Evidence map›Paper›PMID 36365993›Full record

ArticleSensors (Basel, Switzerland)2022

Ultrasonic Guided Waves for Liquid Water Localization in Fuel Cells: An Ex Situ Proof of Principle.

Jakob Sablowski, Ziwen Zhao, Christian Kupsch

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jakob SablowskiMeasurement, Sensor and Embedded Systems Laboratory, Institute of Electrical Engineering, TU Bergakademie Freiberg, Winklerstrasse 5, 09599 Freiberg, Germany.ORCID 0000-0002-9530-9005
Ziwen ZhaoMeasurement, Sensor and Embedded Systems Laboratory, Institute of Electrical Engineering, TU Bergakademie Freiberg, Winklerstrasse 5, 09599 Freiberg, Germany.
Christian KupschMeasurement, Sensor and Embedded Systems Laboratory, Institute of Electrical Engineering, TU Bergakademie Freiberg, Winklerstrasse 5, 09599 Freiberg, Germany.ORCID 0000-0003-0995-3484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water management is a key issue in the design and operation of proton exchange membrane fuel cells (PEMFCs). For an efficient and stable operation, the accumulation of liquid water inside the flow channels has to be prevented. Existing measurement methods for localizing water are limited in terms of the integration and application of measurements in operating PEMFC stacks. In this study, we present a measurement method for the localization of liquid water based on ultrasonic guided waves. Using a sparse sensing array of four piezoelectric wafer active sensors (PWAS), the measurement requires only minor changes in the PEMFC cell design. The measurement method is demonstrated with ex situ measurements for water drop localization on a single bipolar plate. The wave propagation of the guided waves and their interaction with water drops on different positions of the bipolar plate are investigated. The complex geometry of the bipolar plate leads to complex guided wave responses. Thus, physical modeling of the wave propagation and tomographic methods are not suitable for the localization of the water drops. Using machine learning methods, it is demonstrated that the position of a water drop can be obtained from the guided wave responses despite the complex geometry of the bipolar plate. Our results show standard deviations of 4.2 mm and 3.3 mm in the

Indexed as

deposit localizationfuel cellssignal processingultrasonic guided waveswater management

Identifiers

PMID36365993
PMCPMC9656768

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.