Relevant bibliographies by topics / Time-varying effect modeling

Academic literature on the topic 'Time-varying effect modeling'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Time-varying effect modeling"

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Shiyko, Mariya P., Jack Burkhalter, Runze Li, and Bernard J. Park. "Modeling nonlinear time-dependent treatment effects: An application of the generalized time-varying effect model (TVEM)." Journal of Consulting and Clinical Psychology 82, no. 5 (October 2014): 760–72. http://dx.doi.org/10.1037/a0035267.

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Ruhe, Constantin. "Estimating Survival Functions after Stcox with Time-varying Coefficients." Stata Journal: Promoting communications on statistics and Stata 16, no. 4 (December 2016): 867–79. http://dx.doi.org/10.1177/1536867x1601600404.

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In many applications of the Cox model, the proportional-hazards assumption is implausible. In these cases, the solution to nonproportional hazards usually consists of modeling the effect of the variable of interest and its interaction effect with some function of time. Although Stata provides a command to implement this interaction in stcox, it does not allow the typical visualizations using stcurve if stcox was estimated with the tvc() option. In this article, I provide a short workaround that estimates the survival function after stcox with time-dependent coefficients. I introduce and describe the scurve_tvc command, which automates this procedure and allows users to easily visualize survival functions for models with time-varying effects.
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Danieli, Coraline, and Michal Abrahamowicz. "Competing risks modeling of cumulative effects of time-varying drug exposures." Statistical Methods in Medical Research 28, no. 1 (September 7, 2017): 248–62. http://dx.doi.org/10.1177/0962280217720947.

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An accurate assessment of drug safety or effectiveness in pharmaco-epidemiology requires defining an etiologically correct time-varying exposure model, which specifies how previous drug use affects the hazard of the event of interest. An additional challenge is to account for the multitude of mutually exclusive events that may be associated with the use of a given drug. To simultaneously address both challenges, we develop, and validate in simulations, a new approach that combines flexible modeling of the cumulative effects of time-varying exposures with competing risks methodology to separate the effects of the same drug exposure on different outcomes. To account for the dosage, duration and timing of past exposures, we rely on a spline-based weighted cumulative exposure modeling. We also propose likelihood ratio tests to test if the cumulative effects of past exposure on the hazards of the competing events are the same or different. Simulation results indicate that the estimated event-specific weight functions are reasonably accurate, and that the proposed tests have acceptable type I error rate and power. In real-life application, the proposed method indicated that recent use of antihypertensive drugs may reduce the risk of stroke but has no effect on the hazard of coronary heart disease events.
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Kumari, S., and A. Singh. "Effect of Correlations on Routing and Modeling of Time-varying Communication Networks." Acta Physica Polonica B 50, no. 2 (2019): 199. http://dx.doi.org/10.5506/aphyspolb.50.199.

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Flannery, Kaitlin M., Anna Vannucci, and Christine McCauley Ohannessian. "Using Time-Varying Effect Modeling to Examine Age-Varying Gender Differences in Coping Throughout Adolescence and Emerging Adulthood." Journal of Adolescent Health 62, no. 3 (March 2018): S27—S34. http://dx.doi.org/10.1016/j.jadohealth.2017.09.027.

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Fletcher, Robin P., and Johan O. Robertsson. "Time-varying boundary conditions in simulation of seismic wave propagation." GEOPHYSICS 76, no. 1 (January 2011): A1—A6. http://dx.doi.org/10.1190/1.3511526.

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We propose two new boundary conditions to regulate coherent reflections from the model boundaries in numerical solutions of wave equations. Both boundary conditions have the common feature that the boundary condition is varied with respect to time. The first boundary condition expands or contracts the computational model during a modeling simulation. The effect is to cause a Doppler shift in the reflected wavefield that can be used to shift energy outside a frequency band of interest. In addition, when the computational domain is expanding, the range of possible incidence angles on the boundary is restricted. This can be used to increase the effectiveness of many existing absorbing boundary conditions that are more effective for incidence angles close to normal. The second boundary condition is an extension of random boundaries. By carefully changing the realization of a random boundary over time, a more diffusive wavefield can be simulated. We show results with 2D numerical simulations of the scalar wave equation for both these boundary conditions. The first boundary condition has application to modeling, but both these boundary conditions have potential application within algorithms that rely upon modeling kernels, such as reverse-time migration and full-waveform inversion.
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Feingold, Alan. "Time-Varying Effect Sizes for Quadratic Growth Models in Multilevel and Latent Growth Modeling." Structural Equation Modeling: A Multidisciplinary Journal 26, no. 3 (December 20, 2018): 418–29. http://dx.doi.org/10.1080/10705511.2018.1547110.

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Wei, Bowen, Minghan Gu, Huokun Li, Wei Xiong, and Zhenkai Xu. "Modeling method for predicting seepage of RCC dams considering time-varying and lag effect." Structural Control and Health Monitoring 25, no. 2 (August 11, 2017): e2081. http://dx.doi.org/10.1002/stc.2081.

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Xiao, Zhengming, Jinxin Cao, and Yinxin Yu. "Mathematical Modeling and Dynamic Analysis of Planetary Gears System with Time-Varying Parameters." Mathematical Problems in Engineering 2020 (March 16, 2020): 1–9. http://dx.doi.org/10.1155/2020/3185624.

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Planetary gears are widely used in automobiles, helicopters, heavy machinery, etc., due to the high speed reductions in compact spaces; however, the gear fault and early damage induced by the vibration of planetary gears remains a key concern. The time-varying parameters have a vital influence on dynamic performance and reliability of the gearbox. An analytical model is proposed to investigate the effect of gear tooth crack on the gear mesh stiffness, and then the dynamical model of the planetary gears with time-varying parameters is established. The natural characteristics of the transmission system are calculated, and the dynamic responses of transmission components, as well as dynamic meshing force of each pair of gear are investigated based on varying internal excitations induced by time-varying parameters and tooth root crack. The effects of gear tooth root crack size on the planetary gear dynamics are simulated, and the mapping rules between damage degree and gear dynamics are revealed. In order to verify the theoretical model and simulation results, the planetary gear test rig was built by assembling faulty and healthy gear separately. The failure mechanism and dynamic characteristics of the planetary gears with tooth root crack are clarified by comparing the analytical results and experimental data.
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Haneuse, S. J. P. A., K. D. Rudser, and D. L. Gillen. "The separation of timescales in Bayesian survival modeling of the time-varying effect of a time-dependent exposure." Biostatistics 9, no. 3 (November 19, 2007): 400–410. http://dx.doi.org/10.1093/biostatistics/kxm038.

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Dissertations / Theses on the topic "Time-varying effect modeling"

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Sylvestre, Marie-Pierre. "Flexible modelling for the cumulative effects of time-varying exposure, weighted by recency, on the hazard." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=111917.

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Many epidemiological studies assess the effects of time-dependent exposures, where both the exposure status and its intensity vary over time. The analysis of such studies poses the challenge of modelling the association between complex time-dependent drug exposure and the risk, especially given the uncertainty about the etiological relevance of doses taken in different time periods.
To address this challenge, I developed a flexible method for modelling cumulative effects of time-varying exposures, weighted by recency, represented by time-dependent covariates in the Cox proportional hazards model. The function that assigns weights to doses taken in the past is estimated using cubic regression splines. Models with different number of knots and constraints are estimated. Bootstrap techniques are used to obtain pointwise confidence bands around the weight functions, accounting for both the sampling variation of the regression coefficients, and the uncertainty at the model selection stage, i.e. the additional variance due to a posteriori selection of the number of knots.
To assess the method in simulations, I had to develop and validate a novel algorithm to generate event times conditional on time-dependent covariates and compared it with the algorithms available in the literature. The proposed algorithm extends a previously proposed permutational algorithm to include a rejection sampler. While all the algorithms generated data sets that, once analyzed, provided virtually unbiased estimates with comparable variances, the algorithm that I proposed reduced the computational time by more than 50 per cent relative to alternative methods. I used simulations to systematically investigate the properties of the weighted cumulative dose method. Six different weight functions were considered. Simulations showed that in most situations, the proposed method was able to capture the shape of the true weight functions and to produce estimates of the magnitude of the exposure effect on the risk that were close to those used to generate the data. I finally illustrated the use of the weighted cumulative dose modelling by reassessing the association between the use of selected benzodiazepines and fall-related injuries, using administrative data on a cohort of elderly who initiated their use of benzodiazepines between 1990 and 2004.
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Hori, Kazuki. "Disaggregating Within-Person and Between-Person Effects in the Presence of Linear Time Trends in Time-Varying Predictors: Structural Equation Modeling Approach." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/103624.

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Educational researchers are often interested in phenomena that unfold over time within a person and at the same time, relationships between their characteristics that are stable over time. Since variables in a longitudinal study reflect both within- and between-person effects, researchers need to disaggregate them to understand the phenomenon of interest correctly. Although the person-mean centering technique has been believed as the gold standard of the disaggregation method, recent studies found that the centering did not work when there was a trend in the predictor. Hence, they proposed some detrending techniques to remove the systematic change; however, they were only applicable to multilevel models. Therefore, this dissertation develops novel detrending methods based on structural equation modeling (SEM). It also establishes the links between centering and detrending by reviewing a broad range of literature. The proposed SEM-based detrending methods are compared to the existing centering and detrending methods through a series of Monte Carlo simulations. The results indicate that (a) model misspecification for the time-varying predictors or outcomes leads to large bias of and standard error, (b) statistical properties of estimates of the within- and between-person effects are mostly determined by the type of between-person predictors (i.e., observed or latent), and (c) for unbiased estimation of the effects, models with latent between-person predictors require nonzero growth factor variances, while those with observed predictors at the between level need either nonzero or zero variance, depending on the parameter. As concluding remarks, some practical recommendations are provided based on the findings of the present study.
Doctor of Philosophy
Educational researchers are often interested in longitudinal phenomena within a person and relations between the person's characteristics. Since repeatedly measured variables reflect their within- and between-person aspects, researchers need to disaggregate them statistically to understand the phenomenon of interest. Recent studies found that the traditional centering method, where the individual's average of a predictor was subtracted from the original predictor value, could not correctly disentangle the within- and between-person effects when the predictor showed a systematic change over time (i.e., trend). They proposed some techniques to remove the trend; however, the detrending methods were only applicable to multilevel models. Therefore, the present study develops novel detrending methods using structural equation modeling. The proposed models are compared to the existing methods through a series of Monte Carlo simulations, where we can manipulate a data-generating model and its parameter values. The results indicate that (a) model misspecification for the time-varying predictor or outcome leads to systematic deviation of the estimates from their true values, (b) statistical properties of estimates of the effects are mostly determined by the type of between-person predictors (i.e., observed or latent), and (c) the latent predictor models require nonzero growth factor variances for unbiased estimation, while the observed predictor models need either nonzero or zero variance, depending on the parameter. As concluding remarks, some recommendations for the practitioners are provided.
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Greene, Mallik. "Modeling the Dynamics on the Effectiveness of Marketing Mix Elements." 2014. http://scholarworks.gsu.edu/bus_admin_diss/43.

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The objective of this study is to conduct a marketing mix modeling to measure the effectiveness of past marketing activities on the product sales using a time-varying effect model (TVEM) approach. The longitudinal intensive data for this study has come from a large ice cream manufacturer in USA. Traditionally, static regression models have been used to measure the effectiveness of marketing mix variables to predict sales. And, these models used to find the time independent effect of the covariate on the dependent variable. On the other hand, a dynamic model such as time-varying effect model takes time into consideration. Researchers can model the changes in the relationship between dependent and independent variables over time using time-varying effect model. This is the first study, where a time-varying effect model approach has been used to measure the effectiveness of marketing mix elements in the ice cream industry. In addition, we have compared the predictive validity of both static and dynamic models using this data set.
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Kalendra, Eric James. "Space-time modeling of health effects while controlling for spatially varying exposure surfaces." 2010. http://www.lib.ncsu.edu/resolver/1840.16/6027.

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Books on the topic "Time-varying effect modeling"

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0.

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Linden-Carmichael, Ashley N., and Stephanie T. Lanza. Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences. Springer International Publishing AG, 2022.

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Linden-Carmichael, Ashley N., and Stephanie T. Lanza. Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences. Springer International Publishing AG, 2021.

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Buu, Anne, and Runze Li. New Statistical Methods Inspired by Data Collected from Alcohol and Substance Abuse Research. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190676001.003.0021.

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This chapter provides a nontechnical review of new statistical methodology for longitudinal data analysis that has been published in statistical journals in recent years. The methodology has applications in four important areas: (1) conducting variable selection among many highly correlated risk factors when the outcome measure is zero-inflated count; (2) characterizing developmental trajectories of symptomatology using regression splines; (3) modeling the longitudinal association between risk factors and substance use outcomes as time-varying effects; and (4) testing measurement reactivity and predictive validity using daily process data. The excellent statistical properties of the methods introduced have been supported by simulation studies. The applications in alcohol and substance abuse research have also been demonstrated by graphs on real longitudinal data.
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Book chapters on the topic "Time-varying effect modeling"

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Time-Varying Effect Modeling to Study Age-Varying Associations." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 93–104. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_4.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Time-Varying Effect Modeling for Intensive Longitudinal Data." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 117–31. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_6.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "A Conceptual Introduction to Time-Varying Effect Modeling." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 1–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_1.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Time-Varying Effect Modeling to Study Historical Change." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 105–16. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_5.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Specifying, Estimating, and Interpreting Time-Varying Effect Models." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 17–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_2.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Generalized Time-Varying Effect Models for Binary and Count Outcomes." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 51–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_3.

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Lanza, Stephanie T., and Ashley N. Linden-Carmichael. "Further Applications and Future Directions." In Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences, 133–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70944-0_7.

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Tiwari, Binod, and Duc Tran. "Using Experimental Models to Calibrate Numerical Models for Slope Stability and Deformation Analysis." In Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022, 185–95. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16898-7_13.

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AbstractLandslides cause significant loss of lives and properties globally. Rainfall and earthquake are considered to be two frequent causes of landslides although there are dozens of natural or anthropogenic triggers of landslides. Experimental or numerical analyses by varying a single parameter—while keeping other triggers constant—help researchers/practitioners to understand the influence of each triggering factor on slope stability/landslides. However, experimental modeling of landslides in laboratory is exhaustive, time consuming, and expensive process. There are various experimental methods available for such modeling—ranging from centrifuge modeling to small scale 1 g models—depending on the need, available resources, and funds. With the wide availability of materials and development of better sensors/instruments, our capability to perform laboratory experiments, specifically for landslide modeling, has been much easier and accessible in recent decades. Such experiments are valuable to calibrate numerical models so that various analyses can be performed on the real-world problems. In this study, we prepared laboratory scale slopes in Plexiglas containers at varying densities and slope inclinations, and instrumented the slopes properly to measure real time suction, displacement, advancement of wetting front, and accelerations at various locations and depths within the model. The slopes were subjected to rainfall and/or earthquake shaking to evaluate the effect of rainfall and earthquakes—separately and combined—on slope stability. The experimental results were used to calibrate the numerical modeling effort so that a full spectrum of sensitivity analyses could be performed for a slope located in an expensive neighborhood of Southern California.
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West, Mike, and Mark Berliner. "Modelling Time-Varying Hazards and Covariate Effects." In Survival Analysis: State of the Art, 47–62. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-015-7983-4_4.

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Cheng, Yougan, Ronny Straube, Abed E. Alnaif, Lu Huang, Tarek A. Leil, and Brian J. Schmidt. "Virtual Populations for Quantitative Systems Pharmacology Models." In Methods in Molecular Biology, 129–79. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2265-0_8.

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AbstractQuantitative systems pharmacology (QSP) places an emphasis on dynamic systems modeling, incorporating considerations from systems biology modeling and pharmacodynamics. The goal of QSP is often to quantitatively predict the effects of clinical therapeutics, their combinations, and their doses on clinical biomarkers and endpoints. In order to achieve this goal, strategies for incorporating clinical data into model calibration are critical. Virtual population (VPop) approaches facilitate model calibration while faced with challenges encountered in QSP model application, including modeling a breadth of clinical therapies, biomarkers, endpoints, utilizing data of varying structure and source, capturing observed clinical variability, and simulating with models that may require more substantial computational time and resources than often found in pharmacometrics applications. VPops are frequently developed in a process that may involve parameterization of isolated pathway models, integration into a larger QSP model, incorporation of clinical data, calibration, and quantitative validation that the model with the accompanying, calibrated VPop is suitable to address the intended question or help with the intended decision. Here, we introduce previous strategies for developing VPops in the context of a variety of therapeutic and safety areas: metabolic disorders, drug-induced liver injury, autoimmune diseases, and cancer. We introduce methodological considerations, prior work for sensitivity analysis and VPop algorithm design, and potential areas for future advancement. Finally, we give a more detailed application example of a VPop calibration algorithm that illustrates recent progress and many of the methodological considerations. In conclusion, although methodologies have varied, VPop strategies have been successfully applied to give valid clinical insights and predictions with the assistance of carefully defined and designed calibration and validation strategies. While a uniform VPop approach for all potential QSP applications may be challenging given the heterogeneity in use considerations, we anticipate continued innovation will help to drive VPop application for more challenging cases of greater scale while developing new rigorous methodologies and metrics.
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Conference papers on the topic "Time-varying effect modeling"

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Abraham, J. P., E. M. Sparrow, J. C. K. Tong, and W. J. Minkowycz. "Intermittent Flow Modeling: Part 2—Time-Varying Flows and Flows in Variable Area Ducts." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22696.

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The all-flow-regime model of fluid flow, previously applied in [1] to flows with axially and temporally uniform Reynolds numbers, has been implemented here for flows in which the Reynolds number may either vary with time or along the length of a pipe. In the former situation, the timewise variations were driven by a harmonically oscillating inlet flow. These oscillations created a succession of flow-regime transitions encompassing purely laminar and purely turbulent flows as well as laminarizing and turbulentizing flows where intermittency prevailed. The period of the oscillations was increased parametrically until the quasi-steady regime was attained. The predicted quasi-steady friction factors were found to be in excellent agreement with those from a simple model under which the flow is assumed to pass through a sequence of instantaneous steady states. In the second category of non-constant-Reynolds-number flows, axial variations of a steady flow were created by means of a finite-length conical enlargement which connected a pair of pipes of constant but different diameters. The presence of the cross-sectional enlargement gives rise to a reduction of the Reynolds number that is proportional to the ratio of the diameters of the upstream and the downstream pipes. Depending on the magnitude of the upstream inlet Reynolds number, the downstream fully developed flow could variously be laminar, intermittent, or turbulent. The presence or absence of flow separation in the conical enlargement had a direct effect on the laminarization process. For both categories of non-constant-Reynolds-number flows, laminarization and turbulentization were quantified by the ratio of the rate of turbulence production to the rate of turbulence destruction.
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Takahashi, Yoshitaka, and Nobuyuki Shimizu. "Seismic Response Analysis System by Means of Multibody Dynamics Approach: Modeling and Analysis of Geometric Time Varying Structure Systems." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84378.

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In Japan, the seismic design methods for structures are developed in the civil and architectural fields. And these seismic design technologies have also been brought to mechanical structures such as piping facilities and boiler structures, etc.. But, for the geometric time varying structure of which geometric configuration is dependent on time such as cranes, the kinetic and the dynamic characteristics of such structures are not fully considered in the seismic response analyses. In this paper, we try the modeling of the geometric time varying structure systems by means of the method of multibody dynamics. And we examine the effect of the geometric time varying system on the seismic response. The beam elements formulated by the absolute nodal coordinate are used to model the structure that has large displacement motion of the base of the structure. The crane structure for the building construction is modeled in the numerical example. The seismic responses of the moving boom part of the crane model are simulated. New phenomenon has been explored.
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Viswanathan, Chandramouli, Chenn Zhou, John Moreland, and Site Guo. "Usefulness of Virtual 3D Modeling to Visualize the Effect of Uncertain Data in Groundwater Solute Transport." In ASME 2011 World Conference on Innovative Virtual Reality. ASMEDC, 2011. http://dx.doi.org/10.1115/winvr2011-5584.

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Immersive virtual reality models can be effectively used in understanding the system behavior. It will also help the students to understand the influences of boundary conditions by reflection. In particular, those systems which are not suitable for laboratory experiment can be handled using virtual reality platform. In this research, groundwater solute transport simulation was developed as a laboratory module. Groundwater system movement takes place beneath ground. Recently, several sites were contaminated due to manmade activities. This complex process is very difficult to understand with varying boundary conditions. If there is an uncertainity associated with the modeling parameters, remedial alternatives planned may be not as effective as expected. Behavior changes under these circumstances can be tackled through a sensitivity analysis and incorporated in virtual 3D. In this study, by varying the hydraulic conductivity systematically in different layers, the possible variations in the groundwater contamination plume movements were examined for different simulation time domains with remedial alternatives.
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Boone, C., M. Fuest, K. Wellmerling, and S. Prakash. "Effect of Time Dependent Excitation Signals on Gating in Nanofluidic Channels." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-53038.

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Nanofluidic field effect devices feature a gate electrode embedded in the nanochannel wall. The gate electrode creates local variation in the electric field allowing active, tunable control of ionic transport. Tunable control over ionic transport through nanofluidic networks is essential for applications including artificial ion channels, ion pumps, ion separation, and biosensing. Using DC excitation at the gate, experiments have demonstrated multiple current states in the nanochannel, including the ability to switch off the measured current; however, experimental evaluation of transient signals at the gate electrode has not been explored. Modeling results have shown ion transport at the nanoscale has known time scales for diffusion, electromigration, and convection. This supports the evidence detailed here that use of a time-dependent signal to create local perturbation in the electric field can be used for systematic manipulation of ionic transport in nanochannels. In this report, sinusoidal waveforms of various frequencies were compared against DC excitation on the gate electrode. The ionic transport was quantified by measuring the current through the nanochannels as a function of applied axial and gate potentials. It was found that time varying signals have a higher degree of modulation than a VRMS matched DC signal.
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Griffin, Steven, and Karl Schrader. "Structural Modeling Considerations for Dynamic Optical Space Structure Simulations." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/ad-23748.

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Abstract Boeing-SVS has developed an integrated modeling tool, Zelink, which effectively combines three commercial standard codes, Zemax, Simulink and Nastran, to predict the effect of quasistatic and dynamic disturbances on optical metrics of interest in optical space structures. Examples of optical metrics are time-varying wavefront error, point spread functions and predictions of image degradation. A simulation might involve specification of a slew angle and prediction of time-varying wavefront error. Different command shaping and attitude control techniques might be evaluated with respect to their ability to minimize wavefront error. Implementation of such simulations has shown significant dependence of simulation results on the structural modeling approach. In particular, one approach may introduce errors in the optical metric of interest, where another approach may avoid errors. The sensitivity of the optical metric is related to the necessity of maintaining the optical prescription when there is no structural deformation. A quasistatic rotation of the space structure should not significantly distort the optical prescription, since there is almost no structural deformation associated with this maneuver. This paper discusses structural modeling approaches and makes recommendations specific to optical space structure simulations.
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Kowalski, William J., Berk M. Yigit, David J. R. Hutchon, and Kerem Pekkan. "Transition From the Fetal to Neonatal Circulation: Modeling the Effect of Umbilical Cord Clamping." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14431.

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The transition from fetal to neonatal circulation requires a concert of events to transfer gas exchange function from the placenta to the lungs and separate the pulmonary and systemic pathways. Pulmonary vascular resistance (PVR) rapidly decreases within the first minutes of extrauterine life and continues to gradually decrease during the first week, increasing pulmonary blood flow and reducing pulmonary pressure [1, 2]. Umbilical vessels constrict, removing the placental circulation and leading to closure of the ductus venosus (DV) [2]. The increased left atrial filling and reduced right atrial filling results in permanent closure of the flap of the foramen ovale, removing the R→L interatrial shunt. Closure of the ductus arteriosus (DA) completes the separation of the pulmonary and systemic circulations by 48 hours in 82% of term newborns and by 96 hours in 100% [3]. Removal of the placental circulation is routinely achieved by umbilical cord clamping (UCC) immediately after birth. This practice, however, has been called into question by many studies, which suggest that continued umbilical flow in the early neonate is beneficial, and immediate UCC can lead to infant anemia [4, 5]. Due to routine UCC, the effects of this practice on transitional flow patterns are largely unknown [1, 6]. We therefore developed a lumped parameter model (LPM) to study the role of UCC in the fetal to neonatal transition. Our model includes time-varying resistance functions that allow us to simulate the opening of the PVR and closure of the DA and umbilical vessels. This model demonstrates that UCC can lead to an earlier onset of DA flow reversal and slightly reduced cardiac output (CO).
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7

Peng, Tao, Teik C. Lim, and Junyi Yang. "Eccentricity Effect Analysis in Right-Angle Gear Dynamics." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47579.

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Geometric eccentricity here refers to the radial deviation (radial runout) of pinion or gear geometric center off its rotational center or axis. Such a typical manufacturing or assembly error in gear transmission exhibits inherent effects on the gear dynamic responses. Modeling of eccentricity has rarely been done for high speed right-angle gears such as hypoid or spiral bevel gears. In this paper, two modeling methods are proposed to quantitatively represent the eccentricity in the hypoid/bevel gear dynamic analysis. The first method is based on the loaded tooth contact analysis (LTCA) for a long shaft period. The LTCA results are then used to synthesize the corresponding roll angle dependent varying mesh model parameters. A second simpler method using translational kinematic transmission error (TE) modification is proposed to reduce the computational time. The effects of eccentricity on the gear dynamic responses are then investigated. The eccentricity excited low frequency shaft order dynamics is found to affect not only the overall level of vibration but also the high frequency mesh order responses. The sideband responses are simulated and characterized. This study is expected to improve the right-angle gearing system dynamic analytical capability and assist in guiding the manufacturing or assembly error tolerance specification.
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Debusschere, Nic, Matthieu De Beule, Peter Dubruel, Patrick Segers, and Benedict Verhegghe. "Finite Element Modeling of Biodegradable Stents." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14493.

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Biodegradable stents, which temporarily support a stenotic blood vessel and afterwards fully disappear, have recently gained a lot of interest. They avoid long-term complications associated with conventional stents such as late stent thrombosis and in-stent restenosis. Moreover, degradable stents allow for a restoration of vasomotion and vessel growth which makes them particularly suitable for pediatric applications [1]. Finite element simulations have proven to be an efficient and cost-effective tool to investigate and optimize the mechanical performance of minimal invasive devices such as stents [2]. Biodegradable stents have however created new challenges in their design and optimization via finite element analysis because of their complex time-varying material behavior. To correctly simulate the mechanical behavior of biodegradable stents, a model should be developed that incorporates the effect of degradation upon all material characteristics. By combining existing constitutive material models based on continuum damage theory we were able to create such a virtual environment in which the transitional mechanical behavior of biodegradable stents can be investigated.
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9

Xia, Ting. "Modeling Peripheral Muscle Fatigue Using a Variable Recovery Rate." In Applied Human Factors and Ergonomics Conference. AHFE International, 2018. http://dx.doi.org/10.54941/ahfe100077.

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Muscle fatigue is a transient and reversible decrease in performance capacity after a period of physical exertion. A variety of approaches have been applied to model muscle fatigue. Recently a theoretical, phenomenal parameter-based model (Liu-Xia model) was proposed with the capability of predicting fatigue for tasks of any force-time history. The Liu-Xia model has two parameters F and R that define the fatigue and recovery behavior, respectively. Previously, F and R were treated as constant in model validation. In the current study, R is redefined as a function of exertion level in attempt to reflect the effect of muscle contraction on blood flow. The purpose is to examine if an R varying with exertion level can improve model prediction for low intensity, static and intermittent tasks. Particularly, R is modeled as a step-wise function of three regions: 0-10% maximum voluntary contraction (MVC), no occlusion; 10-50% MVC, 0-100% occlusion, assuming a linear relationship in the region; and 51-100%, full occlusion. The results suggest that an R varying with exertion level may serve as a viable way to improve model performance, dependent on a better modeling of the relationship between muscle contraction and blood flow.
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Srinil, Narakorn, Marian Wiercigroch, Patrick O’Brien, and Rae Younger. "Vortex-Induced Vibration of Catenary Riser: Reduced-Order Modeling and Lock-In Analysis Using Wake Oscillator." In ASME 2009 28th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/omae2009-79166.

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A novel reduced-order fluid-structure interaction model for the vortex-induced vibration of catenary riser subject to the ocean current is developed and systematically investigated. The semi analytical-numerical approach accommodates multi-mode nonlinear dynamic responses and accounts for the effect of varying initial curvature of the inclined flexible cylinder. The geometrically nonlinear equations of riser motion are based on a pinned-pinned beam-cable model with bending and extensibility stiffness. The empirical hydrodynamic model is based on a distributed van der Pol wake oscillator which approximates the space-time varying fluid forces. In this initial study, the incoming current flow is assumed to be steady, uniform, unidirectional and perpendicular to the riser initial plane of curvatures. Thus, emphasis is placed on evaluating the riser cross-flow responses due to fluctuating lift forces. A preliminary validation of model and analysis results has been performed. Several insights into the vortex-induced vibration of catenary risers are highlighted through a series of parametric studies. These include the characterization of single-mode vs. multi-mode lock-in, the limitations of a single-mode solution through a convergence analysis which accounts for a varying number of considered riser modes, the prediction of riser maximum response amplitudes, the quantitative/qualitative behaviors of tension- or beam-dominant catenary risers and the overall influence of fluid-riser parameters. Moreover, recent industrial concepts of modes switching/sharing are discussed along with the meaningful effect of Reynolds number.
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Reports on the topic "Time-varying effect modeling"

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Hauzenberger, Niko, Florian Huber, Gary Koop, and James Mitchell. Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland, January 2023. http://dx.doi.org/10.26509/frbc-wp-202305.

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In light of widespread evidence of parameter instability in macroeconomic models, many time-varying parameter (TVP) models have been proposed. This paper proposes a nonparametric TVP-VAR model using Bayesian additive regression trees (BART). The novelty of this model stems from the fact that the law of motion driving the parameters is treated nonparametrically. This leads to great flexibility in the nature and extent of parameter change, both in the conditional mean and in the conditional variance. In contrast to other nonparametric and machine learning methods that are black box, inference using our model is straightforward because, in treating the parameters rather than the variables nonparametrically, the model remains conditionally linear in the mean. Parsimony is achieved through adopting nonparametric factor structures and use of shrinkage priors. In an application to US macroeconomic data, we illustrate the use of our model in tracking both the evolving nature of the Phillips curve and how the effects of business cycle shocks on inflationary measures vary nonlinearly with movements in uncertainty.
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