arxiv: 2604.27432 · v1 · submitted 2026-04-30 · 💻 cs.CE

Recognition: unknown

Modeling of Wastewater Treatment Processes with HydroSludge

S. Iserte , P. Carratal\`a , R. Arnau , R. Mart\'inez-Cuenca , P. Barreda , L. Basiero , J. Climent , S. Chiva

Authors on Pith no claims yet

Pith reviewed 2026-05-07 10:33 UTC · model grok-4.3

classification 💻 cs.CE

keywords HydroSludgewastewater treatmentCFD modelingWRRFcomputational fluid dynamicssimulation toolsmeshingpreprocessing

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The pith

HydroSludge supplies tools that simplify CFD use for wastewater treatment modeling.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces HydroSludge as a framework that supplies tools to ease the use of computational fluid dynamics in wastewater treatment modeling. It targets the barriers of complexity and learning curves that have kept CFD from wider use by experts in the field. These tools handle data preprocessing, support meshing, and facilitate simulations for processes in water resource recovery facilities. If successful, this would allow more accurate evaluations of plant performance and help meet demands for efficient treatment amid water scarcity and tighter rules.

Core claim

HydroSludge offers a series of tools that simplify the implementation of processes and workflows in a WRRF. It leverages these to preprocess existing data, aid the meshing process, and perform CFD simulations. The framework's intuitive interface is positioned as an effective means to increase the efficiency of wastewater treatment by extending CFD usage among modeling experts.

What carries the argument

The HydroSludge framework and its integrated tools for simplifying CFD workflows in wastewater modeling.

If this is right

Experts gain the ability to use high spatial and temporal accuracy modeling without high complexity.
WRRF performance can be evaluated more effectively to ensure maximum efficiency.
Numerical techniques become applicable to biological reactors and secondary settling tanks more broadly.
Operators can respond better to pressures from climate change effects and restrictive regulations.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

The simplification could accelerate the adoption of advanced modeling in smaller or less-resourced facilities.
It opens possibilities for combining CFD with other data sources like real-time sensors.
Similar frameworks could be developed for other fluid-based environmental processes.
The approach might support faster iteration in plant design and upgrades.

Load-bearing premise

Simplifying the CFD implementation through tools and an intuitive interface maintains the accuracy and reliability of the simulation results.

What would settle it

Running the same wastewater treatment model in HydroSludge and in standard CFD software and verifying if the key performance metrics match within acceptable error margins.

Figures

Figures reproduced from arXiv: 2604.27432 by J. Climent, L. Basiero, P. Barreda, P. Carratal\`a, R. Arnau, R. Mart\'inez-Cuenca, S. Chiva, S. Iserte.

**Figure 1.** Figure 1: Coordinate system of the momentum source volumetric region. view at source ↗

**Figure 2.** Figure 2: Overview of third-party software integration in HydroSludge. view at source ↗

**Figure 3.** Figure 3: HydroSludge modules and operations. 16 view at source ↗

**Figure 4.** Figure 4: Scheme of the in/out flows in the structure of the SST under study. view at source ↗

**Figure 5.** Figure 5: Examples of the filtering stage of the SST design tool. view at source ↗

**Figure 6.** Figure 6: Checking stage of the SST design tool. All in all, the filters and the previous check can be used by the state point model and the ten layers model to test whether the activated sludge from the biological reactor settles at the SST. This tool is presented with three areas (see Figure 6b). The first area, found at the top, is a hydraulic diagram of the secondary treatment of a WRRF with a bioreactor and an … view at source ↗

**Figure 7.** Figure 7: Surfaces of the geometry under study view at source ↗

**Figure 8.** Figure 8: Sludge concentration inside the clarifier at the initial timesteps of view at source ↗

**Figure 9.** Figure 9: Sludge concentration inside the clarifier at 2020 seconds of the view at source ↗

**Figure 10.** Figure 10: Overviews of the Anoxic reactor under study. view at source ↗

**Figure 11.** Figure 11: Post-processing result examples. the timestep ≃ 11601.1 that corresponds to the second ≃ 193.4 of the transient simulation. Another example of the tools that HydroSludge provides is a probe-line which is deployed inside the domain to study the behavior of a given variable view at source ↗

**Figure 12.** Figure 12: Velocity profile results at three different locations A, B, and C view at source ↗

read the original abstract

The pressure for Water Resource Recovery Facilities (WRRF) operators to efficiently treat wastewater is greater than ever because of the water crisis, produced by the climate change effects and more restrictive regulations. Technicians and researchers need to evaluate WRRF performance to ensure maximum efficiency. For this purpose, numerical techniques, such as CFD, have been widely applied to the wastewater sector to model biological reactors and secondary settling tanks with high spatial and temporal accuracy. However, limitations such as complexity and learning curve, prevent extending CFD usage among wastewater modeling experts. This paper presents HydroSludge, a framework that provides a series of tools that simplify the implementation of the processes and workflows in a WRRF. This work leverages HydroSludge to preprocess existing data, aid the meshing process, and perform CFD simulations. Its intuitive interface proves itself as an effective tool to increase the efficiency of wastewater treatment

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

This is a software-tool description paper for HydroSludge that identifies a real usability gap in CFD for wastewater but supplies no data to back its efficiency claims.

read the letter

This paper is mainly a description of HydroSludge, a framework that bundles tools for preprocessing data, meshing, and running CFD simulations on water resource recovery facilities. It does not present new algorithms, derivations, or first-principles results, just a packaged workflow on top of existing CFD practice. The authors correctly note that CFD is already used for detailed modeling of reactors and settling tanks but that setup complexity limits wider adoption among operators and researchers. The framework aims to lower that barrier with an intuitive interface and example cases. That recognition of the practical problem is the paper's clearest strength. The central shortcoming is the absence of any supporting evidence for the claim that the tools actually increase efficiency. The abstract states that the interface proves itself effective, yet the manuscript offers no timing data, user studies, accuracy comparisons against baseline OpenFOAM or ANSYS runs, or error metrics. Without those, the effectiveness statement stays an assertion rather than a demonstrated result. There is no mathematical modeling or fitted predictions to scrutinize, and the work stays within standard CFD methods. This kind of paper is mainly useful to wastewater engineers who already want to apply CFD but find general tools cumbersome. Readers outside that narrow applied setting will not find new science or validated improvements. I would not bring it to a reading group or cite it. It does not look ready for peer review until the authors add controlled benchmarks showing real gains in time or usability without accuracy loss.

Referee Report

2 major / 0 minor

Summary. The manuscript introduces HydroSludge, a framework that supplies tools for preprocessing data, aiding meshing, and executing CFD simulations of Water Resource Recovery Facilities (WRRFs). It demonstrates application to example cases and asserts that the framework's intuitive interface reduces complexity and learning curve, thereby proving effective at increasing wastewater treatment efficiency.

Significance. A validated, user-friendly CFD framework for WRRF modeling could lower barriers to high-fidelity simulation among operators and researchers, supporting better reactor and settler design under tightening regulations. The manuscript supplies no quantitative evidence (timing data, error metrics, or baseline comparisons) that the tools achieve measurable efficiency gains while preserving CFD fidelity, so the claimed significance remains unestablished.

major comments (2)

[Abstract] Abstract: the claim that the interface 'proves itself as an effective tool to increase the efficiency of wastewater treatment' is unsupported by any controlled comparisons, user-study metrics, setup-time measurements, or accuracy benchmarks against standard OpenFOAM/ANSYS workflows. This assertion is load-bearing for the paper's central contribution yet reduces to an untested statement.
[Demonstration sections] Demonstration sections: the example cases illustrate tool usage for preprocessing, meshing, and simulation but contain no quantitative validation that discretization or boundary-condition fidelity is preserved relative to baseline CFD pipelines, leaving the 'without sacrificing accuracy' assumption untested.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback on our manuscript. We address each major comment below and indicate the changes we will make in the revised version.

read point-by-point responses

Referee: [Abstract] Abstract: the claim that the interface 'proves itself as an effective tool to increase the efficiency of wastewater treatment' is unsupported by any controlled comparisons, user-study metrics, setup-time measurements, or accuracy benchmarks against standard OpenFOAM/ANSYS workflows. This assertion is load-bearing for the paper's central contribution yet reduces to an untested statement.

Authors: We agree that the original abstract phrasing asserts an untested outcome. The manuscript presents the HydroSludge framework and illustrates its use through example workflows rather than through controlled benchmarks or user studies. In the revision we have replaced the claim with a description of the framework's design goals (simplifying preprocessing, meshing, and simulation steps for WRRF modeling) and have added a short discussion in the conclusions section that explicitly notes the absence of quantitative usability or efficiency metrics and identifies this as a topic for future work. revision: yes
Referee: [Demonstration sections] Demonstration sections: the example cases illustrate tool usage for preprocessing, meshing, and simulation but contain no quantitative validation that discretization or boundary-condition fidelity is preserved relative to baseline CFD pipelines, leaving the 'without sacrificing accuracy' assumption untested.

Authors: The demonstration sections are intended to show how the provided tools integrate with existing CFD pipelines. Because the tools operate by generating inputs for standard solvers without modifying discretization schemes or boundary-condition handling, fidelity is preserved at the level of the underlying solver. We nevertheless accept that direct quantitative evidence was not supplied. We will add a short validation subsection that reports mesh-quality metrics (e.g., orthogonality and skewness) and compares selected field variables (velocity and solids concentration) between the HydroSludge-generated setups and equivalent manually prepared cases using identical solver settings. revision: yes

Circularity Check

0 steps flagged

Tool-description paper with no mathematical derivations or load-bearing predictions

full rationale

The manuscript describes a software framework (HydroSludge) for preprocessing, meshing, and CFD simulation in WRRF modeling. It contains no equations, fitted parameters, uniqueness theorems, or predictive claims that could reduce to inputs by construction. The statement that the interface 'proves itself as an effective tool' is an unvalidated assertion rather than a derivation; it does not match any of the enumerated circularity patterns. No self-citations are load-bearing for a central result, and the work is self-contained as a descriptive tool paper.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review; no equations, parameters, or assumptions are stated.

pith-pipeline@v0.9.0 · 5477 in / 822 out tokens · 49655 ms · 2026-05-07T10:33:00.266155+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

2 extracted references · 1 canonical work pages

[1]

Brennan, D. (2001). The numerical simulation of two-phase flows in settling tanks.Thesis. Clarifier Design: WEF Manual of Practice No. FD-8. (2005). US: McGraw- Hill Professional. Retrieved fromhttps://mhebooklibrary.com/doi/ book/10.1036/0071464166 Climent, J., Basiero, L., Mart´ ınez-Cuenca, R., Berlanga, J. G., Juli´ an-L´ opez, B., & Chiva, S. (2018)....

work page doi:10.1036/0071464166 2001
[2]

(No. 3). Water Science Technology. Tak´ acs, I., Patry, G., & Nolasco, D. (1991). A dynamic model of the clarification-thickening process.Water Research,25(10), 1263-1271. Tchobanoglous, G., Burton, F. L., Stensel, H. D., & Metcalf & Eddy. (2003). Wastewater engineering: treatment and reuse. McGraw-Hill. Vesilind, P. A. (1968). Design of prototype thicken...

1991