A Method to Test Model Calibration Techniques: Preprint
A Method to Test Model Calibration Techniques: Preprint

Author:

Publisher:

Published: 2016

Total Pages: 0

ISBN-13:

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This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.

Discrete Element Method (DEM) Model Calibration Techniques for Additive Manufacturing
Discrete Element Method (DEM) Model Calibration Techniques for Additive Manufacturing

Author: Kristen Meihofer

Publisher:

Published: 2018

Total Pages:

ISBN-13:

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Powder bed fusion is a commonly used Additive Manufacturing technique. This technique uses a layer-by-layer approach to create the desired part in 3D printing, where the layers are created by spreading a thin layer of powder. The ability to simulate this process would give scientists the opportunity to visualize this process before printing the part, allowing them to best utilize the capabilities of powder bed fusion. Spreading of the powder to create the layer to be fused is the first step in the process, and the quality of the layer can impact the building of the part. The overall goal of this research is to investigate the use of simulation models for the spreading of the powder. However, before this simulation is possible, the required simulation inputs must be understood, and the model calibrated. Calibration of the simulation models is the focus of this research. The simulation inputs are based on the powder used in the process. Powder characterization tests are run to understand properties about the powder. One of the most common, due to its simplicity, is the angle of repose test. This paper develops an efficient calibration model for the simulation of the angle of repose test using the discrete element method. The discrete element method (DEM) is the basis to calculate how the particles react when they collide with other particles or equipment. A commercial DEM software, EDEM, is used to simulate the DEM for this experiment. This calibration technique efficiently calibrates the input variables associated with the angle of repose test. Future research can apply this technique to ultimately calibrate a simulation for powder spreading in the powder bed fusion process.

Fundamentals of Clinical Data Science
Fundamentals of Clinical Data Science

Author: Pieter Kubben

Publisher: Springer

Published: 2018-12-21

Total Pages: 219

ISBN-13: 3319997130

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This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Statistical Evaluation of Diagnostic Performance
Statistical Evaluation of Diagnostic Performance

Author: Kelly H. Zou

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 243

ISBN-13: 1439812233

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Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are releva

The Virtual Fields Method
The Virtual Fields Method

Author: Fabrice Pierron

Publisher: Springer Science & Business Media

Published: 2012-03-21

Total Pages: 531

ISBN-13: 1461418240

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The Virtual Fields Method: Extracting Constitutive Mechanical Parameters from Full-field Deformation Measurements is the first and only one on the Virtual Fields Method, a recent technique to identify materials mechanical properties from full-field measurements. It contains an extensive theoretical description of the method as well as numerous examples of application to a wide range of materials (composites, metals, welds, biomaterials etc.) and situations(static, vibration, high strain rate etc.). Finally, it contains a detailed training section with examples of progressive difficulty to lead the reader to program the VFM. This is accompanied with a set of commented Matlab programs as well as with a GUI Matlab based software for more general situations.

Multivariate Calibration
Multivariate Calibration

Author: Harald Martens

Publisher: John Wiley & Sons

Published: 1992-08-07

Total Pages: 444

ISBN-13: 9780471930471

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Multivariate Calibration Harald Martens, Chemist, Norwegian Food Research Institute, Aas, Norway and Norwegian Computing Center, Oslo, Norway Tormod Næs, Statistician, Norwegian Food Research Institute, Aas, Norway The aim of this inter-disciplinary book is to present an up-to-date view of multivariate calibration of analytical instruments, for use in research, development and routine laboratory and process operation. The book is intended to show practitioners in chemistry and technology how to extract the quantitative and understandable information embedded in non-selective, overwhelming and apparently useless measurements by multivariate data analysis. Multivariate calibration is the process of learning how to combine data from several channels, in order to overcome selectivity problems, gain new insight and allow automatic outlier detection. Multivariate calibration is the basis for the present success of high-speed Near-Infrared (NIR) diffuse spectroscopy of intact samples. But the technique is very general: it has shown similar advantages in, for instance, UV, Vis, and IR spectrophotometry, (transmittance, reflectance and fluorescence), for x-ray diffraction, NMR, MS, thermal analysis, chromatography (GC, HPLC) and for electrophoresis and image analysis (tomography, microscopy), as well as other techniques. The book is written at two levels: the main level is structured as a tutorial on the practical use of multivariate calibration techniques. It is intended for university courses and self-study for chemists and technologists, giving one complete and versatile approach, based mainly on data compression methodology in self-modelling PLS regression, with considerations of experimental design, data pre-processing and model validation. A second, more methodological, level is intended for statisticians and specialists in chemometrics. It compares several alternative calibration methods, validation approaches and ways to optimize the models. The book also outlines some cognitive changes needed in analytical chemistry, and suggests ways to overcome some communication problems between statistics and chemistry and technology.

Model Calibration as a Testing Strategy for Dynamic Hypotheses
Model Calibration as a Testing Strategy for Dynamic Hypotheses

Author: Rogelio Oliva

Publisher:

Published: 2000

Total Pages: 26

ISBN-13:

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Calibration estimating model parameters to obtain a match between observed and simulated structures and behaviors-examines whether a model simultaneously adheres to observable structure and behavior. In this paper, I posit that calibration is a stringent test of a hypothesis linking structure tobehavior, and propose a framework to use automated calibration for model testing. I tackle the issue at three levels: theoretical, methodological, and technical. First, I explore the nature of model testing and suggest that the modeling process be recast as an experimental approach to gain confidence in a dynamic hypothesis. At the methodological level, I proposeheuristics to guide the testing strategy and take advantage of the strengths ofautomated calibration. Finally, I present a set of techniques to support the hypothesis testing process. The paper concludes with an example and by summarizing the argument for the proposed approach.

Advances in Large Margin Classifiers
Advances in Large Margin Classifiers

Author: Alexander J. Smola

Publisher: MIT Press

Published: 2000

Total Pages: 436

ISBN-13: 9780262194488

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The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.

On-Wafer Calibration Techniques Enabling Accurate Characterization of High-Performance Silicon Devices at the mm-Wave Range and Beyond
On-Wafer Calibration Techniques Enabling Accurate Characterization of High-Performance Silicon Devices at the mm-Wave Range and Beyond

Author: Andrej Rumiantsev

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 279

ISBN-13: 1000792854

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The increasing demand for more content, services, and security drives the development of high-speed wireless technologies, optical communication, automotive radar, imaging and sensing systems and many other mm-wave and THz applications. S-parameter measurement at mm-wave and sub-mm wave frequencies plays a crucial role in the modern IC design debug. Most importantly, however, is the step of device characterization for development and optimization of device model parameters for new technologies. Accurate characterization of the intrinsic device in its entire operation frequency range becomes extremely important and this task is very challenging. This book presents solutions for accurate mm-wave characterization of advanced semiconductor devices. It guides through the process of development, implementation and verification of the in-situ calibration methods optimized for high-performance silicon technologies. Technical topics discussed in the book include: Specifics of S-parameter measurements of planar structures Complete mathematical solution for lumped-standard based calibration methods, including the transfer Thru-Match-Reflect (TMR) algorithms Design guideline and examples for the on-wafer calibration standards realized in both advanced SiGe BiCMOS and RF CMOS processes Methods for verification of electrical characteristics of calibration standards and accuracy of the in-situ calibration results Comparison of the new technique vs. conventional approaches: the probe-tip calibration and the pad parasitic de-embedding for various device types, geometries and model parameters New aspects of the on-wafer RF measurements at mmWave frequency range and calibration assurance.