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1. Simultaneous Bayesian Calibration and Engineering Design With an Application to a Vibration Isolation System

   https://doi.org/10.1115/1.4050075  

   Ehrett, Carl; Brown, D. Andrew; Kitchens, Christopher; Xu, Xinyue; Platz, Roland; Atamturktur, Sez (March 2021, Journal of Verification, Validation and Uncertainty Quantification)

   null (Ed.)

   Abstract Calibration of computer models and the use of those design models are two activities traditionally carried out separately. This paper generalizes existing Bayesian inverse analysis approaches for computer model calibration to present a methodology combining calibration and design in a unified Bayesian framework. This provides a computationally efficient means to undertake both tasks while quantifying all relevant sources of uncertainty. Specifically, compared with the traditional approach of design using parameter estimates from previously completed model calibration, this generalized framework inherently includes uncertainty from the calibration process in the design procedure. We demonstrate our approach to the design of a vibration isolation system. We also demonstrate how, when adaptive sampling of the phenomenon of interest is possible, the proposed framework may select new sampling locations using both available real observations and the computer model. This is especially useful when a misspecified model fails to reflect that the calibration parameter is functionally dependent upon the design inputs to be optimized. 

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2. Comparative analysis of circular and linear fringe projection profilometry: from calibration to 3D reconstruction

   https://doi.org/10.1364/OPTCON.520433  

   Li, Jiaqiong; Li, Beiwen (March 2024, Optics Continuum)

   This study compares the accuracy of circular and linear fringe projection profilometry in the aspects of system calibration and 3D reconstruction. We introduce, what we believe to be, a novel calibration method and 3D reconstruction technique using circular and radial fringe patterns. Our approach is compared with the traditional linear phase-shifting method through several 2 × 2 experimental setups. Results indicate that our 3D reconstruction method surpasses the linear phase-shifting approach in performance, although calibration efficiency does not present a superior performance. Further analysis reveals that sensitivity and estimated phase error contribute to the relative underperformance in calibration. This paper offers insights into the potentials and limitations of circular fringe projection profilometry. 

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3. Self-Supervised Camera Self-Calibration from Video

   https://doi.org/10.1109/ICRA46639.2022.9811784  

   Fang, Jiading; Vasiljevic, Igor; Guizilini, Vitor; Ambrus, Rares; Shakhnarovich, Greg; Gaidon, Adrien; Walter, Matthew R (May 2022, IEEE)

   Camera calibration is integral to robotics and computer vision algorithms that seek to infer geometric properties of the scene from visual input streams. In practice, calibration is a laborious procedure requiring specialized data collection and careful tuning. This process must be repeated whenever the parameters of the camera change, which can be a frequent occurrence for mobile robots and autonomous vehicles. In contrast, self-supervised depth and ego-motion estimation approaches can bypass explicit calibration by in-ferring per-frame projection models that optimize a view-synthesis objective. In this paper, we extend this approach to explicitly calibrate a wide range of cameras from raw videos in the wild. We propose a learning algorithm to regress per-sequence calibration parameters using an efficient family of general camera models. Our procedure achieves self-calibration results with sub-pixel reprojection error, outperforming other learning-based methods. We validate our approach on a wide variety of camera geometries, including perspective, fisheye, and catadioptric. Finally, we show that our approach leads to improvements in the downstream task of depth estimation, achieving state-of-the-art results on the EuRoC dataset with greater computational efficiency than contemporary methods. 

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4. Cone Penetration Testing to Constrain the Calibration Process of a Sand Plasticity Model for Nonlinear Deformation Analysis

   https://doi.org/10.1201/9781003308829-43  

   A. Chiaradonna; T.J. Carey; K. Ziotopoulou; J.T. DeJong (April 2022, Cone Penetration Testing 2022)

   A reliable prediction of liquefaction-induced damage typically requires nonlinear deformation analyses with an advanced constitutive soil model calibrated to the site conditions. The calibration of constitutive models can be performed by relying primarily on a combination of commonly available properties and empirical or semi-empirical relationships, on laboratory tests on site-specific soils, on in-situ penetration tests, or a combination thereof. Chiaradonna et al. (2022) described a laboratory-based calibration approach of the PM4Sand constitutive model and evaluated the prediction accuracy against the response of a centrifuge experiment of a submerged slope. This paper addresses an alternate calibration approach in which the PM4Sand model is calibrated using centrifuge in-situ CPT data. The model performance for the resulting calibration is evaluated against the centrifuge experimental data and prior simulations from Chiaradonna et al. (2022). In this case, the CPT-based calibration resulted in more accurate estimations of the dynamic response and permanent displacements. 

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5. The impact of tandem redundant/sky-based calibration in MWA Phase II data analysis

   https://doi.org/10.1017/pasa.2020.37  

   Zhang, Zheng; Pober, Jonathan C.; Li, Wenyang; Hazelton, Bryna J.; Morales, Miguel F.; Trott, Cathryn M.; Jordan, Christopher H.; Joseph, Ronniy C.; Beardsley, Adam; Barry, Nichole; et al (January 2020, Publications of the Astronomical Society of Australia)

   null (Ed.)

   Abstract Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array’s (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: the improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error. 

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