Design Parameters Research Articles

Developed a solar still unit for saltwater desalination: numerical prediction and performance verification

Abstract In the globe, there is a rise in water demand for agricultural, industrial, and domestic purposes. Single-basin solar stills (SBSS) have been a subject of research in various countries, particularly in regions with water scarcity or limited access to clean drinking water. In this work, SBSS for desalinating high-salinity water were developed, tested, and evaluated based on a developed numerical model using MATLAB R2021a program to predict the best productivity through the best selection of raw materials used to develop the SBSS. A four-inclined SBSS was fabricated and examined experimentally according to numerical model findings for best design parameters at Marsa Matrouh, 31° 21′ 10.44″N, 27°14′14.10″ E, Agricultural Station—Agricultural Research Center (ARC), Egypt. The hourly experimental results are compared with the numerical results. A good correlation between the numerical and the experimental results with variations in water, and glass temperatures of 9, and 18% respectively, and a variation in cumulative productivity by 11%. The results clearly showed that instantaneous productivity increases by decreasing water depth to 10 mm and using the SBSS unit partially insulated from the bottom of the basin. Adding insulation in front of the sides and back of tempered glass increases the shading area and decreases water temperature hence the cumulative productivity by 15%. The cumulative productivity reached 3 L for the SBSS unit partially insulated from the bottom of the basin with an area of 0.6 m2 for only 12 h working system at a water depth of 10 mm.

Explicit Analytical Form for the Average Run Length of Double-Modified Exponentially Weighted Moving Average Control Charts Through the MA(q) Process and Applications

The Statistical Process Control (SPC) approach using mathematical modeling proves effective for correlated data, with applications in healthcare, finance, and technology to enhance quality and efficiency. Here, we provide a novel SPC method using mathematical modeling and discuss its use in simulation tests to assess its applicability for tracking processes containing correlated data operating on sophisticated control charts. Particularly, an approach for detecting small shifts in the mean of a process running on the double-modified exponentially weighted moving average (DMEWMA) control chart, which is symmetric about the center line with upper and lower control limits, is of special interest. The computations showed exceptional accuracy, with ARL from the explicit formula closely matching that from the NIE method. Simulation tests assess its applicability in detecting small mean shifts and compare its performance with exponentially weighted moving average (EWMA) and modified exponentially weighted moving average (MEWMA) control charts across various scenarios. For several values of the design parameters, the performances of these three control charts are also compared in terms of the relative average index and relative standard deviation index. The results show that the DMEWMA chart outperforms others for several process mean shifts. The method’s practical use is demonstrated with stock data, highlighting its superior effectiveness in enhancing process monitoring.

Nonlinear damping amplifier friction bearings

Abstract The paper introduces damping amplifiers integrated into the core material of conventional nonlinear friction base isolators to improve their vibration attenuation capabilities and mitigate their shortcomings. Four new types of damping amplifier friction bearings are introduced: levered, nested, compound, and damping. The H2 optimisation strategy is utilised to obtain the closed-form analytical solution for the optimised designed parameters. The analytical investigation confirms the efficiency of the recently obtained closed-form equations for the optimal design parameters. The frequency response function was used to develop closed-form formulas for the isolator and main structure's dynamic responses. The harmonic and random white-noise excitation served as the basis. Furthermore, numerical analysis by considering real earthquake load has confirmed the novel isolators' efficiency. The vibration reduction capacities of the H2 optimised damping amplifier friction bearings, compound damping amplifier friction bearings, nested damping amplifier friction bearings, and levered damping amplifier friction bearings are 76.1 % superior to the optimum conventional base isolator. These findings demonstrate how the proposed designs may improve structural resistance to dynamic loads.

Induction Motor Geometric Parameter Optimization Using a Metaheuristic Optimization Method for High-Efficiency Motor Design

In this study, the optimum design for an induction motor (IM) was realized by providing details of its geometric design. The IM optimization was carried out using the Artificial Ecosystem-based Optimization (AEO) algorithm, a metaheuristic method. The AEO algorithm was used for the first time in IM optimization, and the design parameters were optimized. Ten motor design parameters were used as design variables. IM efficiency was improved, as the objective function. The genetic algorithm (GA) optimization method was used for comparison with the results obtained with the AEO method. The optimized and unoptimized results of the IM design generated with codes created in the Matlab program were verified with the Ansys RMxprt program, and it could be seen that the results are in good agreement. As a result of these studies, it was observed that the use of AEO in determining the geometric parameters of the IM had better convergence accuracy and reached the optimum result in a shorter time compared to the GA optimization method. It was observed that IM efficiency increased from 90.34% to 91.575% on average with the AEO method.

Guided Waves in Composite Overwrapped Pressure Vessels and Considerations for Sensor Placement Toward Structural Health Monitoring—An Experimental Study

Abstract The utilization of composite overwrapped pressure vessels (COPVs) to store hydrogen, especially at high pressures, is gaining more popularity due to their lightweight design and high storage density, offering significant economic advantages. However, the presence of material defects or fatigue can lead to critical failures, requiring an innovative and robust approach to ensure safe operation and system integrity. Developing a continuous structural health monitoring (SHM) system for COPVs can provide comprehensive real-time information about their condition, facilitating a shift away from periodic inspections. This study scrutinizes the behavior of guided waves (GWs) within COPVs to design a sensor network for damage detection and localization. First, the dispersive and multimodal propagation behavior of GWs is experimentally investigated. Subsequently, important parameters for the network design are derived and finally a sensor network consisting of 15 piezoelectric transducers is designed to cover the entire cylindrical area. The effectiveness is then evaluated experimentally by placing artificial defects on the surface of the COPV. The multi-layered dataset of GW signals was analyzed using both commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as statistical features (kurtosis, skewness, variance, etc.). These features were utilized to compute a damage index, and the effectiveness of the detection performance was assessed using receiver operating characteristic curves. It can be seen that some features are more sensitive and robust under varying experimental conditions. The results show that ultrasonic GW SHM system is a promising solution for damage detection and localization in COPVs.

Design Analysis and Isotropic Optimization for Miniature Capacitive Force/Torque Sensor

A capacitive six-axis force/torque (F/T) sensor has favorable characteristics for miniature design. However, when designing small-sized force/torque sensors, anisotropy among the six axes can lead to uneven sensitivity across each axis. This is due to increased crosstalk errors, which degrade sensor performance. To design a miniature six-axis force/torque sensor, it is essential to analyze the isotropic relationships between the six-axis forces/torques and the capacitance change to reduce crosstalk errors. This paper presents a miniature capacitive six-axis F/T sensor optimized for isotropy. It also establishes a systematic method for designing sensing electrodes. The sensor’s deformable structure is analyzed using Castigliano’s beam theory, and design parameters are optimized with isotropy analysis of the deformable part. The criteria are also presented, including selecting the electrode area and initial gap using linear equations derived from capacitance change analysis. The optimized miniature F/T sensor is calibrated using a neural network-based calibration method, and its accuracy errors are compared to a reference sensor. The design framework provides a foundation for future developments in miniature sensors.

Analytical Modeling and Design Optimization of High‐Performance ZnO‐Nanowire/CuO‐Thin Film/p+‐Si Multi‐Junction Solar Cells

In the current work, an optimized design window for the indium tin oxide (ITO)/n‐ZnO‐nanowire (NW)/p‐CuO‐thin film/p+‐Si multi‐junction solar cells is provided for achieving high power conversion efficiency (PCE). The requisite model has been developed using the drift‐diffusion approach and validated against existing experimental data. The effects of various design parameters are thoroughly investigated and optimized to achieve higher PCE. Initially, by optimizing the lengths of ZnO NWs and the thickness of CuO films, a PCE of 22% is achieved. To enhance the PCE further, ZnO NWs are doped with cobalt (Co) (0–15%), and the CuO thin film is doped with graphene (Gr) (0–10%), independently. The impact of annealing of the top‐ITO layer on PCE has also been studied without any doping. Finally, optimizing the geometric parameters of ZnO‐NW (length of 200 nm), CuO thin film (thickness of 350 nm), doping concentrations of Co (5%) and Gr (5%), and the annealing temperature of ITO (450 °C), PCE of the proposed n‐ZnO‐NW/p‐CuO‐thin film/p+‐Si multi‐junction solar cell is obtained to be ≈40%. Thus, in this work, a comprehensive set of design parameters for ZnO‐NW/CuO‐thin‐film/Si‐based solar cells is provided to achieve high PCE.

Mitigating the Impact of Partial Shading Conditions on Photovoltaic Arrays Through Modified Bridge-Linked Configuration

Global reliance on depleting energy resources is driving the urgent need for alternative solutions to address escalating energy demands. Solar energy, a prominent renewable resource, leverages various configurations and techniques to maximize power output, even under challenging environmental conditions. In photovoltaic (PV) arrays, partial shading conditions (PSCs) significantly hinder efficiency by reducing power extraction across solar panels. Traditionally, configurations such as series, parallel, series-to-parallel, and bridge-linked (BL) are employed to optimize power output; however, each has limitations under PSCs. Here, we introduce a modified bridge-linked (Modified BL) configuration designed to mitigate the adverse effects of partial shading on PV arrays. This approach allows for interconnected solar modules that reduce shading impact across an entire array, thus preserving efficiency by isolating shaded sections and minimizing power loss. The Modified BL configuration not only supports maximum power point tracking (MPPT) but also enhances resilience against shading, ensuring stable power output. Our simulation results underscore the critical influence of irradiance levels on PV electricity generation, suggesting that incorporating irradiance variability as a design parameter is essential in selecting optimal PV interconnection schemes under PSCs. This study contributes to advancing solar array design by providing a robust method to maintain power output in partial shading conditions, ultimately supporting broader efforts in renewable energy optimization.

Computational Fluid Dynamics Modeling of Material Transport Through Triply Periodic Minimal Surface Scaffolds for Bone Tissue Engineering.

Cell-laden, scaffold-based tissue engineering methods have been successfully utilized for the treatment of bone fractures and diseases, caused by factors such as trauma, tumors, congenital anomalies, and aging. In such methods, the rate of scaffold biodegradation, transport of nutrients and growth factors, as well as removal of cell metabolic wastes at the site of injury are critical fluid-dynamics factors, affecting cell proliferation and ultimately tissue regeneration. Therefore, there is a critical need to identify the underlying material transport mechanisms and factors associated with cell-seeded, scaffold-based bone tissue engineering. The overarching goal of this study is to contribute to patient-specific, clinical treatment of bone pathology. The overall objective of the work is to establish computational fluid dynamics (CFD) models: (i) to identify the consequential mechanisms behind internal and external material transport through/over porous bone scaffolds designed based on the principles of triply periodic minimal surfaces (TPMS) and (ii) to identify TPMS designs with optimal geometry and flow characteristics for the treatment of bone fractures in clinical practice. In this study, advanced CFD models were established based on ten TPMS scaffold designs for (i) single-unit internal flow analysis, (ii) single-unit external flow analysis, and (iii) cubic, full-scaffold external flow analysis, where the geometry of each design was parametrically created. The influence of several design parameters, such as surface representation iteration, wall thickness, and pore size on geometry accuracy as well as computation time, was investigated in order to obtain computationally efficient and accurate CFD models. The fluid properties (such as density and dynamic viscosity) as well as the boundary conditions (such as no-slip condition, inlet flow velocity, and pressure outlet) of the CFD models were set based on clinical/research values reported in the literature, according to the fundamentals of internal and external Newtonian flow modeling. The main fluid characteristics influential in bone regeneration, including flow velocity, flow pressure, and wall shear stress (WSS), were analyzed to observe material transport internally through and externally over the TPMS scaffold designs. Regarding the single-unit internal flow analysis, it was observed that P.W. Hybrid and Neovius designs had the highest level of not only flow pressure but also WSS. This can be attributed to their relatively flat surfaces when compared to the rest of the TPMS designs. Schwarz primitive (P) appeared to have the lowest level of flow pressure and WSS (desirable for development of bone tissues) due to its relatively open channels allowing for more effortless fluid transport. An analysis of streamline velocity exhibited an increase in velocity togther with a depiction of potential turbulent motion along the curved sections of the TPMS designs. Regarding the single-unit external flow analysis, it was observed that Neovius and Diamond yielded the highest level of flow pressure and WSS, respectively, while Schwarz primitive (P) similarly had a relatively low level of flow pressure and WSS suitable for bone regeneration. Besides, pressure buildup was observed within the inner channels of almost all the TPMS designs due to flow resistance and the intrinsic interaction between the fluid flow and the scaffold walls. Regarding the cubic (full-scaffold) external flow analysis, the Diamond and Schwarz gyroid (G) designs appeared to have a relatively high level of both flow pressure and WSS, while Schwarz primitive (P) similarly yielded a low level of flow pressure and WSS. Overall, the outcomes of this study pave the way for optimal design and fabrication of complex, bone-like tissues with desired material transport properties for cell-laden, scaffold-based treatment of bone fractures.

Design, Development and Optimization of a Robotic Weed Control System for Greenhouses

This study presents the design and development of a robotic prototype specifically engineered for weed elimination within cucumber plants growing in greenhouse conditions. Given the limited research in automated weed control tailored to cucumber cultivation, this project fills a crucial gap in agricultural robotics. The cucumber plants are arranged in a single row, maintaining a spacing of approximately 40 cm between each plant, while the rows themselves are positioned about 1 meter apart. The greenhouse environment features sandy loam soil, which informs the robot's design and operational parameters. The robot employs three arrays of ultrasonic sensors strategically positioned to enhance weed detection capabilities. A PIC18 F4550-E/P microcontroller serves as the processing unit, enabling real-time feedback from the sensors that triggers the actuation of a robotic arm. This arm is engineered to maneuver between plant rows, utilizing rotating blades for efficient weed cutting. A comprehensive experimental procedure was conducted, comprising 54 trials within the greenhouse setting, to optimize the performance of the robotic arm. Key variables investigated included arm motor (AM) speed, blade rotation (BR) speed, and blade design. The research tested three BR speeds—3500, 2500, and 1500 RPM—determined based on prior literature concerning rotary movers. Furthermore, two AM speeds (10 and 30 RPM) paired with three distinct blade designs—S-shaped, triangular, and circular—were evaluated primarily for their cost-efficiency and performance based on initial testing outcomes. Results revealed a significant correlation between motor speed and weed cutting efficiency, showing that higher motor speeds correlated with a decreased percentage of cut weeds. Consequently, the 10 RPM motor speed was identified as the optimal setting for arm movement, balancing effective weed removal with operational efficiency.

Industrial pipeline vibration attenuation with magnetorheological tuned mass damper

In order to solve the high-frequency vibration problem of industrial pipeline in petrochemical enterprises, a tuned mass damper (TMD) based on magnetorheological (MR) technology was proposed. The magnetorheological-tuned mass damper (MR-TMD) can reduce the vibration response of the structure by tuning resonance with the pipeline system, it can also have the semi-active control characteristics of MR devices. By analyzing the vibration signals collected on the pipeline site, the relevant design requirements and parameters of the damper were determined. The optimal frequency ratio, passive damping, and mass ratio of the damper were determined using the optimal design theory. Meanwhile, the high-performance MR composite was prepared for the working conditions of MR-TMD and a modified Herschle-Bulkley model was derived to characterize the behavior of the material. Furthermore, the mechanical performance of the proposed MR-TMD was tested, the output damping force is about 890.5 N when the applied current is 2 A, which can meet the working requirements of pipeline vibration attenuation. Then, according to the established vibration control model of pipeline system, the vibration system was simulated and analyzed combined with LQR algorithm, and the vibration attenuation performance in different conditions were predicted and compared. The research shows that the TMD combined with MR technology can effectively reduce the vibration of industrial pipeline system.

Dual Horn MIMO antenna using SIW technology for mmWave high speed vehicular communication

Abstract The current research investigation proposes solutions for the high speed,
high data rate, reliability and high penetration losses using substrate-integrated waveguide
(SIW) optimized horn antenna technology. A dual horn MIMO antenna with the
cavity holes is designed using multilayer substrates Rogers/Duroid 5880 and Rogers
RO3003 of size 56.31×35.06×1.54 mm3 and it provides wide band frequency range of
26.63 - 35.30 GHz. The critical design parameters and their impact are also included
here. The gain and radiation efficiency in the band are 6.94 - 8.93 dBi and 96.1 %-98%
respectively. The proposed H-plane dual horn MIMO antenna is able to receive signals
in all directions in this research. The ECC is 0-0.002 and the TARC is 8.69 GHz in
the band. The CCL in the band is less than 0.5 as per ITU. The impact of MEG using
isotropic and Gaussian environments and multipath propagation w.r.t.NLOS are also
carried out in this research.

FREE VIBRATION ANALYSIS IN INNOVATIVE 3D PRINTING SANDWICH PANAELS FOR AIRCRAFT STRUCTURE

Sandwich panel structures are composed of three layers: core and two facings. The configuration of the core deeply influences the mechanical properties of the sandwich panel. Numerous innovative core shapes have been proposed to enhance these properties; however, many have not been implemented due to manufacturing difficulties, particularly spherical shapes. This research aims to address this manufacturing challenge by utilizing 3D printing technology to produce sandwich panels with a spherical core. Additionally, the study investigates the effects of varying design parameters like sphere diameter, offset distance and face thickness on the free vibration features of the sandwich panels experimentally and numerically. Experimental tests validated the finite element models with an error margin below 12%. The key parameters explored were spherical diameter (3-12mm), offset distance (10-33mm), and face thickness (1-5mm). The results demonstrate a direct correlation between these parameters and the sandwich beam natural frequency.

Thick Hydrogel Membrane With Macro‐Channel for Rapid Uranium Extraction From Seawater

AbstractThe growing demand for uranium driven by nuclear power development necessitates the creation of macroscale, cost‐effective, and efficient adsorbents for uranium extraction from seawater, a challenge yet to be fully addressed. Amidoxime‐based hydrogel adsorbents are promising candidates but suffer from performance limitations due to bound water obstructing pore channels and impeding uranyl ion migration. Herein, a thick macro‐channel poly(amidoxime)‐polyvinyl alcohol hydrogel membrane (MCHM) with a double cross‐linking structure is introduced, designed to enhance uranium adsorption. Unlike traditional powders and microfibers, the macroscale thick membrane facilitates deployment and recovery in marine environments, while its directional channel structure improves mass transfer properties and accessibility to amidoxime groups. Using COMSOL Multiphysics, design parameters such as channel size, membrane thickness, and arrangement are optimized, significantly enhancing performance while reducing costs. In natural seawater, the optimized MCHM with 2.0 mm channels, 20 times thicker than ultra‐thin hydrogel membranes demonstrated improvements of 99% in adsorption capacity and 179% in adsorption rate compared to non‐channel counterparts. This method uniquely combines material innovation with computational modeling, providing valuable insights into how the internal channel structure of adsorbents influences their performance. The findings provide a scalable design solution for hydrogel adsorbents, enabling sustainable uranium extraction from seawater.

An Investigation of Parameter Dimension Reduction Optimization of PMA-Synrm

The rotor of a permanent magnet-assisted synchronous reluctance (PMA-Synrm) motor mostly adopts the structure of a multi-layer magnetic barrier and multi-layer ferrite, which leads to the design parameters of this kind of motor increase with the increase in the number of magnetic barrier layers. A large number of design parameters are coupled with each other, which makes the optimization design of a permanent magnet-assisted synchronous reluctance motor particularly difficult. In this paper, a 7.5 kW, 1500 rpm permanent magnet-assisted synchronous reluctance motor is taken as the research object, and the optimization design of parameter dimension reduction is studied. The rotor structure of the motor is a combination of five layers of magnetic barrier and five layers of ferrite. By using the parameter dimension reduction method proposed in this paper, the number of parameters involved in the optimization is reduced from 26 to 7, which greatly improves the optimization efficiency of this kind of motor and realizes the comprehensive global optimization design of a permanent magnet-assisted synchronous reluctance motor. This paper provides a reference for the optimization of a permanent magnet-assisted synchronous reluctance motor.

Strength Analysis and Design of a Multi-Bridge V-Shaped Rotor for High-Speed Interior Permanent Magnet Synchronous Motors

High-speed operation is a crucial approach for achieving high power density of drive motors for new energy vehicles. However, mechanical strength of the rotor has become the primary bottleneck in the development of high-speed drive motors. Adopting a multi-bridge structure can effectively enhance the mechanical strength of the V-shaped rotors widely used in interior permanent magnet synchronous motors (IPMSMs). Firstly, based on the equivalent centroid principle, the centrifugal forces generated by the rotor’s pole shoes and permanent magnets are calculated. An improved centrifugal force method is proposed to establish an analytical mechanical model of the multi-bridge V-shaped rotor structure. This method comprehensively considers the force conditions, deformation constraints, and material properties of the magnetic bridges. Additionally, stress concentration is taken into account to ensure the accuracy of the model. The effects of various structural parameters on the maximum mechanical stress and deformation are then analyzed. These parameters include the V-angle, pole shoe angle, and the dimensions of three types of magnetic bridges, namely, the central bridge, air-gap bridge, and middle bridge. Finally, recommendations for selecting structural parameters in the mechanical strength design of multi-bridge V-shaped rotors are summarized. The effectiveness of the proposed rotor structure is verified through finite element method and experiments.

Generalizable Metamaterials Design Techniques Inspire Efficient Mycelial Materials Inverse Design.

Fungal mycelial materials can mimic numerous nonrenewable materials; they are even capable of outperforming certain materials at their own applications. Fungi's versatility makes mock leather, bricks, wood, foam, meats, and many other products possible. That said, there is currently a critical need to develop efficient mycelial materials design techniques. In mycelial materials, and the wider field of biomaterials, design is primarily limited to costly forward techniques. New mycelial materials could be developed faster and cheaper with robust inverse design techniques, which are not currently used within the field. However, computational inverse design techniques will not be tractable unless clear and concrete design parameters are defined for fungi, derived from genotype and bulk phenotype characteristics. Through mycelial materials case studies and a comprehensive review of metamaterials design techniques, we identify three critical needs that must be addressed to implement computational inverse design in mycelial materials. These critical needs are the following: 1) heuristic search/optimization algorithms, 2) efficient mathematical modeling, and 3) dimensionality reduction techniques. Metamaterials researchers already use many of these computational techniques that can be adapted for mycelial materials inverse design. Then, we suggest mycelium-specific parameters as well as how to measure and use them. Ultimately, based on a review of metamaterials research and the current state of mycelial materials design, we synthesize a generalizable inverse design paradigm that can be applied to mycelial materials or related design fields.

Multi-Objective Optimization of a Two-Stage Helical Gearbox with Two Gear Sets in First Stage to Reduce Volume and Enhance Efficiency using the EAMR Technique

This study presents the results of a work employing the Evaluation by an Area-based Method of Ranking (EAMR) methodology to address the Multi-Objective Optimization Problem (MOOP) of a two-stage helical gearbox comprising two gear sets in the initial stage. The objective of this study is to identify the most critical design parameters for minimizing the volume of the gearbox while optimizing its efficiency. In this study, three key design parameters were selected for analysis: the wheel face width coefficients Xba for the first and second stages, as well as the gear ratio of the first stage u1. Furthermore, the EAMR technique was employed to address the Multi-Criteria Decision-Making (MCDM) challenge, with the entropy method used to ascertain the weight criterion for resolving the MOOP. The study's findings offer valuable insights into the optimal values for three primary design parameters, which are essential for the development of a two-stage helical gearbox with two gear sets in the initial stage.

Effects of uncertainty in the design parameters during the design of horizontal gravity oil, gas and water separators

The design of bulk separators for oil, gas, and water vessel-type gravity separators significantly affects the cost of topside and subsea oil- and gas-processing installations. There are often many uncertainties during the design process, such as the separator performance, fluid properties, and variation and evolution of the inlet conditions. The industry employs mechanistic models, empirical correlations, numerical studies using Computational Fluid Dynamics, and extensive and expensive experimental campaigns with separator prototypes. However, owing to time, personnel, and information integration constraints in the design phase, design evaluation, and validation are often limited to performing comprehensive sensitivity studies. This often leads to suboptimal designs and early bottlenecks. This study proposes using stochastic mathematical programming and optimization to include the effects of uncertainties in the design parameters during the separator design process. The proposed solution involves the development of a three-phase horizontal separator design model. The model was implemented using Microsoft Excel Visual Basic for Applications. The study then considered the effects of the uncertainties in the oil, gas, and water flow rates and slug volume on the optimal design using stochastic optimization. Conservative, optimistic, and ultimate design parameters (P10, P50, and P90) were obtained for each scenario. The results of this study provide a method and tool to aid topside design teams while expanding on previous research in the literature regarding separator design.

Optimization of Selected Parameters in Vertical, Horizontal, and Hybrid Surface Flow Constructed Wetland Systems for Improving the Treatment Efficiency of Textile and Sewage Effluents

Constructed wetland systems (CWSs) can offer cost-effective wastewater treatment in developing countries like Pakistan. This study focused on optimizing design and operational parameters of CWSs in horizontal surface flow (HSF), vertical surface flow (VSF), and hybrid mesocosms for treating sewage and textile effluents using local hydrophytes: Lemna minor, Typha latifolia, and Eichhornia crassipes. Pollutants and heavy metals (Cd, Cr, Cu, Pb, Ni, and Zn) were removed under different flow configurations, bedding materials, hydrophyte species, and hydraulic retention times (HRT) to optimize the overall contaminant removal efficiency (RE). Key findings indicated that the hybrid CWS achieved a maximum RE of 63.62% for total suspended solids (TSS) and 57.9% for biochemical oxygen demand (BOD) at an HRT of 3 days, with efficiencies declining at longer retention times. Additionally, the hybrid system showed maximum metal removal, with Cd and Cr RE reaching 75.2% and 70.5%, respectively. The study also highlighted the critical role of hydrophyte species and HRT in optimizing RE. Furthermore, the choice of hydrophyte species significantly influenced pollutant removal, with treatment cells containing mixed hydrophytes achieving the highest removal efficiencies (63.62%), followed by Eichhornia crassipes with high Cd (643.33 mgkg−1) and Cr (1103.72 mgkg−1) uptake. A lower HRT of 3 days resulted in the highest overall removal efficiency of 57.5%, which decreased with longer HRTs (from 6 to 9 days). Optimizing design and operational parameters is crucial for maximizing CWS treatment potential.