Convergence Analysis and Experimental Validation of a Fused Numerical/Experimental Active System Optimization Framework

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Nihar Deodhar ◽  
Christopher Vermillion
Keyword(s):  
Numerical Model ◽  
Design Optimization ◽  
Convergence Analysis ◽  
Experimental Validation ◽  
Estimation Error ◽  
System Optimization ◽  
Response Surfaces ◽  
Optimization Framework ◽  
Quality Of Fit

This paper presents a convergence analysis and experimental validation of an iterative design optimization framework that fuses numerical simulations with experiments. At every iteration, a G-optimal design generates a set of simulations and experiments that are used to characterize response surfaces. A subset of the experiments termed as the training points are used to fit a combined numerical/experimental response. This numerical response is obtained as a result of numerical model correction via experiments. The quality of fit for this combined response is evaluated using the remaining validation points. Based on the quality of fit, the feasible design space is reduced for a given confidence interval using hypothesis testing. A convergence analysis of the framework quantifies the closeness of the corrected numerical model to the true system as a function of response estimation error. This design optimization framework, along with the convergence result, is validated through an airborne wind energy (AWE) application using a lab-scale water channel setup. The quality of flight is greatly improved by optimizing the center of mass location, pitch angle set point, horizontal and vertical stabilizer areas using an effective experimental infusion as compared to a pure numerically optimized design.

Experimentally-Infused Active System Optimization Framework: Theoretical Convergence Analysis and Airborne Wind Energy Case Study

2018 ◽  
Author(s):  
Nihar Deodhar ◽  
Christopher Vermillion
Keyword(s):  
Numerical Model ◽  
Wind Energy ◽  
Convergence Analysis ◽  
Design Space ◽  
System Optimization ◽  
System Response ◽  
Optimization Strategy ◽  
Active System ◽  
True System ◽  
Iterative Framework

This research presents a convergence analysis for an iterative framework for optimizing plant and controller parameters for active systems. The optimization strategy fuses expensive yet valuable experiments with less accurate yet cheaper simulations. The numerical model is improved at each iteration through a cumulative correction law, using an optimally designed set of experiments. The iterative framework reduces the feasible design space between iterations, ultimately yielding convergence to a small design space that contains the optimum. This paper presents the derivation of an asymptotic upper bound on the difference between the corrected numerical model and true system response. Furthermore, convergence of the numerical model to the true system response and convergence of the design space are demonstrated on an airborne wind energy (AWE) application.

scholarly journals Learning As It Happens: A Decade of Analyzing and Shaping a Large-Scale Online Learning System

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Matthieu J. S. Brinkhuis ◽  
Alexander O. Savi ◽  
Abe D. Hofman ◽  
Frederik Coomans ◽  
Han L. J. Van der Maas ◽  
...  
Keyword(s):  
Online Learning ◽  
Large Scale ◽  
Response Times ◽  
Learning System ◽  
Learning Gains ◽  
Online Experimentation ◽  
Quality Of Fit ◽  
Item Reliability ◽  
Made In

With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion responses. We present the methods we use to both steer and analyze this system in real-time, using scoring rules on accuracy and response times, a tailored rating system to provide both learners and items with current ability and difficulty ratings, and an adaptive engine that matches learners to items. Moreover, we explore the quality of fit by means of prediction accuracy and parallel item reliability. Limitations and pitfalls are discussed by diagnosing sources of misfit, like violations of unidimensionality and unforeseen dynamics. Finally, directions for development are discussed, including embedded learning analytics and a focus on online experimentation to evaluate both the system itself and the users’ learning gains. Though many challenges remain open, we believe that large steps have been made in providing methods to efficiently manage and research educational big data from a massive online learning system.

scholarly journals Moisture Desorption Studies on Polymer Hydrated and Vacuum Extruded Bentonite Clay Mat

2016 ◽  
Vol 138 (12) ◽  
Author(s):  
Eric Wooi Kee Loh ◽  
Devapriya Chitral Wijeyesekera ◽  
Mihaela Anca Ciupala
Keyword(s):  
Bentonite Clay ◽  
Moisture Diffusion ◽  
Critical Study ◽  
Thin Layer Drying ◽  
Drying Models ◽  
Tropical Climates ◽  
And Control ◽  
Moisture Desorption ◽  
Quality Of Fit

Moisture desorption observations from two bentonite clay mats subjected to ten environmental zones with individually different combinations of laboratory-controlled constant temperatures (between 20 °C and 40 °C) and relative humidity (between 15% and 70%) are presented. These laboratory observations are compared with predictions from mathematical models, such as thin-layer drying equations and kinetic drying models proposed by Page, Wang and Singh, and Henderson and Pabis. The quality of fit of these models is assessed using standard error (SE) of estimate, relative percent of error, and coefficient of correlation. The Page model was found to better predict the drying kinetics of the bentonite clay mats for the simulated tropical climates. Critical study on the drying constant and moisture diffusion coefficient helps to assess the efficacy of a polymer to retain moisture and control desorption through water molecule bonding. This is further substantiated with the Guggenheim–Anderson–De Boer (GAB) desorption isotherm model which is presented.

Design Optimization of RML Glove for Improved Grasp Performance

2018 ◽  
Author(s):  
Teja Vanteddu ◽  
Bijo Sebastian ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Design Optimization ◽  
Daily Living ◽  
Experimental Validation ◽  
Large Diameter ◽  
Future Research ◽  
Linkage Mechanism ◽  
Design Variables ◽  
Wide Range ◽  
Optimal Values ◽  
Optimal Set

This paper describes the design optimization of the RML Glove in order to improve its grasp performance. The existing design is limited to grasping objects of large diameter (> 110mm) due to its inability in attaining high bending angles. For an exoskeleton glove to be effective in its use as an assistive and rehabilitation device for Activities of Daily Living (ADL), it should be able to interact with objects over a wide range of sizes. Motivated by these limitations, the kinematics of the existing linkage mechanism was analyzed in detail and the design variables were identified. Two different cost functions were formulated and compared in their ability to yield optimal values for the design variables. The optimal set of design variables was chosen based on the grasp angles achieved and the resulting mechanism was simulated in CAD for feasibility testing. An exoskeleton mechanism corresponding to the index finger was manufactured with the chosen design variables and detailed experimental validation was performed to illustrate the improvement in grasp performance over the existing design. The paper ends with a summary of the experimental results and directions for future research.

scholarly journals Numerical model and experimental validation of the heat transfer in air cooled solar photovoltaic panel

2016 ◽  
Vol 20 (suppl. 4) ◽  
pp. 1071-1081 ◽  
Author(s):  
Senthil Ranganathan ◽  
Natarajan Elumalai ◽  
Puja Natarajan Priyadharshini
Keyword(s):  
Heat Transfer ◽  
Numerical Model ◽  
Experimental Validation ◽  
Solar Photovoltaic ◽  
Photovoltaic Panel

Multifidelity Recursive Cokriging for Dynamic Systems' Response Modification

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Luigi Bregant ◽  
Lucia Parussini ◽  
Valentino Pediroda
Keyword(s):  
Numerical Model ◽  
Numerical Simulations ◽  
Dynamic Systems ◽  
System Optimization ◽  
The Other ◽  
Experimental Measurements ◽  
Reciprocal Influence ◽  
Tests And Measurements ◽  
Invaluable Tool ◽  
Mixed Approach

In order to perform the accurate tuning of a machine and improve its performance to the requested tasks, the knowledge of the reciprocal influence among the system's parameters is of paramount importance to achieve the sought result with minimum effort and time. Numerical simulations are an invaluable tool to carry out the system optimization, but modeling limitations restrict the capabilities of this approach. On the other side, real tests and measurements are lengthy, expensive, and not always feasible. This is the reason why a mixed approach is presented in this work. The combination, through recursive cokriging, of low-fidelity, yet extensive, numerical model results, together with a limited number of highly accurate experimental measurements, allows to understand the dynamics of the machine in an extended and accurate way. The results of a controllable experiment are presented and the advantages and drawbacks of the proposed approach are also discussed.

scholarly journals The Quality of Accruals and Earnings: The Role of Accrual Estimation Errors

2002 ◽  
Vol 77 (s-1) ◽  
pp. 35-59 ◽  
Author(s):  
Patricia M. Dechow ◽  
Ilia D. Dichev
Keyword(s):  
Estimation Error ◽  
Cash Flows ◽  
Empirical Measure ◽  
Earnings Persistence ◽  
Working Capital ◽  
Estimation Errors ◽  
Accrual Quality ◽  
Flows Over Time

This paper suggests a new measure of one aspect of the quality of working capital accruals and earnings. One role of accruals is to shift or adjust the recognition of cash flows over time so that the adjusted numbers (earnings) better measure firm performance. However, accruals require assumptions and estimates of future cash flows. We argue that the quality of accruals and earnings is decreasing in the magnitude of estimation error in accruals. We derive an empirical measure of accrual quality as the residuals from firm-specific regressions of changes in working capital on past, present, and future operating cash flows. We document that observable firm characteristics can be used as instruments for accrual quality (e.g., volatility of accruals and volatility of earnings). Finally, we show that our measure of accrual quality is positively related to earnings persistence.

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