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Record W4415502651 · doi:10.3390/pr13113410

Batch-Process Approach to Osmotic Power Generation: Modeling and Performance Assessment

2025· article· en· W4415502651 on OpenAlexafffund
Daniel Ruiz, Édgar Quiñones-Bolaños, Mostafa H. Sharqawy

Bibliographic record

VenueProcesses · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Canada
KeywordsReverse osmosisVolume (thermodynamics)TurbineOsmosisPower (physics)Pressure-retarded osmosisEnergy balanceFoulingFrancis turbineEnergy (signal processing)

Abstract

fetched live from OpenAlex

This paper presents a novel batch Forward Osmosis (FO) process for hydropower generation. It focuses on analyzing the parameters needed to make the proposed osmotic power plant implementable with currently available technology. Starting from the solution–diffusion model and using flow and mass balance equations, the equations that describe the behavior of the system over time are obtained. Membrane orientation, concentration polarization, reverse solute flux, and membrane fouling are not considered. The equations for calculating the operation time for the charging and discharging stages are obtained. Also, an equation for calculating the required membrane area to make the duration of the two stages the same is obtained. The results indicate that a volume of approximately 30.4 m3 discharging through a 0.84 inch diameter outflow jet towards a turbine could generate an energy of 25 kw·h. The discharging stage would take 12 h, and with a membrane with a water permeability constant Am=1.763·10−12 m/(s·Pa), the charging stage would require a membrane superficial area Arm=1·104 m2 to have the same duration. The proposed osmotic power plant, whose working principle is based on volume change over time, contrary to pressure retarded osmosis, whose working principle requires expending energy to extract energy from the salinity gradient, could deliver greater net produced energy with comparatively lower operational costs as it does not require high-pressure pumps or energy recovery devices as are required in pressure-retarded osmosis. The use of several tanks that charge and discharge alternatively can make the system generate energy as if it were a continuous process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.280
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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