Search Results (1,016)

Coal-bearing tight gas and deep coalbed methane (CBM) widely co-occur in China, and integrated commingled production outperforms separate development. Conventional separated simulation fails to capture coupled reservoir–wellbore gas–water flow. This study develops an integrated geomechanical coupled numerical model with multi-scale fractures and multi-phase wellbore flow: tight gas reservoirs use a stress-sensitive single-porosity model, deep CBM adopts a dual-porosity model for matrix desorption, and EDFM characterizes non-Darcy flow in hydraulic fractures. The Gray gas column and liquid column methods calculate layered bottomhole pressure according to reservoir vertical distribution, and matrix bordering solves the whole coupled system. Validated by field data of Well C-1 in Shanxi, the model yields average relative errors of 8.76% for daily gas output and 2.92% for daily water output. Sensitivity analysis on Well C-2 indicates vertical reservoir stacking controls interlayer pressure difference, and commingled gas curves show dual peaks with shifting dominant gas sources over production stages. A 3.9% rise in deep coalbed methane gas content significantly boosts mid-term peak production and cumulative gas output, making reservoir gas content the dominant geological factor governing commingled production performance. A 120.0% increase in tight gas saturation only delivers a slight uplift in cumulative production under low-porosity conditions. Elevated reservoir stress sensitivity triggers a cumulative gas production reduction of over 50%. Cumulative gas output varies proportionally with hydraulic fracture length, while fracture network width brings mismatched production improvement due to pressure drawdown funnel effects. Therefore, hydraulic fracturing operations should prioritize extending artificial fractures to expand the drainage area of commingled wells. Schemes with constant bottomhole flowing pressure and constant gas rate exert marginal influences on ultimate cumulative production and can be flexibly switched on site. To stabilize daily gas deliverability throughout the early, middle and late production stages, a bottomhole pressure drawdown rate of 0.05 MPa/d or a fixed daily gas rate of 4000 m³/d is recommended. This work provides theoretical support for optimizing commingled development of superimposed tight gas and deep CBM reservoirs. Full article

Connections between earth–rockfill and concrete dams are critical components of hybrid-dam seepage-control systems because material-stiffness contrasts and complex foundation conditions can create localized preferential seepage paths. Using HS Reservoir as a case study, this predictive design-stage assessment employed a full-domain three-dimensional model of the dam–foundation–abutment system and a local three-dimensional model of the cutoff-spur-wall connection. The seepage field, hydraulic gradients, and zonal seepage discharges were evaluated under the normal pool, design flood, and check flood levels, together with the responses of the connection interface and right-abutment grout curtain. Across the three baseline scenarios, the impervious core accounted for 82.2–83.6% of the total head difference at the maximum riverbed section, and the reported control-location gradients remained below the corresponding design values. At the check flood level, the modeled 178 and 179 m head contours passed above the local curtain crest at elevation 177.5 m, identifying an over-curtain seepage pathway. From the design flood level to the check flood level, right-abutment discharge increased from 259.86 to 544.49 m³/d (109.5%), while total discharge increased by 28.6%. Flow in the connection zone diverted around and beneath the cutoff spur wall, and the connection-surface gradients increased with reservoir level. These model predictions characterize the three-dimensional seepage response of the connection zone and right-abutment seepage-control system and can inform curtain-crest review, construction quality control, and post-impoundment monitoring. Full article

Estimating transmissivity and hydraulic conductivity is crucial for groundwater resource assessment, flow modeling, pollution remediation, and sustainability studies. In the volcanic highlands of Ethiopia, millions rely on hand-dug wells and springs for drinking and irrigation, yet the hydraulic properties of these shallow aquifers remain largely uncharacterized. This study provides the first comprehensive estimation of transmissivity and hydraulic conductivity for the shallow groundwater aquifers in the Lake Tana Basin through integrated analyses of pumping and slug tests. The effective dataset comprised 31 tests, unevenly distributed among four aquifer types: eight in Quaternary basalt, 13 in weathered basalt regolith, seven in pyroclastic deposits, and three in alluvio-lacustrine sediments. Time-series groundwater level data were additionally used to characterize seasonal recharge responses and recession behaviors. Quaternary basalt aquifers showed high transmissivity values of 117–1064 m²/d, with a geometric mean of 235 m²/d, reflecting the influence of open and hydraulically connected fractures. Weathered basalt regolith aquifers had transmissivity values of 0.27–71 m²/d, with a geometric mean of 3.09 m²/d, whereas pyroclastic aquifers ranged from 0.17 to 11 m²/d, with a geometric mean of 0.96 m²/d. The alluvio-lacustrine aquifers ranged from 1.68 to 173 m/d, with a geometric mean of 8.56 m²/d; however, this estimate should be interpreted cautiously because it is based on only three tests. This study reveals strong heterogeneity within and across aquifers. Pumping tests were generally more applicable to the relatively transmissive Quaternary basalt aquifers, whereas slug tests provided a practical approach for characterizing shallow weathered regolith, pyroclastic, and alluvio-lacustrine aquifers. Seasonal groundwater level patterns varied with geology and topographic position: aquifers on slopes and plateaus generally showed rapid recharge and recession responses, whereas those at foothills and floodplains exhibited more sustained groundwater levels, probably because of lateral inflow and interactions with river water. The findings provide preliminary hydraulic-property ranges for groundwater assessment and indicate that fractured Quaternary basalt aquifers may represent promising targets for water-supply development. Full article

The creation of innovative learning environments in courses to provide sustained talent support has long remained a central research concern for high-quality social development. Neglected foundational skills in professional course clusters are often a hidden barrier to higher education for sustainable development (HESD). To close five persistent foundational skill gaps across improper citation (J1), ineffective figure use (J2), poor analysis (J3), irresponsible AI use (J4), and comprehensive application (J5) within the hydraulic engineering course cluster, a four-stage deliberate practice module (5Di-40Pr-5Tr-3Cm) has been embedded into a two-week hydraulic model experiment course, and its learning outcomes are systematically evaluated. A systematic analysis of its achievement levels across neglected foundational skill indicators of J1~J5 at each stage was conducted, stratified by the overall cohort and subgroups (P: objective demand, T: behavior type, G: optimization methods). The key findings include: ① deliberate practice demonstrates better teaching outcomes than lecture-based instruction, which can be evidenced in 2026, when J5’s achievement levels at the 3Cm stage yielded a moderate effect size relative to the 2025 lecture-based condition (d = 0.42); compared with the 2024 no-intervention baseline, the cumulative effect is a obvious increasing trend (d = 1.43); ② In far-transfer subgroup diagnosis, P2 (medium objective demand) shows a rank-order reversal, low at 40Pr but higher at 3Cm, and is identified as the “partial understanding” group and providing a diagnostic anchor for tiered intervention; ③ In near-transfer pathway diagnosis, J5’s low performance in 5Tr (65.35%, below overall mean of 83.09%; CV = 7%) stems from two distinct pathways: a “knowledge-deficit pathway” (max-decay subgroups) and a “processing-load pathway” (subgroups where J1, J2 do not exhibit max decay). In addition, stage-specific thresholds (40Pr: 90%, range 60~99%; 5Tr and 3Cm: 83% ± 3%, range of for 40Pr, mean = 90%, recommended range = 60~99%; for 5Tr, mean = 83% ± 3%, range = 65~96% and 75~90%) provide quantitative benchmarks for targeted intervention. These cumulative findings are intended to advance the evaluation paradigm of engineering practice courses from “total score attainment” toward “structural diagnosis” and align with the competency-oriented philosophy of higher education for sustainable development (HESD). Full article

Coastal defenses under tsunami-like long waves are judged not only by wave attenuation but by their own stability and the hazard left landward, so a porous structure is assessed through several responses at once. OpenFOAM (porousWaveFoam) and FLOW-3D HYDRO are the two models most widely used for such problems, representing the open-source and the commercial approach, and each has an extensive record for solitary waves and for porous structures separately. Which to adopt for a given response is not established, since the two have not been compared where both occur together. Five hydraulic benchmarks were, therefore, reproduced with both, taken as configured in practice, since the differing elements cannot be exchanged by the user. Agreement was decomposed into error components and into the scalars that enter a design check, and each difference was weighed against a combined uncertainty. Neither model is superior across the responses. Across 57 signals, the more accurate one changes with the metric in 81% of cases, and six of thirteen governing comparisons exceed the uncertainty. Some of the largest errors are shared, so changing the model does not remove them, and the cost ordering reverses with the problem size. Model selection should, therefore, follow the target design response, together with a statement of whether the difference exceeds the uncertainty. These findings hold within the configurations tested; extension to random waves remains for future work. Full article

Vulnerable coastal urban margins face overlapping pressures from erosion, climate change, and plastic-waste accumulation. This study presents a screening-level numerical assessment of a hollow modular unit made of a recycled polyethylene terephthalate (PET)–concrete composite, proposed for coastal slope protection and stabilisation in Chucuito, Callao, Peru. A limit-equilibrium baseline indicates that the unprotected slope is marginal to unstable under the site’s seismic demand, motivating the evaluation of a surface-protection concept through a parallel, one-way finite element analysis–computational fluid dynamics (FEA–CFD) framework applied at three slope angles (60°, 53°, 45°). The FEA structural-response screening indicates consistent trends across configurations under an equivalent impact load and the adopted basal restraint. For the hydraulic comparison, inlet velocities of 3, 5 and 7 m/s were anchored to the site-specific Delft3D inundation modelling (site maximum 5 m/s), with a conservative 10 m/s upper bound; relative to a rip-rap reference, the hollow configuration suggests midpoint run-up velocity reductions of approximately 52% at θ = 53° under the conservative scenario and ≈57% at 3 and 5 m/s, falling to ≈25% at 7 m/s with overlapping ranges and the simulated free surface exceeding the crest. The CFD free-surface elevations show order-of-magnitude consistency with an indicative EurOtop-based run-up benchmark used as a consistency check rather than as hydraulic validation. Independent of this hydraulic comparison, the hollow geometry saves ≈ 62% of the material volume relative to an equivalent solid concrete block, valorises ≈ 793 post-consumer PET bottles per unit at a 10% dosage, and suggests a 42–58% embodied-CO₂ reduction relative to the same solid-concrete reference, driven mainly by the hollow geometry rather than by the PET substitution itself. The results are internally consistent but not experimentally validated and are intended as a comparative baseline to guide subsequent experimental and field studies, in line with Sustainable Development Goals (SDG) 11, 12 and 13. Full article

Pressure losses in heating, ventilation, and air-conditioning (HVAC) duct elbows significantly increase fan power requirements and reduce overall system efficiency. This study presents a comprehensive computational fluid dynamics (CFD) investigation aimed at identifying effective strategies for reducing pressure losses in 90° HVAC duct elbows. The numerical methodology was first validated against published experimental measurements, demonstrating excellent agreement and providing confidence in the predictive capability of the CFD model. The validated model was then employed to evaluate the influence of duct geometry, inlet velocity, guide vane configuration, inter-vane spacing, perforated guide vanes, and duct material roughness on aerodynamic performance using the SST k–ω turbulence model. The results show that round elbows reduce pressure losses by approximately 50% compared with hydraulically equivalent rectangular elbows, highlighting the strong influence of duct geometry on flow separation. Among the flow-control strategies investigated, curved guide vanes produced the greatest improvement, with an optimized three-vane arrangement and a non-dimensional spacing of $\mathrm{s}/{\mathrm{D}}_{\mathrm{h}}\approx 0.15$ (corresponding to 150 mm for the specific geometry tested) reducing pressure losses by approximately 31% relative to the baseline elbow without guide vanes. In contrast, the investigated perforated guide vane provided only marginal improvement, indicating that its geometry requires further optimization to minimize blockage and mixing losses. The material roughness study showed that smooth, rigid duct materials produced only minor differences in pressure loss, whereas flexible ducts generated noticeably higher losses because of their increased surface roughness. These findings demonstrate that optimizing elbow geometry and guide vane design is considerably more effective than modifying duct material or using the investigated perforated vane configuration. The study provides practical design recommendations for improving the aerodynamic performance and energy efficiency of HVAC duct systems. Full article

Vegetation distribution is important for regulating overland-flow hydraulics and reducing hydraulic erosion potential on slopes. However, quantitative procedures for determining the maximum admissible spacing of multi-row vegetation under specified soil and design rainfall conditions remain limited. This study combined fixed-bed flume experiments with a theoretical hydraulic model to determine the lateral and downslope vegetation spacings required to maintain the predicted overland-flow velocity below the critical velocity for soil-particle initiation. A total of 120 runoff tests were conducted at a slope gradient of 15° under eight flow discharges (0.3–1.0 L/s) and three vegetation configurations: single-row vegetation with varying lateral spacing b, multi-row vegetation with varying b at d = 0.030 m, and multi-row vegetation with varying downslope spacing d at b = 0.010 m. Flow depth and discharge were measured, and the cross-sectional mean velocity was calculated to evaluate the Reynolds number Re, Froude number Fr, and local resistance coefficient ξ. The measured Re and Fr ranged from 475 to 1770 and from 0.83 to 2.06, respectively, indicating laminar-to-transitional regimes based on Re and predominantly supercritical flow states based on Fr, with limited subcritical and critical cases. Increasing b, d, or Q generally reduced ξ, whereas multi-row vegetation produced greater flow resistance than single-row vegetation. At each Q level, the ξ–b and ξ–d relationships followed power functions with R² ≥ 0.73. An improved local resistance formulation incorporating b, d, Re, and Fr was developed and evaluated using 129 measured data points, yielding R² values of 0.77–0.90. The proposed model was further combined with SCS-CN runoff estimates and a critical initiation velocity criterion for five soil types characterized by mean particle diameter and particle density and five 1-h design rainfall depths of 25–125 mm. Model-derived vegetation-spacing estimates were obtained for 18 of the 25 soil–rainfall scenarios, and denser vegetation distributions were generally required as the design rainfall depth increased. These results provide experimentally informed, model-based guidance for estimating multi-row vegetation spacing under specified soil and rainfall conditions. The proposed relationships and spacing estimates are condition-specific to the fixed-bed experiments with artificial emergent vegetation at a slope gradient of 15° and to the investigated hydraulic and geometric ranges. They should not be interpreted as universal design criteria or direct predictions of field soil erosion; application beyond these conditions requires further calibration and validation. Full article

The lack of freshwater in the world requires a paradigm shift from linear water consumption to resilient and low-energy desalination technologies. Although reverse osmosis (RO) is the standard in the industry, its usefulness is essentially constrained by concentration polarization (CP) and non-useful hydraulic pressure losses. This paper applies a high-fidelity computational model in ANSYS Fluent 2022 R1 to conduct a comparative parametric evaluation of hexagonal and sinusoidal feed-spacer geometries relative to a baseline grid configuration. The solute concentration gradients at the fluid–membrane interface were solved using a 3D species transport model, which was optimized using one-micron near-wall inflation layers. The hexagonal configuration produced the lowest maximum membrane-surface salt mass fraction, decreasing it from 0.1127 kg/kg for the baseline grid to 0.0429 kg/kg, corresponding to a 61.9% reduction. Although the hexagonal design required an inlet pressure of 205.7 Pa, it produced a more favorable normalized mass-transfer–friction trade-off than the sinusoidal configuration (447.8 Pa), with a System Performance Index (η) of 2.53. These results demonstrate comparative micro-scale improvements in concentration polarization control and hydraulic performance under the simulated conditions. Experimental testing and system-level modeling are required before conclusions can be drawn regarding full-module energy consumption, photovoltaic integration, long-term fouling behavior, or economic feasibility. This study is consistent with the emerging Concepts and design for sustainability, whereby a circular and energy-efficient water economy is facilitated through an innovative mechanical design. Full article

At Yuehai Lake, China, managed Yellow River diversion maintains open water while imposing a persistent hydraulic boundary on the shallow aquifer. We combined water balance, zonal Darcy estimation, a calibrated regulated-stage groundwater model, particle tracking, major ions, and stable isotopes. Yellow River diversion supplied 93.7% of quantified external inflows. Zonal Darcy and model leakage were 2.39 and 2.47 × 10⁶ m³ a⁻¹. Across the monitored stage range (1105.96–1106.42 m), modeled leakage was 2.41–2.53 × 10⁶ m³ a⁻¹; alternative upper-aquifer structures produced 1.91–3.02 × 10⁶ m³ a⁻¹ without reversing exchange or eliminating the mound. Particles from 441 lakebed cells moved a median 24.5 m over 1065 d, indicating slow near-shore advection. Selected-screen isotopes were consistent with evaporatively enriched lake-water influence, whereas major ions showed a distinct west–east shift from Ca–Mg–HCO₃ toward Na–SO₄ and Na–Cl facies. Yuehai Lake therefore functions as a regulated losing lake. Its salinity pattern likely reflects lake leakage, agricultural return flow, soil-salt mobilization, background saline groundwater, and restricted drainage. Management should integrate lake-stage, groundwater-flow, and salinity monitoring. Full article

Accurate binarization of phase-detection probe signals (gas vs. liquid) is necessary for the estimation of local void fraction, interfacial velocity, and bubble statistics in gas–liquid flows, particularly in nuclear thermal–hydraulic experiments. Classical threshold-based methods—single or double level—perform well on clean laboratory signals but degrade under realistic industrial conditions where noise, baseline drift, and clustered (slug-like) events challenge fixed rules. This work investigates whether deep learning (DL) models trained exclusively on synthetic data can deliver robust, generalizable binarization on real probe measurements. We (i) build a parametric generator of realistic time series from bubbly pulse templates, extended to clusters/slug patterns and perturbed with controlled noise, drift, and oscillatory baselines; (ii) train four lightweight DL architectures—one-dimensional U-Net (UNET-1D), Temporal Convolutional Network (TCN), a minimal one-dimensional Convolutional Neural Network (CNN-1D), and a Bidirectional Long-Short Memory network (BiLSTM)—only on synthetic signals; and (iii) evaluate them against classical threshold methods using event-level and sample-level metrics. On synthetic signal evaluation, UNET-1D and TCN achieve near-perfect event detection and sub-millisecond onset errors. On real bubbly and slug flow sensor data, classical threshold-based methods remain highly competitive on clean sensor signals, while DL models retain advantages under non-stationary baselines and clustered events, yielding accurate void and timing with no hand-tuned assumptions. Results support DL as a practical, data-driven complement to fixed algorithms, particularly in noisy or drift-dominated measuring conditions typical of nuclear thermal–hydraulic loops and safety-relevant test facilities. Full article

Conventional coring drilling tools suffer from suboptimal annular flow design, leading to excessive pressure loss and hydraulic torque in ultra-deep well coring operations. To address this issue, we propose a systematic multi-objective optimization framework for the annular flow structure of single-acting double-tube coring tools, with the dual objectives of minimizing annular pressure loss and local circumferential hydrodynamic torque exerted on the outer pipe surface. Four key design variables, including the inner diameter and angle of the flow distribution sub, the number of water outlets on the centralizer, and the distance between the slip seat and the inner step surface of the drill bit, were selected. 81 sample points were generated via L81 orthogonal experiments combined with 3D CFD simulations. High-precision XGBoost surrogate models were established, and PAWN global sensitivity analysis was performed to identify dominant factors. The improved non-dominated sorting whale optimization algorithm was used to obtain the Pareto optimal solution set. The results show that the number of water outlets on the centralizer is the most significant factor affecting annular pressure loss, while the distance between the slip seat and the drill bit’s inner step dominates hydraulic torque. Compared with the original design, the optimized structure reduces annular pressure loss by 32.36% and local hydraulic torque by 4.02%, an absolute decrease of approximately 9.46 N·m. This study provides a reusable optimization method and clear parameter direction for ultra-deep well coring tools. Full article

To address the issues of optimization instability and imbalance in the contributions of multiple governing equations in conventional Physics-Informed Neural Networks (PINNs) for hydraulic transient problems, a gradient-based equation adaptive weighting strategy is proposed in this study. This strategy is incorporated into the PINN framework, referred to as GEAW-PINNs (gradient-based equation adaptive weighting in Physics-Informed Neural Networks), for predicting pressure and flow velocity during water hammer events. In GEAW-PINNs, the loss terms associated with different governing equations in the partial differential equation (PDE) constraints are dynamically weighted, thereby enhancing training stability. In the model construction, the classical governing equations of water hammer are employed to establish the PDE constraints, in which the Brunone model is incorporated. Meanwhile, the corresponding model coefficient is treated as a trainable parameter, enabling simultaneous parameter inversion and prediction of pressure and flow velocity. High-accuracy numerical solutions are generated as reference data to validate the proposed framework. The results demonstrate that GEAW-PINN effectively improves the stability of PINNs for the prediction of pressure in water hammer phenomena, thereby enhancing overall optimization performance and prediction accuracy. For the reservoir–pipeline–valve system, the proposed method achieved relative errors of only 0.00742 for pressure and 0.0183 for velocity. And the proposed method can also provide accurate predictions in complex pipe network systems. For the pipeline network system, the absolute prediction errors were approximately 15 for pressure and 0.05 for velocity. Finally, the robustness of the proposed method was evaluated under different random seeds and 25 dB noise. The prediction error exhibited little variation across different random seeds, with a variance of only $1.1429\times {10}^{-7}$ and $6.87\times {10}^{-7}$. Under 25 dB noise, the prediction error increased only slightly to $9.88\times {10}^{-3}$ and $2.5\times {10}^{-2}$. This study provides a practical example for achieving stable PINN training in multi-physics coupled problems. Full article

Agrivoltaic (AV) systems represent a promising strategy for integrating renewable energy production and agricultural activity on the same land unit, while contributing to soil water conservation under increasingly frequent drought conditions. This preliminary, single-site case study investigates the effects of a horizontal biaxial tracking AV system on soil water dynamics in a durum wheat field in the Po Valley (Borgo Virgilio, Mantua, Italy) over a full monitoring period, covering the final crop growth stages and the post-harvest bare soil phase (May–December 2024). Monitoring of soil temperature, volumetric water content (VWC), and soil water potential (SWP) was conducted at four depths (15, 30, 45, and 60 cm) at one representative monitoring station per treatment, comparing soil under AV cover (AVC) and in unshaded conditions (UC), located 10 m apart. Paired VWC and SWP measurements were used to derive site-specific soil water characteristic curves (SWCCs) and to calibrate the agro-hydrological model CRITERIA-1D, which was used to estimate available water (AW) in the first 80 cm of depth for both treatments. Measured VWC values were higher in the AVC profile than in the UC profile at all monitored depths throughout the May–September period, with differences persisting, although at lower values through October–December. Estimated AW was consistently higher under AVC than in UC during both the dry and wet periods. Despite higher VWC, the AVC profile showed more negative average SWP values at all depths during summer. This pattern is consistent with the shape of the derived SWCCs and may point to differences in water-retaining capacity between the two profiles, possibly related to structural modifications induced by 13 years of AV system operation. These preliminary findings suggest that AV systems could potentially improve soil water availability in the root zone of rainfed cereal crops and propose the hypothesis that long-term AV cover may act as a driver of changes in soil hydraulic properties, with implications for the sustainability and climate resilience of dryland farming systems. However, given the design of this case study, with only one monitoring point per treatment, the observed differences reflect the specific monitored locations and cannot fully disentangle the AV treatment effect from pre-existing spatial heterogeneity in soil properties. The preliminary results obtained in this study should therefore not be generalised beyond the specific conditions of this case study, and the interpretations proposed here should be treated as unproven hypotheses rather than established conclusions. Further studies with spatial replication and multi-year monitoring are needed to confirm these patterns. Full article

Aquaponic systems couple fish and plant production in recirculating loops, yet quantitatively assessed dynamic models for engineering analysis, scale-up, and operation under realistic conditions remain limited. Here, a modular process-based MATLAB R2026a framework is developed for the recirculating aquaponic system operated at the ASTREDHOR facility (France). The model links hydraulic transport with fish metabolism, nitrification, solids removal, and plant nitrate uptake, using monitoring-derived boundary conditions for temperature, dissolved oxygen, pH, and electrical conductivity. The fish-growth component was calibrated and evaluated against archived, temporally reconstructed biomass trajectories derived from campaign-based biometrics in three production cycles with different fish compositions and environmental regimes. Tank-wise $R^2$ values were 0.865–0.952 in the calibration windows and 0.700–0.921 in the fixed-parameter prediction windows, with prediction-period NRMSE values of 0.64–3.91%. These descriptive metrics quantify agreement on the reconstructed evaluation grid rather than performance over independently retained biometric sampling occasions. Complete corresponding time series were unavailable for TAN, ${\mathrm{NO}}_2^{-}$, ${\mathrm{NO}}_3^{-}$, total suspended solids, and plant uptake; these simulated outputs were therefore used only for mechanistic consistency assessment and exploratory scenario analysis, rather than independent validation. Local sensitivity analysis showed limited effects of temperature sensitivity (${\alpha }_T$), optimal temperature ($T_{opt}$), and minimum dissolved oxygen ($D{O}_{min}$) under observed conditions, whereas the feeding ratio ($TR$) and metabolic scaling exponent (n) strongly influenced simulated fish growth and nitrogen loading. Parametric sweeps provided preliminary, model-derived indications of feeding and biofilter-sizing limits under intensified loading; these thresholds require confirmation against independent water-quality measurements. The resulting framework is positioned as an off-line digital shadow with a fish-growth component assessed against reconstructed biomass trajectories and exploratory water-quality simulations. Full article