52 research outputs found
Enforcing temporal consistency in physically constrained flow field reconstruction with FlowFit by use of virtual tracer particles
No full textAbstract Processing techniques for particle-based optical flow measurement data such as 3D particle tracking velocimetry (PTV) or the novel dense Lagrangian particle tracking method ‘Shake-the-Box’ (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier–Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. FlowFit’s core method is not altered in the current work, but rather its input in the form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem
Extremes of fractional noises: A model for the timings of arrhythmic heart beats in post-infarction patients
No full textWe have analyzed symbol sequences of heart beat annotations obtained from 24-h electrocardiogram recordings of 184 post-infarction patients (from the Cardiac Arrhythmia Suppression Trial database, CAST). In the symbol sequences, each heart beat was coded as an arrhythmic or as a normal beat. The symbol sequences were analyzed with a model-based approach which relies on two-parametric peaks over the threshold (POT) model, interpreting each premature ventricular contraction (PVC) as an extreme event. For the POT model, we explored (i) the Shannon entropy which was estimated in terms of the Lempel–Ziv complexity, (ii) the shape parameter of the Weibull distribution that best fits the PVC return times, and (iii) the strength of long-range correlations quantified by detrended fluctuation analysis (DFA) for the two-dimensional parameter space. We have found that in the frame of our model the Lempel–Ziv complexity is functionally related to the shape parameter of the Weibull distribution. Thus, two complementary measures (entropy and strength of long-range correlations) are sufficient to characterize realizations of the two-parametric model. For the CAST data, we have found evidence for an intermediate strength of long-range correlations in the PVC timings, which are correlated to the age of the patient: younger post-infarction patients have higher strength of long-range correlations than older patients. The normalized Shannon entropy has values in the range 0.5<hLZ<1.0 which indicates a high degree of randomness in the PVC timings. For the CAST and the model data, the ranges of both measures were found to be in good accordance. The correlation between the age and the persistence strength found for the CAST data could be explained as a change of model parameters
Über das Potential von lagrangem Transport in der Strömungsfeldrekonstruktion unter physikalischen Nebenbedingungen (On the Potential of Lagrangian Transport in Physically Constrained Flow Field Reconstructions)
No full textModerne Strömungsmessverfahren basieren auf Hochgeschwindigkeitskameraaufnahmen von in der Strömung mitbewegten Tracer Partikeln in ausgeleuchteten Ebenen oder Volumina. Die Bildverarbeitung sowie die zum Tracking eingesetzten Algorithmen spielen dabei eine Schlüsselrolle was die Qualität und Genauigkeit der erzeugten Daten betrifft. Die robuste Shake-The-Box Methode [Schanz et al., 2013] ermöglicht akkurates Partikeltracking auch bei hohen Partikeldichten, liefert jedoch räumlich versprenkelte Informationen. Aufwendige Interpolationsalgorithmen wurden entwickelt um unter Zuhilfenahme weiterer physikalischer Nebenbedingungen aus den Navier-Stokes Gleichungen zugleich Geschwindigkeits- und Beschleunigungsfelder als Lösung eines inversen Problems zu rekonstruieren. Damit ist es praktisch möglich, das klassische Nyquistlimit zu unterschreiten. Die volle zeitliche Entwicklung der Felder wurde bisher jedoch entweder nicht berücksichtigt [Gesemann et al., 2016] oder die zeitliche Kopplung durch aufwendige Zeitintegrationsverfahren resultierte in hohem Rechenaufwand [Schneiders and Scarano, 2018]. Diese Arbeit zeigt auf, dass die zeitliche Kopplung einzelner Zeitschritte durch virtuelle Lagrange Tracerpartikel die Rekonstruktionsfehler senken kann. Hierzu wurden künstliche Experimente auf Basis von DNS Rechnungen verwendet. Der Einfluss zusätzlicherFaktoren wie den Fehlerkorrelationen oder der Regularisierung des inversen Problems wird diskutiert.
Flow field measurements are nowadays performed with high-speed camera recordings of tracer particles in an illuminated fluid layer or volume. The following postprocessing is key to the quality of the resulting velocity and/or acceleration fields. Dense 3D particle tracking following the Shake-The-Box method [Schanz et al., 2013] yields accurate but scattered data. Sophisticated interpolation schemes were proposed that can make use of further physical constraints from the Navier-Stokesequations in order to simultaneously determine velocity and acceleration fields as solutions to an inverse problem. This allows to resolve structures beyond the classical Nyquist limit for each single field variable. So far, the full temporal domain has either not been considered yet [Gesemann et al., 2016] or the temporal coupling of several time instants via simulation methods resulted in high computational costs [Schneiders and Scarano, 2018]. This work shows that the introduction of memory to the reconstruction process (by temporal coupling) results in improved flow field reconstructions of artificial DNS experiments. For this purpose, additional artificial Lagrangian tracers (virtual particles) were advected between the fields, which is the most natural way to achieve temporal coupling in the framework of such algorithms. Several contributions like reconstruction error correlations and the flow field regularization within the inverse problem were revised to explain the improvements
DFT and TD-DFT studies to elucidate the configurational isomers of ferric aerobactin, ferric petrobactin, and their ferric photoproducts
Get PDFAuthor contributions: Sasha Gardner carried out all calculations and composed the original draft of the manuscript including tables and figures. Carl J. Carrano suggested the project, provided the original experimental data, and provided early guidance on the interpretation of the experimental work. Yuezhi Mao and Andrew Cooksy provided guidance and resources for the calculations. Frithjof Küpper provided guidance on the context of the work and on the original experimental work and drafted relevant sections of the manuscript. All authors save Carrano edited the manuscript.Peer reviewe
Uncertainty Reduction of FlowFit Flow Field Estimation by Use of Virtual Particle
Get PDFFrom experiments, data is available in the form of particle pictures from which particle tracks can be inferred by tracking techniques such as tomographic PTV or Shake-The-Box. But complete knowledge of the velocity field is sought on the basis of the scattered velocity and acceleration data. For this purpose different spatial interpolation algorithms were proposed, such asFlowFit and VIC+, which take Lagrangian particle track data (position, velocity and acceleration) as input and exploit known physical properties such as continuity and the Navier-Stokes equations for incompressible and uniform-density flows to reconstruct accurate and high resolution velocity, acceleration and pressure fields. The mentioned algorithms reach higher spatial resolutions beyond Nyquist than interpolation schemes that make use of the constraint of solenoidality only, due to the increased amount of data.
We aim to develope a method in which virtual particles from previous reconstructions are advected into the following interpolation timestep with an individual weight dependend on (i) the Lagrangian correlation functions known from the track data and (ii) the local velocity gradient tensor as estimated.
Usually, the time steps are about the size of the Kolmogorov time scale so the Lagrangian velocities and accelerations at two subsequent time instants are still significantly correlated. Therefore, a straightforward approach to combine the information of multiple reconstructions is to involve additional virtual particles into the reconstruction process that are advected with the estimated velocity and acceleration in order to act as information carrier between the reconstructed fields, thus enforcing consistency in time
Enforcing Temporal Consistency in Physically Constrained Flow Field Reconstruction with FlowFit by Use of Virtual Tracer Particles
Get PDFProcessing techniques for particle based optical flow measurement data such as 3D Particle Tracking Velocimetry (PTV) or the novel dense Lagrangian Particle Tracking method Shake-The-Box (STB) can provide time-series of velocity and acceleration information scattered in space. The following post-processing is key to the quality of space-filling velocity and pressure field reconstruction from the scattered particle data. In this work we describe a straight-forward extension of the recently developed data assimilation scheme FlowFit, which applies physical constraints from the Navier-Stokes equations in order to simultaneously determine velocity and pressure fields as solutions to an inverse problem. We propose the use of additional artificial Lagrangian tracers (virtual particles), which are advected between the flow fields at single time instants to achieve meaningful temporal coupling. This is the most natural way of a temporal constraint in the Lagrangian data framework. Not FlowFit's core method is altered in the current work, but its input in form of Lagrangian tracks. This work shows that the introduction of such particle memory to the reconstruction process significantly improves the resulting flow fields. The method is validated in virtual experiments with two independent DNS test cases. Several contributions are revised to explain the improvements, including correlations of velocity and acceleration errors in the reconstructions and the flow field regularization within the inverse problem
A routine design strategy to change organisational processes in the front end of radical innovation
No full textFor technology firms like Barco, radical innovation a way to escape intense competition, but also crucial for long-term survival as they provide the foundations on which future generations of products are created (McDermott & O’Connor, 2002; Sandberg & Aarikk-Stenroos, 2014). However, a required mature radical innovation capability in the front end of the process was lacking (O’Connor & DeMartino, 2006). Therefore, they have to change their internal processes and organisational routines that are regarded as the building blocks for this organisational capability (Junginger, 2008; Salvato & Rerup, 2011). Understanding organisational change is one of the great endeavours of many researchers and management consultants in the field of organisation design. A way to understand organisational change is by looking at organisational routines (Becker, 2005). Organisational routines are important to organisational change, but easier to study (Feldman & Pentland, 2003). However, an understanding how routines are designed or come to life is still a key question in the field of organisation design (Howard-Grenvile, 2005; Wegener et al., 2019). The approach of many managers and consultants of carefully designing PowerPoints and checklists while hoping for routines to change is a mistake (Pentland & Feldman, 2008). This leads to the following research question: How to design an organisational routine that develops a radical innovation capability within a technology firm?To answer this question and to provide organisation designers or organisational researchers empirical insights on how to design a routine in a performative way I developed and executed a routine design strategy. This strategy is based on existing routine design literature (Pentland & Feldman, 2008) and the double diamond approach (Design Council, 2005).This study shows that using a routine design strategy consisting of three interdependent phases are critical to routine design. First, emphasize with routine actors, conduct activities to discover and define the challenges and needs the actors face in their patterns of action. Second, lock in desired performance, prototype in collaboration with the routine actors the desired performances and lock them in a physical artefact. Third, build the ostensive, perform the designed performances in design experiments within a reflective and experimental space to practice the routine in safe but realistic boundaries.Strategic Product Desig
Robert Thayer Wilce, pioneer of Arctic marine botany (9 December 1924 – 26 February 2022)
Get PDFAcknowledgements: Special thanks are due to Bob Wilce, Donna Parker and Alexander Wilce for their help with the interviews for this article, as well as to Ambassador Mark G. and Patricia Hambley and Leslie and Lyman Wood (Springfield, Massachusetts) for their hospitality and logistical support which made the author’s visits possible (the last one during the difficult circumstances of the COVID19 pandemic). Also, the author would like to thank Michael Wynne (University of Michigan, Ann Arbor), for a critical read and fact-checking details of this article.Peer reviewe
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