Transient Pressure Response in Pipes Colonized by Golden Mussels (Limnoperna fortunei): An Experimental Study

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This study provides applicable insights for operators of hydropower facilities and water utilities affected by golden mussel biofouling. The results can assist in developing mitigation strategies for transient pressure control in critical infrastructures.

Abstract

Rapid pressure fluctuations—known as hydraulic transients—occur during valve operations or load changes in turbines and pumps. The presence of biofouling, particularly caused by the golden mussel (Limnoperna fortunei), can intensify these effects and compromise the structural integrity of pressurized systems. This study experimentally evaluated the influence of such biofouling on pressure peaks during transient events in forced conduits. A hydraulic test rig was developed using PVC pipes with nominal diameters of 2½”, 3”, and 4”, tested under both clean conditions and with simulated biofouling printed in 3D, replicating mussel morphology. Results showed that, under the same initial flow rates, pressure peaks in biofouled pipes were significantly higher than in clean ones, especially in smaller diameters. To mitigate structural risks, the downstream shut-off valve closure time was modulated using a needle valve, effectively reducing peak pressures to levels closer to design limits. It is concluded that L. fortunei colonization alters transient hydraulic behavior and should be considered in the design and operation of systems vulnerable to biofouling, particularly in critical infrastructure such as water supply networks and hydroelectric power plants.

1. Introduction

The proliferation of aquatic invasive species and their impact on hydraulic systems have emerged as significant concerns for the operation, maintenance, and safety of water infrastructure. Among the most pervasive species in South America is the golden mussel (Limnoperna fortunei), a freshwater bivalve mollusk native to Southeast Asia. Introduced to the continent in the 1990s—primarily through ballast water discharge—its rapid dissemination has been facilitated by high reproductive rates, short life cycles, and broad environmental tolerance.

Once established, L. fortunei forms dense colonies on submerged surfaces, with adhesion densities exceeding 10,000 individuals per square meter. These biofouling layers obstruct pipelines, restrict flow, increase head losses, and impair the functioning of hydraulic components such as valves, pumps, and conduits. Beyond ecological impacts—including alterations in planktonic communities and intensified eutrophication—the presence of this species in pressurized conduits introduces direct technical challenges to the dynamic behavior of hydraulic systems.

A particularly critical phenomenon in such systems is the occurrence of hydraulic transients—rapid pressure fluctuations caused by abrupt changes in flow velocity, typically induced by valve closures or pump shutdowns. These events, commonly referred to as water hammer, may generate extreme overpressures that surpass the design limits of piping systems. While previous research has explored hydraulic transients under various operational conditions, including the influence of internal roughness and geometric obstructions, there remains a considerable gap in the literature concerning the specific effects of biological biofouling—particularly that caused by L. fortunei—on transient pressure wave propagation and intensity.

Despite increasing awareness of biofouling in water supply and energy systems, experimental studies quantifying how L. fortunei colonization alters the hydraulic response of pressurized systems remain limited. Furthermore, there is a notable lack of empirical data to inform the design and operation of infrastructure exposed to such biological pressures.

To address these gaps, the present study experimentally evaluates the influence of biofouling by Limnoperna fortunei on transient pressure behavior in pressurized pipelines. Simulated infestations were modeled using 3D-printed internal surfaces that replicate the mussel’s morphology. Tests were conducted using PVC pipes with nominal diameters of 2.5”, 3”, and 4”, under gravity-driven flow conditions, with pressure surges induced by abrupt valve closures. Additionally, a mitigation strategy based on controlled modulation of valve closure time was assessed for its effectiveness in reducing overpressure events.

By providing controlled laboratory data and practical engineering insights, this study advances the understanding of how biological colonization affects transient hydraulic phenomena. It further offers contributions to the development of preventive and adaptive strategies for the design, operation, and maintenance of water infrastructure vulnerable to invasive biofouling.

1.1. The Golden Mussel (Limnoperna fortunei)

Limnoperna fortunei, commonly known as the golden mussel, is a freshwater bivalve mollusk native to Southeast Asia that has, over the past few decades, become one of the most problematic invasive species across various South American freshwater ecosystems. Its introduction beyond its native range occurred primarily via ballast water discharge from ships, with initial records in South America dating back to the 1990s [1].

The species is characterized by a high reproductive rate, short life cycle, and a planktonic larval stage, which facilitates its dispersal through river systems [2]. It also exhibits remarkable tolerance to wide ranges of temperature, pH, nutrient availability, and flow velocity, all of which contribute to its invasive success [2,3].

This organism, native to Southeast Asia, shows a high capacity to adapt to both freshwater and brackish environments, with rapid growth, a short life cycle, effective osmoregulation, and a planktonic larval stage [4].

The rapid spread of the golden mussel in aquatic environments is often accelerated by anthropogenic factors, such as interbasin water transfer projects, which act as “invasion corridors” by connecting previously isolated watersheds, thus enabling the species to colonize new areas [5,6,7].

In invaded environments, L. fortunei causes both ecological and operational disruptions. Ecologically, it alters the composition and abundance of phytoplankton and zooplankton, disrupts nutrient cycling, and contributes to eutrophication through the excretion of nitrogen- and phosphorus-rich metabolites [2,3]. Its filtration activity also affects water transparency, potentially promoting the growth of toxic cyanobacteria [2,8].

From an engineering standpoint, dense mussel colonies—often exceeding 10,000 individuals per square meter—adhere to submerged surfaces, forming biofouling layers that clog pipelines, impair valves, and compromise pumping operations [1,9,10]. In water transfer systems and pressurized pipelines, such incrustations reduce hydraulic efficiency, increase head losses, and exacerbate the effects of hydraulic transients, such as water hammer [9,11].

Experimental studies have shown that flow velocity has a direct influence on the detachment of golden mussels adhered to different surfaces. The median velocities required to promote detachment were approximately 1.70 m/s on carbon steel, 1.72 m/s on rope, and 1.50 m/s on wood, indicating variations in adhesion depending on the type of substrate. Moreover, even materials with lower apparent roughness may require higher average velocities for the removal of the organisms, possibly due to the morphology and orientation of the mussel’s attachment filaments [12].

Given the ecological and operational impacts associated with biofouling by Limnoperna fortunei, various mitigation strategies have been explored in the literature. Environmental manipulation—particularly the control of water temperature and flow regimes—can inhibit the filtration activity of the organism, reducing its metabolic rate and colonization potential. This has been demonstrated in recent studies employing physio-hydrodynamic models to simulate behavior under different hydraulic conditions [2].

Moreover, the regulation of anthropogenic dispersal vectors—such as ballast water discharge, aquaculture practices, and recreational water use—is considered crucial to limit the spread of this invasive species, especially in ecologically sensitive regions such as the Cerrado biome [1]. Advances in genetic tools have also shown promise, enabling the characterization of population structure and dispersal pathways of L. fortunei, which in turn supports the development of regionally adapted and more effective control technologies [3].

Recent research highlights the potential of early detection through environmental DNA (eDNA) analysis as a strategic approach for mapping species distribution and anticipating ecological impacts [6,7]. Although existing control techniques have demonstrated effectiveness in localized applications—such as small water bodies and aqueducts—they remain limited in large-scale open reservoirs, where no single intervention proves consistently effective [13].

Nevertheless, there is still a notable gap in the literature regarding quantitative analyses of how biofouling by Limnoperna fortunei affects hydraulic transients in pressurized conduits, a phenomenon with significant implications for the integrity and operation of water infrastructure systems [11].

1.2. Hydraulic Transients in Pressurized Conduits

Hydraulic transients in pressurized conduits, commonly referred to as water hammer, are transient pressure phenomena that occur due to sudden changes in flow velocity within pressurized systems [14]. These variations can result from abrupt valve closures, pump shutdowns, or unexpected flow obstructions [15]. The impact of such events can generate excessive pressures capable of compromising the integrity of hydraulic components, including pipelines, joints, and control devices [16].

Experimental verifications described by Wang et al. [17] demonstrate that the maximum pressure in the pipeline exceeded the static pressure of the reservoir by more than 150 times. For the same static pressure, the increase in the initial flow velocity caused an initial increase in the maximum pressure, followed by a reduction and new growth, a behavior that was accentuated with the decrease in the static pressure of the reservoir [17].

Pressure waves are progressively dissipated due to head losses along the pipeline. Under these conditions, the waves propagate upstream and are gradually attenuated until the fluid velocity reaches zero after a certain period of time [18].

Mathematical modeling and computational simulation are essential tools for predicting and mitigating the effects of such phenomena. Approaches such as finite element methods, transfer functions, and state-space representations are frequently employed [19,20]. Specialized software has been used to simulate pressure wave propagation along long pipelines and identify critical points susceptible to failure [21].

Studies based on Computational Fluid Dynamics (CFD) have compared different valve closure modeling strategies, demonstrating that parameters such as valve response time have a direct influence on the magnitude of water hammer effects [21].

CFD studies in a hydroelectric power plant showed that during the closing of the linear valve in the first stage, a progressive increase in pressure was observed along the pipeline, with greater fluctuations recorded at the ends of the system. Reducing the closing time resulted in higher overpressure peaks, while gradually increasing this time proved effective in attenuating negative pressures. Additionally, for the same closing time, smaller units presented more frequent pressure oscillations in the terminal region of the valve, evidencing the influence of the size of the system on the transient behavior of the hydraulic network [22].

Experimental investigations have shown that rubber bypass branches can mitigate transient pressure surges in PVC pipelines, acting as passive energy dissipation mechanisms [23].

Additional factors—such as hydraulic friction, the presence of cavitation bubbles, and the geometry of suspended particles—also significantly influence flow behavior during transient events [24,25,26]. Hybrid models applied to systems combining closed conduits and open channels have proven effective in representing the complex hydrodynamic interactions involved [27].

Other relevant considerations include evaluating the performance of pneumatically actuated automatic valves, whose effectiveness can be compromised by delayed response to transient conditions [28]. In complex industrial environments, such as nuclear facilities or reactor systems, failures caused by water hammer represent critical risks that require integrated thermo-hydraulic modeling approaches [29].

An in-depth understanding of the mechanisms behind hydraulic transients and their associated variables is therefore essential for the safe design and operation of pressurized hydraulic systems, especially under critical conditions [30,31,32,33,34].

2. Materials and Methods

2.1. Characterization of Biological Infestation

Infestation by the invasive mollusk Limnoperna fortunei was considered a critical parameter in simulating the effects of biofouling on hydraulic transients in pressurized conduits. This species forms colonies that adhere to submerged surfaces, significantly altering the hydraulic properties of the system—particularly by modifying the internal roughness and geometry of pipelines.

To provide context, a real colony sample was collected from the reservoir of the Furnas Hydroelectric Plant (MG), where it was attached to the outer surface of a ¾” HDPE pipe. The sample was sent to the Limnoperna fortunei Research Laboratory (LELF/UFMG), where the projected shadow of the colony was analyzed on graph paper to characterize the topography of the fouled surface (Figure 1).

Studies conducted at the Hydraulic Research Center of UFMG (CPH-UFMG) aimed to physically characterize the incrustations by analyzing dried L. fortunei shells. However, logistical challenges—such as sourcing large shell quantities, time-consuming field collection, transportation, cleaning, structural sorting, and attachment to test surfaces—led to the development of controlled, laboratory-based alternatives. In addition, sanitary regulations and legal restrictions due to the species’ invasive potential impose strict limitations on its handling.

The biofouled surface used in this study was selected from a sample previously analyzed by Rico (2018) [35], as part of an experiment that investigated the hydraulic effects of Limnoperna fortunei colonization in open channels. This same sample was later selected by Santos et al. [34] due to its representative morphology of golden mussel fouling, and was subsequently used for three-dimensional scanning.

As described by Santos et al. [34], the scanning process employed structured light technology, generating a detailed virtual model composed of triangular meshes. For computational processing, the model was simplified using MeshLab software while preserving the essential geometric characteristics of the surface. A mesh independence analysis confirmed that the simplification introduced a relative error of less than 0.2% in the calculated roughness parameters, validating the accuracy and reliability of the final model.

The 3D scanning procedure enabled a high-resolution and geometrically faithful representation of the colonized surface, supporting detailed roughness characterization across the entire area of interest. Although this study focused on a specific sample, the adopted methodology—encompassing 3D scanning, controlled mesh simplification, and geometric validation—is replicable and applicable to other surfaces fouled by L. fortunei. Consequently, the results can be extended to a range of hydraulic scenarios impacted by this invasive species. The mesh analysis revealed an approximate difference of 14.0 mm between the highest and lowest points on the fouled surface. This value was adopted as the reference height e for the experimental biofouling model (Figure 2).

Based on Figure 3 and Equations (1)–(5), adapted from Souza et al. [9], the representative thickness of the biofouling over time was estimated using a Limnoperna fortunei growth curve specific to the sample under study, as presented in

Table 1. Estimated growth parameters of L. fortunei over time based on the adopted model.

t [s]	sl [mm]	θ	e [mm]	bs [mm]	sh [mm]		t [s]	sl [mm]	θ	e [mm]	bs [mm]	sh [mm]
1	2.6	32.7	0.8	0.5	1.3		22	29.7	41.2	12.3	7.5	19.8
2	4.5	34.5	1.5	0.9	2.4		23	30.5	41.4	12.7	7.7	20.4
3	6.4	35.7	2.2	1.3	3.5		24	31.3	41.4	13.0	8.0	21.0
4	8.2	36.5	2.9	1.7	4.6		25	32.0	41.5	13.4	8.2	21.6
5	9.9	37.2	3.5	2.2	5.7		26	32.7	41.6	13.7	8.4	22.1
6	11.6	37.7	4.2	2.6	6.8		27	33.5	41.7	14.1	8.6	22.7
7	13.1	38.2	4.9	3.0	7.8		28	34.2	41.8	14.4	8.8	23.2
8	14.6	38.6	5.5	3.4	8.8		29	34.9	41.9	14.8	9.0	23.8
9	16.0	38.9	6.1	3.7	9.8		30	35.6	42.0	15.1	9.2	24.3
10	17.4	39.2	6.7	4.1	10.8		31	36.3	42.0	15.4	9.4	24.8
11	18.7	39.5	7.3	4.4	11.7		32	37.0	42.1	15.8	9.6	25.4
12	19.9	39.7	7.8	4.8	12.6		33	37.7	42.2	16.1	9.8	25.9
13	21.1	39.9	8.3	5.1	13.4		34	38.4	42.3	16.5	10.0	26.5
14	22.2	40.1	8.8	5.4	14.2		35	39.1	42.3	16.8	10.3	27.1
15	23.3	40.3	9.3	5.7	15.0		36	39.8	42.4	17.2	10.5	27.6
16	24.3	40.5	9.8	6.0	15.8		37	40.5	42.5	17.5	10.7	28.2
17	25.3	40.6	10.3	6.3	16.5		38	41.3	42.6	17.9	10.9	28.8
18	26.3	40.8	10.7	6.5	17.2		39	42.1	42.6	18.3	11.2	29.5
19	27.2	40.9	11.1	6.8	17.9		40	42.9	42.7	18.7	11.4	30.1
20	28.1	41.0	11.5	7.0	18.5		41	43.8	42.8	19.1	11.7	30.8
21	28.9	41.1	11.9	7.3	19.2		42	44.6	42.9	19.6	11.9	31.5

.

$$\mathrm{s}\mathrm{l}=0.0005\ast {\mathrm{t}}^3-0.0458\ast {\mathrm{t}}^2+2.0912\mathrm{t}+0.5439$$

(1)

$$\mathsf{\theta }=29.873 \ast {\mathrm{sl}}^{0.0951}$$

(2)

$$\mathrm{e}=0.472\ast \mathrm{sl}\ast \tan \mathsf{\theta }$$

(3)

$$\mathrm{bs}=0.288\ast \mathrm{sl}\ast \tan \mathsf{\theta }$$

(4)

$$\mathrm{sh}=0.760\ast \mathrm{sl}\ast \tan \mathsf{\theta }$$

(5)

It is important to note that, in this study, the applied model neglects detachment effects. This simplification is justified by the fact that the experiment was conducted under bench-scale, gravity-driven flow conditions, operating at low flow rates.

This methodology enabled the creation of a representative morphological and hydraulic characterization of L. fortunei biofouling, providing a solid foundation for laboratory simulation of infestation scenarios.

Specific care was taken to ensure that, in none of the analyzed conduits, the average flow velocity exceeded the critical pullout limits of the golden mussel (Limnoperna fortunei), determined for different substrates by Castro [12]: 1.70 m/s on carbon steel, 1.72 m/s on rope, and 1.50 m/s on wood, as shown in

Table 2. Flow rate of L. fortunei over time based on the adopted model.

Diameter [in]	Flow Rate [m3/h]	Velocity in Clean Pipes	Velocity in Biofouled Pipes
4	25.50	0.90	1.31
4	11.60	0.41	0.60
4	6.10	0.22	0.31
3	11.60	0.73	1.23
3	6.10	0.38	0.65
2.1/2	6.10	0.51	0.95

.

It is important to highlight that flow velocities exceeding the critical threshold of approximately 1.7 m/s—identified as sufficient to induce detachment of Limnoperna fortunei from metallic and fibrous substrates [12]—may introduce additional operational risks. Although elevated velocities can promote partial removal of adhered colonies, the resulting biological debris may accumulate in downstream components such as valves, elbows, filters, or pipe constrictions, potentially leading to partial or complete blockages. Moreover, the sudden detachment and transport of these fragments can generate localized flow disturbances and pressure fluctuations, which may intensify hydraulic transient effects. These considerations underscore the need to maintain flow conditions within safe operational margins that simultaneously ensure hydraulic efficiency and mitigate the risks associated with biofouling removal.

This methodology enabled the creation of a representative morphological and hydraulic characterization of L. fortunei biofouling, providing a solid foundation for laboratory simulation of infestation scenarios.

In this study, 3D printing was proposed as an alternative to overcome the challenges mentioned above, despite the significant costs and time involved in manufacturing the test conduits.

To replicate the fouling pattern observed on the plate, a representative section of the scanned surface described in Santos et al. [34] was extracted. This segment was selected based on the assumption that it most accurately represented the overall morphology of the colonized surface. Angular cuts in triangular profiles were then made and sequentially assembled to form a test conduit (Figure 4, Figure 5, Figure 6 and Figure 7), following the fouling distribution pattern defined in Table 1. In this process, the mussel height e was set at 14.0 mm, consistent with the scanned data, while the average biofouling thickness was defined as 8.6 mm, based on Table 1. This geometric pattern was maintained across all modeled conduits.

Six conduits were fabricated, each measuring 2.40 m in length, using PVC pipes: two with diameters of 2½”, two of 3”, and two of 4”. For each diameter, one smooth (control) conduit and one simulating L. fortunei infestation were constructed.

Each biofouled conduit consisted of twelve 200 mm long elements connected using male–female joints within the corresponding PVC pipe. In total, thirty-six 3D-printed elements were manufactured to assemble the experimental conduits.

As a final note, the entire printing and preparation process required approximately one year.

The 2.40 m pipe length adopted for the experiments was defined based on operational, technical, and logistical considerations. The test sections were 3D-printed in 20 cm modules, this dimension being set slightly below the 22 cm maximum printable length of the equipment— making it practical to assemble a total length that was a multiple of 20 cm, ensuring geometric consistency and ease of handling. According to Azevedo Netto et al. [36], a straight pipe length of 10 to 30 times the internal diameter is recommended to ensure a fully developed turbulent velocity profile—criteria met by the adopted configuration. Additionally, 6 m PVC bars, commonly available in Brazil, allowed both test and control pipes to be produced from a single bar per diameter, minimizing waste.

Regarding diameters, 2½”, 3”, and 4” were selected from an initial range of five options (2”, 2½”, 3”, 4”, and 6”) due to their common use in Brazilian water distribution and conveyance systems, particularly in facilities susceptible to Limnoperna fortunei infestation. These intermediate sizes enabled the representation of different hydraulic scenarios while preserving experimental feasibility in terms of cost, duration, and complexity.

Figure 4. Assembly of the 3D-scanned segments to form a test conduit element.

Figure 4. Assembly of the 3D-scanned segments to form a test conduit element.

Figure 5. 3D printing design of one of the elements that make up one of the three test conduits with biofouling.

Figure 5. 3D printing design of one of the elements that make up one of the three test conduits with biofouling.

Figure 6. Set of 12 elements, each 0.20 m long, which will form one of the test conduits.

Figure 6. Set of 12 elements, each 0.20 m long, which will form one of the test conduits.

Figure 7. Assembled pipe representing the L. fortunei biofouling pattern in one of the test conduits.

Figure 7. Assembled pipe representing the L. fortunei biofouling pattern in one of the test conduits.

The biofouled pipe segments were fabricated using Fused Deposition Modeling (FDM) 3D printing with PLA filament, 0.3 mm layer height, and a 0.4 mm nozzle. While 3D printing is widely used in experimental hydraulics, concerns remain regarding its dimensional precision and surface roughness, which may affect flow behavior. According to De Souza et al. [37], such factors can lead to deviations when compared to machined components.

Studies by Rota et al. [38] and Oertel et al. [39] report dimensional deviations of around 0.4 mm—equivalent to the nozzle diameter—and less than 3% in discharge coefficients, respectively. In this study, the estimated deviation (~0.4 mm) represents about 1% of the average mussel length and was considered acceptable for the tested flow regime and physical scale. Thus, the simulation’s geometric fidelity and the reliability of results were preserved.

2.2. Experimental Setup

The experiments were conducted on a hydraulic test bench designed to investigate flow behavior and the effects of biofouling—particularly from Limnoperna fortunei—on transient phenomena (Figure 8). The setup includes a vertical head of approximately 4 m between the upstream reservoir and the discharge point, simulating realistic gravity-fed conditions in pressurized conduits and providing sufficient energy to trigger hydraulic transients.

Three test configurations were evaluated using rigid PVC conduits with nominal diameters of 2½”, 3”, and 4”. For each diameter, two conditions were analyzed:

• Reference conduit (control): clean pipe, free from fouling;
• Biofouled conduit: pipe partially coated internally with material simulating golden mussel colonies, representing typical infestation patterns.

2.3. Hydraulic Components

The experimental system consisted of the following components:

• Upstream reservoir: positioned at the highest point, with a total capacity of 4000 L and a central circular cross-section of 1.60 m in diameter.
• Main conduit: consisting of 1.45 m of cast iron piping with associated valves and fittings, along with 11.8 m of PVC pipeline, including a 2.40 m test section with flanged ends.
• Flow control valve: installed downstream to regulate flow conditions prior to transient generation.
• Quick-shut valve: a pneumatically actuated butterfly valve located at the end of the pipeline, responsible for inducing water hammer.

Figure 8. (a). Reservoir and initial flow line segment of the test bench. (b). Test bench containing the flow meter, pressure sensors, pneumatic valve, flow control valve, and one of the test conduits.

Figure 8. (a). Reservoir and initial flow line segment of the test bench. (b). Test bench containing the flow meter, pressure sensors, pneumatic valve, flow control valve, and one of the test conduits.

A schematic diagram of the experimental setup is presented in Figure 9, illustrating the configuration of the test section, instrumentation layout, and flow direction. This visual representation aims to facilitate the understanding of the experimental procedures and the positioning of key components.

Figure 9. Schematic diagram illustrating the main components of the experimental system.

Figure 9. Schematic diagram illustrating the main components of the experimental system.

2.4. Hydraulic Transient Generation and Pneumatic Control System

Sudden flow blockage was achieved using a butterfly valve actuated by a pneumatic actuator, electronically controlled via a solenoid valve (Figure 10). The air supply system included a compressor calibrated to 5.2 bar, providing pressure to the actuator. Valve closure time was fine-tuned using a needle valve installed at the solenoid outlet, enabling precise control of transient intensity.

Figure 10. (a). Detail of the potentiometer mounted on top of the pneumatic actuator for measuring the valve closing time. (b). Detail of the needle valves used to control the air outlet and, consequently, the valve closing time.

Figure 10. (a). Detail of the potentiometer mounted on top of the pneumatic actuator for measuring the valve closing time. (b). Detail of the needle valves used to control the air outlet and, consequently, the valve closing time.

2.5. Instrumentation and Data Acquisition

The instrumentation system employed in this study comprised the following components:

Pressure Transmitters (PT-001, PT-002, PT-003): Industrial-grade sensors with a 4–20 mA output signal and ±0.5% accuracy. Calibration was performed using a certified reference pressure gauge with a measurement uncertainty of 0.68%. Only PT-001, positioned closest to the shut-off valve, was considered in the analysis, as it consistently recorded the highest overpressure values.

Ultrasonic Flow Transmitter (FT-001): A non-invasive ultrasonic flowmeter with a 4–20 mA output and ±1% accuracy. It was calibrated against a certified reference flowmeter with an uncertainty of 0.1 m³/h. The sensor was installed upstream of the test section, in a region of fully developed flow, according to recommended distances to reduce signal interference.

Valve Position Transmitter (ZT-001): A single-turn 10 kΩ analog potentiometer mounted on the pneumatic actuator shaft to track the angular displacement of the butterfly valve disc. A signal corresponding to the fully closed position was set as 0% opening, and the fully open position as 100%. Measurement resolution was determined by the 10-bit analog-to-digital converter of the acquisition unit.

Data Acquisition System: Built on an ATmega328P microcontroller (Arduino Nano platform), operating at 16 MHz and equipped with 10-bit A/D converters. Pressure, flow, and valve position data were sampled at 200 Hz and logged in real time using a custom MATLAB 2022 script, ensuring high-resolution capture of transient events.

The accuracy and resolution of each instrument were verified to confirm that the overall measurement uncertainty remained within acceptable limits for hydraulic data analysis.

2.6. Theoretical Considerations on Biofouling Effects

From a theoretical perspective, biological sedimentation modifies the propagation of pressure waves in pressurized conduits through multiple interrelated mechanisms. Firstly, colonization by Limnoperna fortunei significantly increases the internal wall roughness, thereby intensifying distributed frictional losses along the flow path [9]. These increased losses promote more rapid attenuation of pressure waves as they travel through the system. Secondly, biofouling reduces the effective cross-sectional area of the conduit, leading to higher local flow velocities for a given discharge rate. Considering that the magnitude of pressure surges is directly proportional to the change in flow velocity [36], the velocity amplification induced by biofouling contributes to elevated peak pressures during transient events. Lastly, the geometric irregularities formed by the fouling layer function as localized zones of energy dissipation, causing partial reflection, scattering, and distortion of the pressure wavefront. Collectively, these phenomena influence the wave celerity, amplify surge pressures, and alter the damping characteristics of the transient response.

3. Results and Discussion

Figure 11, Figure 12, Figure 13, Figure 14, Figure 15 and Figure 16 present the average results obtained from four experimental repetitions, based on readings from Pressure Sensor 1—located immediately upstream of the shut-off valve—and the potentiometer attached to the valve’s pneumatic actuator. Both devices were integrated into the test bench and used to evaluate the system’s response during sudden valve closure. Each graph corresponds to a specific test condition, defined by the combination of nominal pipe diameter (2½”, 3”, or 4”) and flow rate (6.1, 11.6, or 25.5 m³/h).

In the graphs, the left vertical axis represents the pressure in meters of the water column (mH₂O) measured by the pressure sensor, while the right vertical axis indicates the percentage of the valve opening derived from the potentiometer signal. Solid lines correspond to pressure readings under three conditions:

• Black line (SM): clean pipe, no biofouling (reference condition).
• Red line (CM): biofouled pipe with fully open needle valve (fast closure).
• Blue line (CM)*: biofouled pipe with partially closed needle valve (slowed closure).

Dashed lines indicate the actuator’s motion during valve closure, enabling direct correlation between transient pressure behavior and valve dynamics.

Overall, the results indicate that biofouling significantly affects both the magnitude and profile of the pressure surge, especially in smaller-diameter pipes. The strategy of slowing down valve closure (CM*) proved effective in mitigating these effects and shows potential for use in biofouling-prone systems.

3.1. Pipe 2½”, Flow Rate 6.1 m³/h

In the smallest cross-sectional area evaluated, biofouling caused a sharp increase in peak pressure. The CM condition reached a maximum pressure of 13.3 mH₂O compared to 9.0 mH₂O in the SM condition—an increase of 48.4%. This spike is attributed to increased flow velocity, added surface roughness, and higher head loss caused by mussels adhered to the pipe wall.

To reduce this pressure spike in the CM condition to values equal to or lower than in the SM condition, the valve closure time was adjusted. While the clean pipe (SM) closed in 0.88 s, the CM* condition required 1.98 s—a 117.6% increase. This adjustment reduced the peak pressure to 8.7 mH₂O—lower than the reference (Figure 11).

These findings reinforce that adjusting valve closure time is an effective strategy to mitigate the adverse hydraulic effects of biofouling, especially in systems more vulnerable to pressure surges.

Figure 11. Transient pressure behavior and valve closure dynamics in a 2½” pipe operating at 6.1 m³/h. Solid lines indicate pressure readings: black (SM)—reference pipe without biofouling; red (CM)—biofouled pipe with rapid valve closure; blue (CM*)—biofouled pipe with delayed valve closure. Dashed lines represent the actuation movement of the pneumatic valve.

Figure 11. Transient pressure behavior and valve closure dynamics in a 2½” pipe operating at 6.1 m³/h. Solid lines indicate pressure readings: black (SM)—reference pipe without biofouling; red (CM)—biofouled pipe with rapid valve closure; blue (CM*)—biofouled pipe with delayed valve closure. Dashed lines represent the actuation movement of the pneumatic valve.

3.2. Pipe 3”, Flow Rate 6.1 m³/h

With the increased pipe diameter, the influence of biofouling became less pronounced. Peak pressure rose modestly from 9.0 mH₂O (SM) to 9.7 mH₂O (CM), an increase of only 7.1%. The delayed closure in the CM* condition extended the closure time to 1.05 s (up 27.3%), which was sufficient to mitigate the surge (Figure 12).

Here, the oscillatory response following valve closure was more dampened, suggesting that the system’s capacity to dissipate energy was greater in the presence of fouling, possibly due to added turbulence and flow resistance.

Figure 12. Pressure response and valve actuation in a 3” pipe at 6.1 m³/h, under different biofouling and closure conditions. A slight pressure increase is observed in the biofouled condition (CM), with noticeable damping in the CM* condition due to slower valve closure.

Figure 12. Pressure response and valve actuation in a 3” pipe at 6.1 m³/h, under different biofouling and closure conditions. A slight pressure increase is observed in the biofouled condition (CM), with noticeable damping in the CM* condition due to slower valve closure.

3.3. Pipe 3”, Flow Rate 11.6 m³/h

The increase in flow rate amplified the water hammer effects. The CM condition recorded a peak of 13.2 mH₂O versus 11.4 mH₂O in the SM condition—an increase of 15.8%. The delayed closure in CM* increased closure time to 1.24 s (a 47.1% increase), significantly reducing the pressure amplitude (Figure 13).

The waveform pattern remained very similar to the previous test, while the needle valve modulation effectively restored safe operating levels consistent with design expectations.

Figure 13. Transient pressure variation in a 3” pipe operating at 11.6 m³/h. The CM* condition reduces peak pressures and extends valve closure time, promoting system stability.

Figure 13. Transient pressure variation in a 3” pipe operating at 11.6 m³/h. The CM* condition reduces peak pressures and extends valve closure time, promoting system stability.

3.4. Pipe 4”, Flow Rate 6.1 m³/h

In this larger-diameter, low-flow scenario, biofouling effects were negligible. The pressure peak changed only 2.0%, from 8.2 mH₂O (SM) to 8.3 mH₂O (CM). Closure time remained almost unchanged at 0.82 s (Figure 14).

This result demonstrates that for large-diameter pipes under low flow, the influence of L. fortunei is minimal, and mitigation strategies may be unnecessary in such cases.

Figure 14. Pressure response in a 4” pipe with a flow rate of 6.1 m³/h. Biofouling influence on transient behavior is minimal; pressure curves for SM and CM conditions are nearly identical. Damping effect from valve modulation is negligible in this configuration.

Figure 14. Pressure response in a 4” pipe with a flow rate of 6.1 m³/h. Biofouling influence on transient behavior is minimal; pressure curves for SM and CM conditions are nearly identical. Damping effect from valve modulation is negligible in this configuration.

3.5. Pipe 4”, Flow Rate 11.6 m³/h

Despite a 90% increase in flow compared to the previous test, the impact of biofouling remained minor. The peak pressure changed by just 1.0% (11.0 mH₂O to 11.1 mH₂O), with a constant closure time of about 0.81 s. While oscillations became slightly more evident, they were not significantly influenced by biofouling (Figure 15).

These results suggest that for systems with large diameters and moderate flow rates, L. fortunei colonization has little to no effect on transient pressure events.

Figure 15. Comparison of pressure curves in a 4” pipe at 11.6 m³/h. Slight increase in peak pressure under CM condition; however, the overall transient response remains stable. The CM* condition provides minor improvement in oscillation damping.

Figure 15. Comparison of pressure curves in a 4” pipe at 11.6 m³/h. Slight increase in peak pressure under CM condition; however, the overall transient response remains stable. The CM* condition provides minor improvement in oscillation damping.

3.6. Pipe 4”, Flow Rate 25.5 m³/h

In this configuration—representing the highest kinetic energy tested for this diameter—the impact of biofouling became significant. Peak pressure increased by 23.4%, from 14.0 mH₂O (SM) to 17.2 mH₂O (CM) (Figure 16). This indicates that under high-flow conditions, biofouling in large-diameter pipes can pose relevant hydrodynamic risks.

The extended closure time in CM* (1.49 s, a 69.2% increase) effectively reduced surge amplitudes and restored system stability.

Figure 16. Evolution of peak pressures in a 4” pipe operating at 25.5 m³/h. Biofouling (CM condition) causes a significant increase in peak pressure. Modulating valve closure time (CM*) effectively reduces the amplitude of transient oscillations.

Figure 16. Evolution of peak pressures in a 4” pipe operating at 25.5 m³/h. Biofouling (CM condition) causes a significant increase in peak pressure. Modulating valve closure time (CM*) effectively reduces the amplitude of transient oscillations.

To provide a clearer overview of the experimental results,

Table 3. Summary of key experimental results.

Graph	Pipe Diameter	Flow Rate (m3/h)	SM Peak Pressure (mH2O)	CM Peak Pressure (mH2O)	SM Valve Time (s)	CM* Valve Time (s)
Figure 11	2½”	6.1	9.0	13.3	0.88	1.98
Figure 12	3”	6.1	9.0	9.7	0.88	1.05
Figure 13	3”	11.6	11.4	13.2	0.88	1.24
Figure 14	4”	6.1	8.2	8.3	0.82	0.82
Figure 15	4”	11.6	11.0	11.1	0.81	0.81
Figure 16	4”	25.5	14.0	17.2	0.82	1.49

summarizes the key parameters for each of the six test conditions. It includes pipe diameters, flow rates, peak pressure values observed in both clean and biofouled pipes, the valve closure times applied, and the effectiveness of delayed closure in mitigating hydraulic transients. Notably, for the cases corresponding to Figure 14 and Figure 15, the valve closure time was not adjusted, as the pressure difference between clean and fouled conditions was only 0.1 mH₂O—representing an increase of less than 2%.

Although the experimental approach provided direct and quantitative insights into the effects of biofouling during pressure transients, it did not include numerical simulations of the internal flow field. Nevertheless, computational fluid dynamics (CFD) techniques represent a powerful tool to visualize and analyze the three-dimensional distribution of velocity, pressure, and turbulence within fouled pipelines. Future studies conducted by our research group will incorporate such simulations to deepen the understanding of transient flow behavior and support the development of predictive models for systems affected by golden mussel colonization.

In this context, methodologies used in advanced surface finishing processes for confined geometries—such as the Soft Abrasive Flow (SAF) technique—have highlighted the importance of multiphase flow modeling and the assessment of local hydrodynamic effects, including cavitation and surface abrasion. These approaches contribute to a better understanding of complex interactions in constrained environments [40] and offer valuable potential for future investigations into the influence of biofouling on flow dynamics and energy dissipation mechanisms during hydraulic transients.

4. Conclusions

This experimental study demonstrates that biofouling caused by the golden mussel (Limnoperna fortunei) significantly influences the transient hydraulic behavior of pressurized conduit systems. The presence of simulated bioincrustation—represented by 3D-printed internal roughness—resulted in substantial increases in peak pressure during valve closure events, particularly in smaller-diameter conduits and under higher flow conditions. For example, in the 2½” pipe operating at 6.1 m³/h, the peak transient pressure rose by 48.4% (from 9.0 to 13.3 mH₂O) due to biofouling. In the 4” pipe at 25.5 m³/h, the increase reached 23.4%, highlighting the importance of flow rate even in larger systems.

These findings hold critical implications for the design, operation, and risk management of hydraulic infrastructures susceptible to invasive species, such as hydroelectric facilities and potable water distribution networks. The study also demonstrates that modulating valve closure time—achieved through the installation of a needle valve—effectively mitigates pressure surges. In all experimental conditions, this control strategy reduced peak pressures to values equal to or below those observed in clean pipes. It therefore represents a practical, low-cost, and easily deployable solution to safeguard hydraulic systems from biofouling-induced transients.

This research contributes novel empirical evidence to the emerging interface between biological invasions and hydraulic engineering. It underscores the need for interdisciplinary approaches that integrate ecological surveillance, early detection of invasive species, and adaptation of control strategies to mitigate the hydrodynamic impacts of biofouling.

Nevertheless, certain limitations must be acknowledged. The experiments were conducted on a bench scale and under low-pressure, gravity-driven conditions, which may not fully capture the complexity of large-scale or pressurized systems. Additionally, the potential detachment of mussels under high shear stress was not evaluated, as the flow velocities remained moderate. Future work should incorporate Computational Fluid Dynamics (CFD) to model three-dimensional flow structures and simulate interactions between flow, infrastructure, and biological material under varied operating scenarios. Expanding the methodology to pilot-scale or in situ applications would further strengthen the external validity of the findings.

In summary, the study highlights the relevance of biofouling as a key factor in transient flow behavior and supports the development of proactive maintenance and control strategies aimed at improving the resilience and operational safety of water infrastructure systems.