scholarly journals Dual-Doppler Analysis in a Single Plane from an Airborne Platform

2006 ◽  
Vol 23 (1) ◽  
pp. 3-22 ◽  
Author(s):  
D. Leon ◽  
G. Vali ◽  
M. Lothon
Keyword(s):  
Random Noise ◽  
A Priori ◽  
Three Dimensional ◽  
Velocity Fields ◽  
Doppler Velocity ◽  
Single Plane ◽  
Observation Plane ◽  
Velocity Estimate ◽  
Velocity Variations ◽  
Doppler Analysis

Abstract A modified dual-Doppler analysis technique for use with airborne Doppler radars utilizing two fixed beams is presented. Although the data collected by such a system would ideally lie in the plane defined by the radar beam orientations and the aircraft velocity vector, variations in the aircraft attitude and drift angles lead to displacements between the radar observations and the idealized observation plane. These variations motivated the development of a formal framework in which an a priori velocity estimate is used in conjunction with the two Doppler velocity measurements to form a three-dimensional velocity estimate. Two velocity components, lying within or close to the observation plane, and therefore containing only a small contribution from the a priori velocity estimate, are then extracted from the three-dimensional velocity estimate. Advantages of using the three-dimensional framework include improved accuracy (when an a priori velocity estimate is available) and a framework for assessing the effects of cross-plane contamination on the retrieved velocity components. The velocity fields retrieved using the modified dual-Doppler analysis are affected by errors in the platform motion correction to the Doppler velocities, random noise in the mean Doppler velocity estimates, displacements between the radar beams (and between the radar beams and the idealized observation plane), and meteorological velocity variations about the a priori velocity estimate. Errors in the platform motion correction remain poorly characterized but are believed to be the largest source of error in many cases. However, these errors result primarily in biases (or low-frequency errors) in the retrieved velocity fields and therefore do not interfere with the ability to resolve actual velocity variations. Random noise in the mean Doppler velocity estimates increases dramatically with decreasing signal-to-noise ratio (SNR) (for SNR < 5 dB) and effectively limits the use of the single-plane dual-Doppler (SPDD) analysis to SNR > 0 dB. Displacements between the volumes sampled by the nadir and slanted beams can also be a significant source of error, especially at larger displacements from the aircraft. Errors resulting from meteorological velocity variations about the a priori velocity estimate tend to be small compared to the velocity variations of interest. The dual-Doppler analysis presented in this paper has been applied to retrieve two-dimensional velocity fields with a resolution of ∼50 m using Doppler velocities collected using dual-beam configurations of the Wyoming Cloud Radar. Results are in horizontal and vertical planes for marine stratocumulus, cumulus congestus, and for the clear-air boundary layer.

A MASS CONSERVATIVE STREAMLINE TRACKING METHOD FOR THREE-DIMENSIONAL CFD VELOCITY FIELDS

2007 ◽  
Vol 14 (1) ◽  
pp. 107-120 ◽  
Author(s):  
Roslyn Preetika Singh ◽  
Zhenquan Li
Keyword(s):  
Three Dimensional ◽  
Velocity Fields ◽  
Tracking Method

Applications of 3D printing in critical care medicine: A scoping review

2021 ◽  
pp. 0310057X2097665
Author(s):  
Natasha Abeysekera ◽  
Kirsty A Whitmore ◽  
Ashvini Abeysekera ◽  
George Pang ◽  
Kevin B Laupland
Keyword(s):  
Critical Care ◽  
Scoping Review ◽  
A Priori ◽  
Three Dimensional ◽  
Critical Care Medicine ◽  
Future Research ◽  
Care Practice ◽  
Three Dimensional Printing ◽  
Wide Range ◽  
Dimensional Printing

Although a wide range of medical applications for three-dimensional printing technology have been recognised, little has been described about its utility in critical care medicine. The aim of this review was to identify three-dimensional printing applications related to critical care practice. A scoping review of the literature was conducted via a systematic search of three databases. A priori specified themes included airway management, procedural support, and simulation and medical education. The search identified 1544 articles, of which 65 were included. Ranging across many applications, most were published since 2016 in non – critical care discipline-specific journals. Most studies related to the application of three-dimensional printed models of simulation and reported good fidelity; however, several studies reported that the models poorly represented human tissue characteristics. Randomised controlled trials found some models were equivalent to commercial airway-related skills trainers. Several studies relating to the use of three-dimensional printing model simulations for spinal and neuraxial procedures reported a high degree of realism, including ultrasonography applications three-dimensional printing technologies. This scoping review identified several novel applications for three-dimensional printing in critical care medicine. Three-dimensional printing technologies have been under-utilised in critical care and provide opportunities for future research.

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

2005 ◽  
Vol 22 (7) ◽  
pp. 909-929 ◽  
Author(s):  
Hirohiko Masunaga ◽  
Christian D. Kummerow
Keyword(s):  
A Priori ◽  
Three Dimensional ◽  
Tropical Rainfall Measuring Mission ◽  
Dimensional Structure ◽  
Retrieval Algorithm ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Global Precipitation

Abstract A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

scholarly journals Interseismic deformation of the Nankai subduction zone, southwest Japan, inferred from three-dimensional crustal velocity fields

2007 ◽  
Vol 59 (10) ◽  
pp. 1073-1082 ◽  
Author(s):  
Takao Tabei ◽  
Mari Adachi ◽  
Shin’ichi Miyazaki ◽  
Tsuyoshi Watanabe ◽  
Sayomasa Kato
Keyword(s):  
Subduction Zone ◽  
Three Dimensional ◽  
Velocity Fields ◽  
Southwest Japan ◽  
Crustal Velocity ◽  
Interseismic Deformation ◽  
Nankai Subduction Zone

scholarly journals Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110135
Author(s):  
Florian Jaton
Keyword(s):  
Machine Learning ◽  
William James ◽  
A Priori ◽  
Learning Algorithms ◽  
Three Dimensional ◽  
Ground Truth ◽  
Machine Learning Algorithms ◽  
Ground Truthing ◽  
Set Up ◽  
The Moment

This theoretical paper considers the morality of machine learning algorithms and systems in the light of the biases that ground their correctness. It begins by presenting biases not as a priori negative entities but as contingent external referents—often gathered in benchmarked repositories called ground-truth datasets—that define what needs to be learned and allow for performance measures. I then argue that ground-truth datasets and their concomitant practices—that fundamentally involve establishing biases to enable learning procedures—can be described by their respective morality, here defined as the more or less accounted experience of hesitation when faced with what pragmatist philosopher William James called “genuine options”—that is, choices to be made in the heat of the moment that engage different possible futures. I then stress three constitutive dimensions of this pragmatist morality, as far as ground-truthing practices are concerned: (I) the definition of the problem to be solved (problematization), (II) the identification of the data to be collected and set up (databasing), and (III) the qualification of the targets to be learned (labeling). I finally suggest that this three-dimensional conceptual space can be used to map machine learning algorithmic projects in terms of the morality of their respective and constitutive ground-truthing practices. Such techno-moral graphs may, in turn, serve as equipment for greater governance of machine learning algorithms and systems.

A Variational Method for Filling in Missing Data in Doppler Velocity Fields

2021 ◽  
Author(s):  
VINCENT T. WOOD ◽  
ROBERT P. DAVIES-JONES ◽  
ALAN SHAPIRO
Keyword(s):  
Missing Data ◽  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Original Data ◽  
Radar Data ◽  
Velocity Fields ◽  
Doppler Velocity ◽  
Doppler Radar Data ◽  
Ground Clutter ◽  
Tornado Warnings

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

Adaptive Geometry Representation of Turbine Vane Frames for Use in Optimization

2021 ◽  
Author(s):  
Sebastian F. Riebl ◽  
Christian Wakelam ◽  
Reinhard Niehuis
Keyword(s):  
Design Space ◽  
Cfd Simulation ◽  
A Priori ◽  
Three Dimensional ◽  
Optimization Method ◽  
Three Dimensions ◽  
Design Parameters ◽  
Adjustment Process ◽  
Turbine Vane ◽  
Integrated Concept

Abstract Turbine Vane Frames (TVF) are a way to realize more compact jet engine designs. Located between the high pressure turbine (HPT) and the low pressure turbine (LPT), they fulfill structural and aerodynamic tasks. When used as an integrated concept with splitters located between the structural load-bearing vanes, the TVF configuration contains more than one type of airfoil with sometimes pronouncedly different properties. This system of multidisciplinary demands and mixed blading poses an interesting opportunity for optimization. Within the scope of the present work, a full geometric parameterization of a TVF with splitters is presented. The parameterization is chosen as to minimize the number of parameters required to automatically and flexibly represent all blade types involved in a TVF row in all three dimensions. Typical blade design parameters are linked to the fourth order Bézier-curve controlled camber line-thickness parameterization. Based on conventional design rules, a procedure is presented, which sets the parameters within their permissible ranges according to the imposed constraints, using a proprietary developed code. The presented workflow relies on subsequent three dimensional geometry generation by transfer of the proposed parameter set to a commercially available CAD package. The interdependencies of parameters are discussed and their respective significance for the adjustment process is detailed. Furthermore, the capability of the chosen parameterization and adjustment process to rebuild an exemplary reference TVF geometry is demonstrated. The results are verified by comparing not only geometrical profile data, but also validated CFD simulation results between the rebuilt and original geometries. Measures taken to ensure the robustness of the method are highlighted and evaluated by exploring extremes in the permissible design space. Finally, the embedding of the proposed method within the framework of an automated, gradient free numerical optimization is discussed. Herein, implications of the proposed method on response surface modeling in combination with the optimization method are highlighted. The method promises to be an option for improvement of optimization efficiency in gradient free optimization of interdependent blade geometries, by a-priori excluding unsuitable blade combinations, yet keeping restrictions to the design space as limited as possible.

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