ArticleMaterials (Basel, Switzerland)2023
Derivation of Corrosion Depth Formula According to Corrosion Factors in District Heating Water through Regression Analysis.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed, 2 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
In order to predict the corrosion depth of a district heating pipeline, it is necessary to analyze various corrosion factors. In this study, the relationship between corrosion factors such as pH, dissolved oxygen, and operating time and corrosion depth was investigated using the Box-Behnken method within the response surface methodology. To accelerate the corrosion process, galvanostatic tests were conducted in synthetic district heating water. Subsequently, a multiple regression analysis was performed using the measured corrosion depth to derive a formula for predicting the corrosion depth as a function of the corrosion factors. As a result, the following regression formula was derived for predicting the corrosion depth: "corrosion depth (μm) = -133 + 17.1 pH + 0.00072 DO + 125.2 Time - 7.95 pH × Time + 0.002921 DO × Time".
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.