navier-Stokes code was implemented to estimate the drag forces at the junc- tion. Carefully selected design variable combinations based on-the theory of Design of Experiments constituted the initial group of feasible cases for which the flow solver had to be run. The drag values of these feasible cases were then used to create a second order response surface which could predict with rea- sonable accuracy the interference drag given the value of the design variables within the feasible region. A further optimization isolated the minimum in- terference drag combination of design variable values within the design space. The minimurn interference drag combination of design variable values was eval- uated numerically by the flow solver. The prediction of the response surface and the numerical value obtained by the flow solver for the interference drag of the optimal wing-fuselage combination differed by less than five percent. To demonstrate the ability of the method to be used in an interdisciplinary analysis and optimization program, a landing gear design module is included which provides volume constraints on the fillet geometry during the fillet sur- face definition phase. The Navier Stokes flow analyses were performed on the Cranfield Cray su- percomputer. Each analysis required between eight to twelve CPU hours, and the total CPU time required for the optimization of the six variable model described in the thesis required thirty Navier Stokes runs implementing the Design of Experimens and Surface Response Methodology implementation. For comparison, a typical optimization implementing a classical conjugate di- rections optimizer with no derivative information available would probably require more than forty iterations. Both the optimization and the flow solver results are discussed and some recommendations for improving the efficiency of the code and for further ap- plications of the method are given.
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Gibson, David Riviere. "Model building and design augmentation for improved response surface estimation." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/32948.

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Davison, Jennifer J. "Response surface designs and analysis for bi-randomization error structures." Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-10042006-143852/.

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Chomtee, Boonorm. "Comparison of design optimality criteria of reduced models for response surface designs in a spherical design region." Diss., Montana State University, 2003. http://etd.lib.montana.edu/etd/2003/chomtee/ChomteeB_03.pdf.

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In this dissertation, the major objective is to compare 3 and 4 factor response surface designs in a spherical design region by studying design optimality criteria (D, A, G, and IV-criteria) over sets of reduced models. Hence, theoretical and computational details of evaluating optimality criteria for reduced models for response surface designs in a spherical design region have been described. Specifically, robustness results of the spherical response surface designs and the comparison of design optimality criteria of the response surface designs across the full second-order model and sets of reduced models for 3 and 4 design variables based on the four optimality criteria (D, A, G, and IV-criteria) are presented. Also, new types of D, A, G, and IV optimality criteria for response surface designs in a spherical design region are developed by using prior probability assignment to model effects (for some specified values of pl, pq, p 1, and p2). The four new D, A, G , and IV optimality criteria will be referred to as weighted design optimality criteria. The weighted design optimality criteria of the response surface designs across the weak heredity and strong heredity reduced models for 3 and 4 design variables are evaluated.
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Giunta, Anthony A. "Aircraft Multidisciplinary Design Optimization using Design of Experiments Theory and Response Surface Modeling Methods." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30613.

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Design engineers often employ numerical optimization techniques to assist in the evaluation and comparison of new aircraft configurations. While the use of numerical optimization methods is largely successful, the presence of numerical noise in realistic engineering optimization problems often inhibits the use of many gradient-based optimization techniques. Numerical noise causes inaccurate gradient calculations which in turn slows or prevents convergence during optimization. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expense of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimization. To address these issues, a procedure has been developed to create two types of noise-free mathematical models for use in aircraft optimization studies. These two methods use elements of statistical analysis and the overall procedure for using the methods is made computationally affordable by the application of parallel computing techniques. The first modeling method, which has been the primary focus of this work, employs classical statistical techniques in response surface modeling and least squares surface fitting to yield polynomial approximation models. The second method, in which only a preliminary investigation has been performed, uses Bayesian statistics and an adaptation of the Kriging process in Geostatistics to create exponential function-based interpolating models. The particular application of this research involves modeling the subsonic and supersonic aerodynamic performance of high-speed civil transport (HSCT) aircraft configurations. The aerodynamic models created using the two methods outlined above are employed in HSCT optimization studies so that the detrimental effects of numerical noise are reduced or eliminated during optimization. Results from sample HSCT optimization studies involving five and ten variables are presented here to demonstrate the utility of the two modeling methods.
Ph. D.
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Kim, Yoon G. "A response surface approach to data analysis in robust parameter design." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/38627.

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It has become obvious that combined arrays and a response surface approach can be effective tools in our quest to reduce (process) variability. An important aspect of the improvement of quality is to suppress the magnitude of the influence coming from subtle changes of noise factors. To model and control process variability induced by noise factors we take a response surface approach. The derivative of the standard response function with respect to noise factors, i. e., the slopes of the response function in the direction of the noise factors, play an important role in the study of the minimum process variance. For better understanding of the process variability, we study various properties of both biased and the unbiased estimators of the process variance. Response surface modeling techniques and the ideas involved with variance modeling and estimation through the function of the aforementioned derivatives is a valuable concept in this study. In what follows, we describe the use of the response surface methodology for situations in which noise factors are used. The approach is to combine Taguchi's notion of heterogeneous variability with standard design and modeling techniques available in response surface methodology.
Ph. D.
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Parker, Peter A. "Response Surface Design and Analysis in the Presence of Restricted Randomization." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/26555.

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Practical restrictions on randomization are commonplace in industrial experiments due to the presence of hard-to-change or costly-to-change factors. Employing a split-plot design structure minimizes the number of required experimental settings for the hard-to-change factors. In this research, we propose classes of equivalent estimation second-order response surface split-plot designs for which the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. Designs that possess the equivalence property enjoy the advantages of best linear unbiased estimates and design selection that is robust to model misspecification and independent of the variance components. We present a generalized proof of the equivalence conditions that enables the development of several systematic design construction strategies and provides the ability to verify numerically that a design provides equivalent estimates, resulting in a broad catalog of designs. We explore the construction of balanced and unbalanced split-plot versions of the central composite and Box-Behnken designs. In addition, we illustrate the utility of numerical verification in generating D-optimal and minimal point designs, including split-plot versions of the Notz, Hoke, Box and Draper, and hybrid designs. Finally, we consider the practical implications of analyzing a near-equivalent design when a suitable equivalent design is not available. By simulation, we compare methods of estimation to provide a practitioner with guidance on analysis alternatives when a best linear unbiased estimator is not available. Our goal throughout this research is to develop practical experimentation strategies for restricted randomization that are consistent with the philosophy of traditional response surface methodology.
Ph. D.
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Ling, Qi. "Design of Automotive Joints Using Response Surface Polynomials and Neural Networks." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/45205.

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In the early design stages of a car body, a simplified model, which represents the constituent components of the car body by their performance characteristics, is used to optimize the overall car. The determined optimum performance characteristics of the components are used as performance targets to design these components. Since designers do not know the relation between the performance characteristics of the components and their dimensions and mass, this may lead to unreasonable performance targets for the components. Moreover, this process is inefficient because design engineers use empirical procedures to design the components that should meet these targets. To design the component more efficiently, design tools are needed to link the performance targets with the physical design variables of the components. General methodologies for developing two design tools for the design of car joints are presented. These tools can be viewed as translators since they translate the performance characteristics of the joint into its dimensions and vice-versa. The first tool, called translator A, quickly predicts the stiffness and the mass of a given joint. The second tool, called translator B, finds the dimensions and mass of the most efficient joint design that meets given stiffness requirements, packaging, manufacturing and styling constraints. Putting bulkheads in the joint structure is an efficient way to increase stiffness. This thesis investigates the effect of transverse bulkheads on the stiffness of an actual B-pillar to rocker joint. It also develops a translator A for the B-pillar to rocker joint with transverse bulkheads. The developed translator A can quickly predict the stiffness of the reinforced joint. Translator B uses optimization to find the most efficient, feasible joint design that meets given targets. Sequential Linear Programming (SLP) and the Modified Feasible Direction (MFD) method are used for optimization. Both Response Surface Polynomial (RSP) translator B and Neural Network (NN) translator B are developed and validated. Translator A is implemented in an MS-Excel program. Translator B is implemented in a MATHEMATICA program. The methodology for developing translator B is demonstrated on the B-pillar to rocker joint of an actual car. The convergence of the optimizer is checked by solving the optimization problem many times starting from different initial designs. The results from translator B are also checked against FEA results to ensure the feasibility of the optimum designs. By observing the optimum designs and by performing parametric studies for the effect of some important design variables on the joint mass we can establish guidelines for design of joints.
Master of Science
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Books on the topic "Response surface design"

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Whitcomb, Pat. Response surface methods for process optimization: Ppt Version 27.04. Minneapolis, MN: Stat-Ease, Inc., 2006.

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Institute of Materials, Minerals, and Mining., ed. Optimisation of manufacturing processes: A response surface approach. London: Maney for the Institute of Materials, Minerals and Mining, 2003.

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N, Boyadjieva Lidia, ed. Quality improvement with design of experiments: A response surface approach. Dordrecht: Kluwer Academic Publishers, 2001.

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C, Montgomery Douglas, ed. Response surface methodology: Process and product optimization using designed experiments. New York: Wiley, 1995.

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Myers, Raymond H. Response surface methodology: Process and product optimization using designed experiments. 3rd ed. Hoboken, N.J: Wiley, 2008.

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C, Montgomery Douglas, ed. Response surface methodology: Process and product optimization using designed experiments. 2nd ed. New York: J. Wiley, 2002.

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1941-, Cornell John A., ed. Response surfaces: Designs and analyses. 2nd ed. New York: Marcel Dekker, 1996.

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1941-, Cornell John A., ed. Response surfaces: Designs and analyses. New York: M. Dekker, 1987.

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Box, George E. P. Empirical model-building and response surfaces. New York: Wiley, 1987.

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Robust response surfaces, regression, and positive data analyses. Boca Raton: CRC Press, 2014.

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Book chapters on the topic "Response surface design"

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Berger, Paul D., Robert E. Maurer, and Giovana B. Celli. "Introduction to Response-Surface Methodology." In Experimental Design, 533–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64583-4_16.

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Selvamuthu, Dharmaraja, and Dipayan Das. "Response Surface Methodology." In Introduction to Statistical Methods, Design of Experiments and Statistical Quality Control, 319–51. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1736-1_9.

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Del Vecchio, R. J. "Basics of Response Surface Methods." In Understanding Design of Experiments, 83–90. München: Carl Hanser Verlag GmbH & Co. KG, 2014. http://dx.doi.org/10.3139/9783446442474.015.

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Vining, G. Geoffrey. "Split-Plot Response Surface Designs." In Design and Analysis of Experiments, 471–500. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118147634.ch14.

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Del Vecchio, R. J. "Analysis of Response Surface Method Experiments." In Understanding Design of Experiments, 91–95. München: Carl Hanser Verlag GmbH & Co. KG, 2014. http://dx.doi.org/10.3139/9783446442474.016.

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Jee, Haeseong, David C. Gossard, and Emanuel Sachs. "Automated design of a three-dimensionally printed mushroom surface texture." In Rapid Response Manufacturing, 8–32. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-6365-5_2.

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Kaltenbach, Hans-Michael. "Experimental Optimization with Response Surface Methods." In Statistical Design and Analysis of Biological Experiments, 241–60. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69641-2_10.

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Samuelides, Manuel. "Response Surface Methodology and Reduced Order Models." In Multidisciplinary Design Optimization in Computational Mechanics, 17–64. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118600153.ch2.

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Singhee, Amith. "SiLVR: Projection Pursuit for Response Surface Modeling." In Machine Learning in VLSI Computer-Aided Design, 449–503. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04666-8_16.

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Nugent, Amanda, Howard R. Moskowitz, and Andrea Maier. "RESPONSE SURFACE METHODOLOGY AND CONSUMER-DRIVEN PRODUCT OPTIMIZATION." In Accelerating New Food Product Design and Development, 323–64. Chichester, UK: John Wiley & Sons Ltd and the Institute of Food Technologists, 2017. http://dx.doi.org/10.1002/9781119149330.ch19.

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Conference papers on the topic "Response surface design"

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Rathod, V. P., O. P. Yadav, and A. P. S. Rathore. "Multi-response surface optimization using axiomatic design." In 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2013. http://dx.doi.org/10.1109/ieem.2013.6962457.

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"Aerodynamic configuration design using response surface methodology analysis." In Aircraft Design, Systems, and Operations Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-3967.

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Lenderink, Egbert, and Peter Stehouwer. "Optimization, sensitivity analysis, and robust design using response surface modeling." In Optical Systems Design, edited by Tina E. Kidger and Stuart R. David. SPIE, 2008. http://dx.doi.org/10.1117/12.797649.

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Kodiyalam, Srinivas, Jian Lin, and Brett Wujek. "Design of Experiments based response surface models for design optimization." In 39th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1998. http://dx.doi.org/10.2514/6.1998-2030.

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Wang, Haoyu, and Nam Kim. "Robust Design Using Stochastic Response Surface and Sensitivities." In 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7015.

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Mandic, Tvrtko, Renaud Gillon, and Adrijan Baric. "IC-Stripline design optimization using response surface methodology." In 2013 9th International Workshop on Electromagnetic Compatibility of Integrated Circuits (EMC Compo). IEEE, 2013. http://dx.doi.org/10.1109/emccompo.2013.6735175.

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Wodtke, Hans-Walter, Hans A. Eschenauer, and John S. Lamancusa. "Layout of Extensional Surface Damping Treatment for Minimal Resonance Response." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0385.

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Abstract The efficiency of using surface-mounted damping layers for noise-reduction of thin-walled (sheet metal) structures, largely depends on their distribution on the component. It is therefore attempted — by using FEM and Mathematical Programming (MP) procedures — to determine optimal layer distributions in such a way that the resonance amplitudes in a frequency interval become minimal. An approximation method based on damped single degree of freedom response functions is used for resonance tracking. Beams, circular plates and shallow spherical shells with unconstrained damping treatment are considered as application examples. It will be shown that an optimal layout of the layers can result in substantial reductions in sound radiation. These reductions result not only from an increase in damping and stiffness but may also be due to a modification of the vibration modeshapes.
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Vasu, Anoop, and Ramana V. Grandhi. "A Response Surface Model Using the Sorted k-fold Approach." In 10th AIAA Multidisciplinary Design Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-1485.

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Hadadian, Armin, Ramin Sedaghati, and Ebrahim Esmailzadeh. "Optimal Design of Magnetorheological Damper using Response Surface Method." In 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
20th AIAA/ASME/AHS Adaptive Structures Conference
14th AIAA. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-1835.

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Mendez Ramos, Eugina D., Pranay Mishra, Stephen Edwards, and Dimitri Mavris. "Response Surface Regressions for Low-Thrust Interplanetary Mission Design." In AIAA SPACE 2016. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-5651.

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Reports on the topic "Response surface design"

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Crosier, Ronald B. Some New Three-Level Response Surface Designs. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada243964.

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Robinson, W. Evaluation of thin flexible pavements under simulated aircraft traffic. Engineer Research and Development Center (U.S.), December 2020. http://dx.doi.org/10.21079/11681/39161.

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A full-scale airfield pavement test section was constructed and trafficked by the U.S. Army Engineer Research and Development Center (ERDC) to evaluate the performance of relatively thin airfield pavement structures. The test section consisted of 16 test items that included three asphalt pavement thicknesses and two different aggregate base courses. The test items were subjected to simulated aircraft traffic to evaluate their response and performance to realistic aircraft loads and to evaluate the effect of reductions in tire pressure on thin asphalt pavement. Rutting behavior, pavement cracking, instrumentation response, and falling weight deflectometer response were monitored at selected traffic intervals. The results of this study were used to extend existing Department of Defense pavement design and evaluation techniques to include the evaluation of airfield pavement sections that do not meet the current criteria for aggregate base quality and minimum asphalt concrete surface thickness. These performance data were used to develop new aggregate base failure design curves using existing stress-based design methodology.
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Berkowitz, Jacob, Christine VanZomeren, Nia Hurst, and Kristina Sebastian. An evaluation of soil phosphorus storage capacity (SPSC) at proposed wetland restoration locations in the western Lake Erie Basin. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42108.

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Historical loss of wetlands coupled with excess phosphorus (P) loading at watershed scales have degraded water quality in portions of the western Lake Erie Basin (WLEB). In response, efforts are underway to restore wetlands and decrease P loading to surface waters. Because wetlands have a finite capacity to retain P, researchers have developed techniques to determine whether wetlands function as P sources or sinks. The following technical report evaluates the soil P storage capacity (SPSC) at locations under consideration for wetland restoration in collaboration with the Great Lakes Restoration Initiative (GLRI) and the H2Ohio initiative. Results indicate that the examined soils display a range of P retention capacities, reflecting historic land-use patterns and management regimes. However, the majority of study locations exhibited some capacity to sequester additional P. The analysis supports development of rankings and comparative analyses of areas within a specific land parcel, informing management through design, avoidance, removal, or remediation of potential legacy P sources. Additionally, the approaches described herein support relative comparisons between multiple potential wetland development properties. These results, in conjunction with other data sources, can be used to target, prioritize, justify, and improve decision-making for wetland management activities in the WLEB.
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Doyle, Jesse D., Nolan R. Hoffman, and M. Kelvin Taylor. Aircraft Arrestor System Panel Joint Improvement. U.S. Army Engineer Research and Development Center, August 2021. http://dx.doi.org/10.21079/11681/41342.

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Aircraft Arresting Systems (AAS) for military applications utilize sacrificial panels made of Ultra-High Molecular Weight polyethylene (UHMWPE) that are embedded into the pavement beneath the AAS cable to protect the pavement from cable damage. Problems have been observed with the materials and practices used to seal the UHMWPE panel joints from water and debris. Data obtained from laboratory and field studies were used make improvements to current practice for sealing UHMWPE panel joints. The study evaluated four joint-sealant materials, eight alternative surface treatment and preparation techniques to promote adhesion to UHMWPE, and seven joint-edge geometries. Bond-strength testing of joint-sealant specimens was conducted in the laboratory, followed by field evaluation of construction techniques. Field performance of the joint systems was monitored for 24 months after installation. Additionally, a thermal response model was developed to refine the joint design dimensions. Results confirmed that the best material to use was self-leveling silicone joint sealant. It was recommended that a dovetail groove be cut into the edge of UHMW panels to provide positive mechanical interlock and to reduce adhesive failures of the sealant. It was also recommended that the panel-to-panel joint-sealant reservoir be widened to prevent sealant compression damage.
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Bowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor, and Jeffrey Williams. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2284622.

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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threatened by numerous stressors, most of which originate outside park boundaries. Stream condition and ecosystem health are dependent on processes occurring in the entire watershed as well as riparian and floodplain areas; therefore, they cannot be manipulated independently of this interrelationship. Land use activities—such as timber management, landfills, grazing, confined animal feeding operations, urbanization, stream channelization, removal of riparian vegetation and gravel, and mineral and metals mining—threaten stream quality. Accordingly, the framework for this aquatic monitoring is directed towards maintaining the ecological integrity of the streams in those parks. Invertebrates are an important tool for understanding and detecting changes in ecosystem integrity, and they can be used to reflect cumulative impacts that cannot otherwise be detected through traditional water quality monitoring. The broad diversity of invertebrate species occurring in aquatic systems similarly demonstrates a broad range of responses to different environmental stressors. Benthic invertebrates are sensitive to the wide variety of impacts that influence Ozark streams. Benthic invertebrate community structure can be quantified to reflect stream integrity in several ways, including the absence of pollution sensitive taxa, dominance by a particular taxon combined with low overall taxa richness, or appreciable shifts in community composition relative to reference condition. Furthermore, changes in the diversity and community structure of benthic invertebrates are relatively simple to communicate to resource managers and the public. To assess the natural and anthropo-genic processes influencing invertebrate communities, this protocol has been designed to incorporate the spatial relationship of benthic invertebrates with their local habitat including substrate size and embeddedness, and water quality parameters (temperature, dissolved oxygen, pH, specific conductance, and turbidity). Rigid quality control and quality assurance are used to ensure maximum data integrity. Detailed standard operating procedures (SOPs) and supporting information are associated with this protocol.
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