Mathematical modeling of the clarifier performance for water coagulation

This study explores the performance optimization of clarifiers by examining geometric parameters, flow velocity, and sludge characteristics. Mathematical models predict system behavior under various conditions, aiding in stable operation through optimized temperature, reagent dosing, and sludge management. An experimental approach identifies optimal reagent and temperature settings for water purification, ensuring consistent results. Key performance indicators-water turbidity, suspended solids concentration, and sludge settling velocity-are linked to operational variables. Maintaining stable hydraulics is critical to prevent sludge carryover. The proposed equations facilitate performance evaluation and guide further clarifier design and automation improvements.

Authors

Institutions

Publication Details

Journal
Scientific journal of the Ternopil national technical university
Published
2025-01-01
DOI
https://doi.org/10.33108/visnyk_tntu2025.01.028
Citations
1
Primary Topic
Statistical and Computational Modeling
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mathematical modeling of the clarifier performance for water coagulation

Petro Mykulyk, В. И. Невожай, Taras Dubyniak, Valery Bukhovets et al.
1 citations
Scientific journal of the Ternopil national technical university
Statistical and Computational Modeling
2.48
article

Mathematical modeling of the clarifier performance for water coagulation

Petro Mykulyk, В. И. Невожай, Taras Dubyniak, Valery Bukhovets, Taras Lepkyi
article en
1 citations

Abstract

This study explores the performance optimization of clarifiers by examining geometric parameters, flow velocity, and sludge characteristics. Mathematical models predict system behavior under various conditions, aiding in stable operation through optimized temperature, reagent dosing, and sludge management. An experimental approach identifies optimal reagent and temperature settings for water purification, ensuring consistent results. Key performance indicators-water turbidity, suspended solids concentration, and sludge settling velocity-are linked to operational variables. Maintaining stable hydraulics is critical to prevent sludge carryover. The proposed equations facilitate performance evaluation and guide further clarifier design and automation improvements.

Scientific journal of the Ternopil national technical universityVol. 117(1)
Ternopil Ivan Pului National Technical University (UA)
Openalex Percentile: Top 11%
Statistical and Computational Modeling
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.