Forward Operation Research Articles

Designing a Brushed DC Motor Driver with a Novel Adaptive Learning Algorithm for the Automotive Industry

In this study, a stepper driver, which is suitable for use in the automotive industry, designed for general use, capable of adaptive learning in the systems in which it is used, and with CAN and universal asynchronous receiver–transmitter (UART) communication options, was designed. This design was made with a PIC18F25K22 microcontroller unit (MCU). Rotor speed, armature current, and terminal voltage can be measured on the proposed brushed DC motor drive system. It gives the desired response by evaluating obstacles and other situations in which high currents are drawn from the source. The speed measurement of the vehicle and the open and closed status of an automatic door can be monitored. The main contribution of the designed PCB is an adaptive learning algorithm (ALA) that uses the pulses of the encoder, estimates the position of the step, and manages the operation process to prevent mechanical damage at the final point of the motor. Furthermore, unexpected hitting and pinching which are defined as obstacles to the driver can be controlled by monitoring the current value drawn from the driver. The benefit of this method is that the life of the mechanical step is increased due to the management of the forward and backward step operation, preventing potential accidents.

Carrier Generation and Recombination in AC-QLEDs with a Synergistic Capacitance Effect of ZnO/PVDF Heterofunction Layers.

The alternating current-driven electroluminescence (AC-EL) of Cd-based quantum dots is garnering increasing attention due to advantages such as high efficiency and an extended operating lifetime. However, the generation and transport mechanisms of charge carriers within devices still need to be more understood. Here, we construct a simple device and investigate its luminance mechanisms within a single cycle using time-resolved spectroscopy. We tested the luminance-voltage and luminance-frequency characteristics of the device as the thickness of the insulating layer varied, finding that they both exhibited a trend of initially increasing and then decreasing as the voltage or frequency increased. We subsequently investigated the transient electroluminescent characteristics of the device, which featured a P(VDF-TrFE-CFE) layer as the insulator. This layer prevents carrier injection from the Al electrode, while the ZnO layer acts as a charge-generating layer to provide additional carriers. We observed that with an increase in AC voltage, the strongest luminance peak is advanced in the cycle compared to when lower voltages were applied. The position of the strongest luminance peak is delayed with an increasing AC frequency. The C-V characteristics demonstrated that the synergistic P(VDF-TrFE-CFE)/ZnO exhibited a displacement current transforming to a conduct current, which activates the forward operation of the QLED and enables it to emit light. The mechanism we present may serve as a benchmark for improving the luminance and longevity of such devices.

Galformer: a transformer with generative decoding and a hybrid loss function for multi-step stock market index prediction

The prediction of stock market fluctuations is crucial for decision-making in various financial fields. Deep learning algorithms have demonstrated outstanding performance in stock market index prediction. Recent research has also highlighted the potential of the Transformer model in enhancing prediction accuracy. However, the Transformer faces challenges in multi-step stock market forecasting, including limitations in inference speed for long sequence prediction and the inadequacy of traditional loss functions to capture the characteristics of noisy, nonlinear stock history data. To address these issues, we introduce an innovative transformer-based model with generative decoding and a hybrid loss function, named “Galformer,” tailored for the multi-step prediction of stock market indices. Galformer possesses two distinctive characteristics: (1) a novel generative style decoder that predicts long time-series sequences in a single forward operation, significantly boosting the speed of predicting long sequences; (2) a novel loss function that combines quantitative error and trend accuracy of the predicted results, providing feedback and optimizing the transformer-based model. Experimental results on four typical stock market indices, namely the CSI 300 Index, S&P 500 Index, Dow Jones Industrial Average Index (DJI), and Nasdaq Composite Index (IXIC), affirm that Galformer outperforms other classical methods, effectively optimizing the Transformer model for stock market prediction.

Study on the dynamic characteristics of the head cover-bolts-stay ring of a variable-speed pump-turbine

Abstract The design and operation of variable-speed pump-turbine units is more difficult than that of conventional units due to their adjustable speed, frequent start stop, and forward and reverse operation. Due to the development of variable-speed pump-turbines towards variable-speed, high head, and large capacity, the vibration instability caused by frequent switching between turbine and pump operating conditions is more prominent. The study on the dynamic characteristics of the head cover-bolts-stay ring system is an important guarantee for the long-term safe and stable operation of the units. This article uses the finite element method to conduct modal analysis on the head cover-bolts-stay ring system of a variable-speed pump-turbine. The natural frequency and mode shape are analyzed, and resonance analysis is carried out in combination with the dynamic and static interference characteristics of the variable-speed unit. The research results show that the dynamic and static interference frequency of the unit during the variable-speed process may be close to the natural frequency of the head cover-bolts-stay ring system, which needs to be paid attention to during operation. The results and findings in this article provide theory and practical basis for the research and design of high head, large capacity, and variable-speed pump-turbine units.

Rethinking Pan-Sharpening in Closed-Loop Regularization.

It is generally known that pan-sharpening is fundamentally a PAN-guided multispectral (MS) image super-resolution problem that involves learning the nonlinear mapping from low-resolution (LR) to high-resolution (HR) MS images. Since an infinite number of HR-MS images can be downsampled to produce the same corresponding LR-MS image, learning the mapping from LR-MS to HR-MS image is typically ill-posed and the space of the possible pan-sharpening functions can be extremely large, making it difficult to estimate the optimal mapping solution. To address the above issue, we propose a closed-loop scheme that learns the two opposite mapping including the pan-sharpening and its corresponding degradation process simultaneously to regularize the solution space in a single pipeline. More specifically, an invertible neural network (INN) is introduced to perform a bidirectional closed-loop: the forward operation for LR-MS pan-sharpening and the backward operation for learning the corresponding HR-MS image degradation process. In addition, given the vital importance of high-frequency textures for the Pan-sharpened MS images, we further strengthen the INN by designing a specified multiscale high-frequency texture extraction module. Extensive experimental results demonstrate that the proposed algorithm performs favorably against state-of-the-art methods qualitatively and quantitatively with fewer parameters. Ablation studies also verify the effectiveness of the closed-loop mechanism in pan-sharpening. The source code is made publicly available at https://github.com/manman1995/pan-sharpening-Team-zhouman/.

Analysis of the influence of different support types on the operation performance of bidirectional shaft tubular pump

Abstract Because of the particularity of the pump’s bidirectional operation, and the difference of the flow channels on both sides of the pump. The device has a mature impeller and guide vane combination when it is running forward. And when the device runs in reverse, the support on the shaft side acts as the rear guide vane of the impeller, which has great influence on the performance of the device. However, due to the few operating conditions in reverse operation, the importance of support is often ignored. In this paper, the influence of different support types on the bidirectional flow pattern and performance of the device is analyzed by numerical simulation. The results indicate that by optimizing the variation trend of the edge arc radius of the supporting baffle section, it is possible to effectively control the section with poor flow distribution, thereby reducing hydraulic losses. The support adopts three partitions arranged at an interval of 120°, which has little difference in performance during forward operation compared with other schemes. But during reverse operation, it reduces the impact and friction losses of water flow. And it fully utilizes the direct guide vane function of recovering vorticity, resulting in a significant increase in efficiency. At the same time, the accuracy of numerical simulation results is verified by model tests. The stability of positive and negative operating pressure pulsation supporting the inlet and outlet under the optimal scheme is analyzed.

Fouling-resistant Na-ZSM-5 zeolite membrane for fruit juice concentration in forward osmosis process

To evaluate the potential of Na-ZSM-5 membrane for liquid food concentration, the concentration of fruit juice by a tubular Na-ZSM-5 membrane was demonstrated in forward osmosis operation. Apple, orange, and pineapple juices were successfully concentrated, maintaining their quality without contamination by a draw solution based on a molecular sieving effect of the zeolite membrane. For example, the sugar content of apple juice increased from 10.7 to 17.1 oBrix after 24 h of dehydration. The fouling resistance of Na-ZSM-5 membrane was evaluated using a 10 g L-1 pectin solution and cellulose suspension. Na-ZSM-5 membrane showed stable dehydration performance for fruit juice concentration over 120 h without fouling due to pectin or cellulose. In addition, the membrane exhibited high heat resistance, with no deterioration up to 353 K. We showed that Na-ZSM-5 membrane is a potential material for fruit juice concentration because of its superior heat, acidity, and fouling resistances.

Efficient magnetic forward modeling for strongly magnetized bodies: An iterative integral equation approach

Magnetic surveying encounters challenges in high-precision detection and inversion on strongly magnetized bodies. Nonuniform magnetization caused by self-demagnetization and mutual magnetization makes magnetic field calculation using analytical formulas impractical. The previous discrete numerical methods have suffered from computational inefficiency or low accuracy. To resolve this issue, we develop an algorithm to solve the magnetic field integral equation for calculating the magnetization state of high-susceptibility bodies, combining the improved spatial convolution forward approach with the adaptive relaxation iteration method. To address the excessive computational burden in the magnetization field between 3D voxel arrays of the discrete model, we construct the circular convolution kernel matrix directly when the subsurface space is divided with an equidistant grid, significantly reducing redundant computations. Then, the fast Fourier transform is used to accelerate the forward discrete circular convolution operation. In addition, we derive an iterative computation scheme that adaptively adjusts the relaxation factor based on magnetic field changes to correct the effective magnetization for algorithm convergence. From a pragmatic perspective, equating the cuboid to equal-volume sphere subdivisions is developed to enhance computational efficiency further by approximately 50% despite sacrificing slight accuracy. The sphere and spherical shell models validate the algorithm accuracy, efficiency, and convergence. Furthermore, we analyze the characteristics of the mutual magnetization effect among magnetic bodies under different magnetization conditions. Finally, the applicability of the algorithm is demonstrated with a realistic example. Our algorithm shows promise for precisely exploring highly magnetized minerals, underground pipelines, and unexploded ordnance.

Multimodal soft valve enables physical responsiveness for preemptive resilience of soft robots.

Resilience is crucial for the self-preservation of biological systems: Humans recover from wounds thanks to an immune system that autonomously enacts a multistage response to promote healing. Similar passive mechanisms can enable pneumatic soft robots to overcome common faults such as bursts originating from punctures or overpressurization. Recent technological advancements, ranging from fault-tolerant controllers for robot reconfigurability to self-healing materials, have paved the way for robot resilience. However, these techniques require powerful processors and large datasets or external hardware. How to extend the operational life span of damaged soft robots with minimal computational and physical resources remains unclear. In this study, we demonstrated a multimodal pneumatic soft valve capable of passive resilient reactions, triggered by faults, to prevent or isolate damage in soft robots. In its forward operation mode, the valve, requiring a single supply pressure, isolated punctured soft inflatable elements from the rest of the soft robot in as fast as 21 milliseconds. In its reverse operation mode, the valve can passively protect robots against overpressurization caused by external disturbances, avoiding plastic deformations and bursts. Furthermore, the two modes combined enabled the creation of an endogenously controlled valve capable of autonomous burst isolation. We demonstrated the passive and quick response and the possibility of monolithic integration of the soft valve in grippers and crawling robots. The approach proposed in this study provides a distributed small-footprint alternative to controller-based resilience and is expected to help soft robots achieve uninterrupted long-lasting operation.

Power-enhanced residual network for function approximation and physics-informed inverse problems

In this study, we investigate how the updating of weights during forward operation and the computation of gradients during backpropagation impact the optimization process, training procedure, and overall performance of the neural network, particularly the multi-layer perceptrons (MLPs). This paper introduces a novel neural network structure called the Power-Enhancing residual network, inspired by highway network and residual network, designed to improve the network's capabilities for both smooth and non-smooth functions approximation in 2D and 3D settings. By incorporating power terms into residual elements, the architecture enhances the stability of weight updating, thereby facilitating better convergence and accuracy. The study explores network depth, width, and optimization methods, showing the architecture's adaptability and performance advantages. Consistently, the results emphasize the exceptional accuracy of the proposed Power-Enhancing residual network, particularly for non-smooth functions. Real-world examples also confirm its superiority over plain neural network in terms of accuracy, convergence, and efficiency. Moreover, the proposed architecture is also applied to solving the inverse Burgers' equation, demonstrating superior performance. In conclusion, the Power-Enhancing residual network offers a versatile solution that significantly enhances neural network capabilities by emphasizing the importance of stable weight updates for effective training in deep neural networks. The codes implemented are available at: https://github.com/CMMAi/ResNet_for_PINN.

Multiphase BHB-CLL Resonant Converter Based on Secondary-Side VDR With Automatic Current Sharing Characteristic

A multiphase bidirectional half-bridge (BHB) CLL resonant converter with automatic current sharing characteristics is proposed in this paper for high-power bidirectional energy storage applications. The CLL converter is obtained by placing the resonant inductor in the voltage doubling rectifier (VDR). Compared with LLC resonant converter, the circulating current related to the magnetizing current of the transformer is removed from the resonant inductor. Without extra components and control schemes, the excellent current sharing performance can be achieved only by connecting two wires in the two-phase resonant tanks even when the resonant parameters have 10% tolerance. The current sharing performance of the proposed converter is analyzed by FHA method, and a 1200W experimental prototype is built to verify the superiority of the proposed converter. Under the full load condition, the measured peak efficiency in forward and backward operation mode is 97.99% and 97.8%, the output current sharing error is 0.51% and 4.0%, respectively.

Determination of the critical draw solution concentration for anaerobic microfiltration osmotic membrane bioreactors

Anaerobic microfiltration osmotic membrane bioreactors (AnMF-OMBRs) have the advantages of resource recovery such as energy, water, and nutrients, but they have some drawbacks of low flux and severe membrane fouling. The concentration of draw solution (DS) is effective on the flux and fouling of FO membrane, and microbial inhibition. The aim of this study is to determine the critical DS concentration in AnMF-OMBR and up-flow anaerobic sludge blanket microfiltration osmotic membrane bioreactor (UASB MF-OMBR) systems operated with DS concentrations of 0.47, 1, and 1.5 M. The analytical hierarchical process (AHP) was applied to determine the critical DS concentration considering the criteria of forward osmosis (FO) performance, anaerobic performance, water recovery, microbial inhibition and operation time. The results demonstrated that the DS concentration of 0.47 M showed a better system performance, by causing less membrane fouling and microbial inhibition than that of the 1 and 1.5 M, and higher methane yield was obtained with 0.47 M in both bioreactors. The membrane autopsy analyses verified that the membrane fouling was severe with increasing DS concentration. Microbial community structure was affected by salinity build-up, high free ammonia (FA), and low organic loading rate (OLR). The relative abundance of Synergistota, a syntrophic acetate oxidizer, showed a parallel trend with Methanobacterium, a hydrogenotrophic methanogen in the conditions of high FA and salinity build-up due to the FO operation. Consequently, the critical DS concentration was determined as 0.47 M MgCl2.

IGBT Based Four Quadrant Chopper Drive Closed Loop Control for DC

These manuscripts present a closed-loop IGBT-based fourquadrant chopper drive system for DC motors. This paper intends to improve DC motor control’s accuracy, effectiveness, and adaptability in a variety of applications. In this paper, we build and put into practice a closed-loop control system that incorporates IGBT in order to manage the speed and torque of DC motors in both directions. A feedback system with sensors for measuring motor speed and current is used in the closed-loop control scheme to ensure perfect regulation of motor parameters. The IGBT-based chopper drive architecture allows for smooth switching between forward and reverse motor operation as well as dynamic braking, making it appropriate for applications requiring four-quadrant operation. The main benefits of our suggested system are greater motor protection through fault detection and quick responses to external disturbances, improved speed and torque management, and lower energy consumption. We show experimental data that demonstrate our design’s capacity to maintain stable motor functioning across a variety of operating situations, validating its usefulness in real-world applications. The presented system simulation result is verified in MATLAB/Simulink software. The demonstrated results are motor speed, torque, current and voltage.

Numerical Analysis of Unsteady Internal Flow Characteristics in a Bidirectional Axial Flow Pump

A bidirectional axial flow pump that utilizes an S-shaped hydrofoil design exhibits low efficiency and hydraulic instability when operated in reverse. In order to understand the unsteady flow characteristics of this bidirectional axial pump under different operating conditions, the SST k–ω turbulence model was applied to carry out a three-dimensional unsteady numerical simulation of the full flow channel of the pump. The reliability of the numerical calculation model was verified by comparing it with the experimental head and efficiency. The pressure pulsation characteristics on the impeller surface and the pump device under different operating conditions and the transient forces on the impeller were analyzed. The results show that the head and efficiency in reverse operation were lower than in forward operation and the flow streamline of the impeller outlet area was more turbulent in the reverse operation condition. The monitoring points at the inlet and the top of the impeller surface showed the largest pressure pulsation amplitude. The radial and axial forces on the impeller in the reverse operation were greater than those in the forward operation. Under a reverse 1.0 Qdes condition, the average pressure pulsation amplitudes at the inlet of the impeller were 19.2 times and 5.7 times of that at the inlet of the guide vane and the outlet of the impeller, respectively. This study provides a reference for the hydraulic design and optimization of bidirectional axial flow pumps.

Vehicle Trajectory Prediction Based on Graph Convolutional Networks in Connected Vehicle Environment

Vehicle trajectory prediction is an important research basis for the decision making and path planning of the intelligent and connected vehicle. In the connected vehicle environment, vehicles share information and drive cooperatively, and the intelligent and connected vehicles are able to obtain more accurate and rich perception information, which provides a data basis for accurate prediction of vehicle trajectories. However, attaining accurate and effective vehicle trajectory predictions poses technical challenges due to insufficient extraction of vehicular spatial–temporal interaction features. In this paper, we propose a vehicle trajectory prediction model based on graph convolutional neural network (GCN) in a connected vehicle environment. Specifically, using the driving scene information obtained by the intelligent and connected vehicle, the spatial graph and temporal graph are constructed based on the spatial interaction coefficient (SIC) and self-attention mechanism, respectively. Then, the graph data are entered into the interaction extraction module, and the spatial interaction features and temporal interaction features are extracted separately using the graph convolutional networks, which are fused to obtain the spatial–temporal interaction information. Finally, the interaction features are learned based on the convolutional neural networks to output the future trajectory information of all vehicles in the scene by one forward operation rather than a step-by-step process. The ablation experiment results show that the method proposed in this study to model the spatiotemporal interaction among vehicles based on SIC and self-attention mechanism reduces the prediction error by 5% and 12%, respectively. The results from the model comparison experiment show that the proposed method engenders an 8% improvement in prediction accuracy over the state-of-the-art solution, providing technical and theoretical support for trajectory prediction research of intelligent and connected vehicles.

The Nigerian Military Operation Safe Haven (OPSH) Operation in Internal Security Management in Plateau State: Challenges and Prospects

This study investigated the Nigerian Military Operation Safe Haven (OPSH) in the internal security management in Plateau state, Nigeria from 2010 to 2021. Primary data utilised for this study include a structured set of questionnaires and a key informant interview. The sampling technique adopted for the study was the purposive sampling method, hence only those with adequate knowledge of the subject matter were interviewed. Three senatorial zones were purposively selected for detailed investigation and generalisation. These include the South senatorial zone, Central senatorial zone and North senatorial zone. Also, the Headquarters (HQs) OPSH, Sectors and Forward Operation Basaa (FOBs) were selected in each senatorial zone for detailed investigation and these include; Wase FOB, Shendam FOB (South senatorial Zone), Barkin Ladi (Sector 4), Bassa (Sector 3) (North senatorial zone) and Bokkos (sector 5), Mangu (FOB) (Central senatorial zone). 400 copies of structured questionnaires were administered but 395 copies were retrieved and were used for analysis using SPSS. Analysis of data were both quantitative and qualitative. Findings from the study revealed that the State is bedevilled with new dimension of security threats which were not experienced in the past such as banditry, armed robbery, selective killings, kidnappings, farmers-herders clashes and raiding of towns and villages. Findings from the study also revealed that the Nigerian Military OPSH is responsive to the current security threats bedevilling the State. The study also revealed that the Nigerian military OPSH is faced with lots of challenges such as lack of manpower, logistics and modern equipment to ease their operations. The study recommended that the Nigerian Military OPSH should secure modern day equipment in order to withstand the challenges of modern security threats confronting Plateau State.

Research on Cavitation Performance of Bidirectional Integrated Pump Gate

A pump gate is a device that controls the flow of water. It can stop the flood when it comes, drain the ponding gathered in the city, and improve the water circulation of the city. Traditional pumping stations require a large land area, and their pump houses and gates need to be designed separately. Furthermore, the construction period of traditional pumping stations is lengthy, and the maintenance costs are high. It can no longer meet the needs of modern cities for water environment management. Therefore, it is imperative to design a new type of pump gate. The integrated pump gate introduced in this paper is an integrated construction of gates and pumps to achieve automatic control and bidirectional operation. The research mainly consists of three parts: design of pumping station, theoretical analysis, and numerical calculation. By studying the unstable flow inside the integrated pump, the characteristics and the degree of cavitation occurrence are predicted. This can provide a reference basis for the optimal design and stability operation of the integrated pump gate. To investigate cavitation in an integrated pump gate, numerical simulations were performed for multiple operating conditions using the SST turbulence model. Constant numerical simulations of cavitation through numerical calculation, the characteristic curves of the integrated pump gate under forward and reverse operation at different flow points were obtained, and flow field analysis was performed for the model pump at 1.0 Q. The location and degree of cavitation occurrence were predicted. In this study, a preliminary analysis was conducted to investigate the influence of cavitation on the internal flow characteristics of integrated gate pumps. The research collected data related to cavitation characteristics, streamline patterns, and blade pressures. Additionally, the study explored the characteristics of cavitation phenomena, laying the foundation for the optimization of the design of bidirectional operation in integrated sluice gate pumps for future practical engineering applications.

Reduction of Concentrating Poisonous Metallic Radicals from Industrial Wastewater by Forward and Reverse Osmosis

The research aims to use a new technology for industrial water concentrating that contains poisonous metals and recovery quantities from pure water. Therefore, the technology investigated is the forward osmosis process (FO). It is a new process that use membranes available commercial and this process distinguishes by its low cost compared to other process. Sodium chloride (NaCl) was used as draw solution to extract water from poisonous metals solution. The driving force in the FO process is provided by a different in osmotic pressure (concentration) across the membrane between the draw and poisonous metals solution sides. Experimental work was divided into three parts. The first part includes operating the forward osmosis process using TFC membrane as flat sheet for NaCl. The operating parameters studied were: draw solutions concentration (10 – 95 g/l), draw solution flow rate (12-36 I/h), temperature of draw solution (30 and 40°C), feed solution concentration (10 -210 mg/l), feed solution flow rate (10 -50 l/h), temperature of feed solution (30 and 40°C) and Pressure (0.4 bar). The second part includes operating the forward osmosis process using CTA membrane as flat sheet for NaCl. The operating parameters studied were: draw solution concentration (15 – 95 g/l), feed solution concentration (10-210 mg/l). Constant temperature was maintained at 30°C. The last part includes operating the reverse osmosis process using TFC membrane as spiral wound module in order to separate NaCl salt from draw solution and obtain on pure water so as to usefully in different uses and also obtain on solution of NaCl concentrate which was recirculated to forward osmosis process. It is then used as draw solution. The operating parameter studied was: feed solution flow rate (15-55 l/h). The experimental results show that the water flux increases with increasing draw solution concentration, feed solution flow rate, temperature of draw solution and decreases with increasing feed solution concentration, draw solution flow rate and temperature of feed solution. The experiments also show that CTA membrane gives higher water flux than TFC membrane for forward osmosis operation.

Novel Y-function based strategy for parameter extraction in S/D asymmetric architecture devices and low frequency noise characterization in GAA Si VNW pMOSFETs

In this work, DC and low frequency noise measurements are performed in p-channel gate-all-around (GAA) silicon vertical nanowire (Si VNW) MOSFETs. The DC measurements highlight asymmetry in the drain current and transconductance transfer characteristic even in linear operation, at an applied drain voltage of −50 mV. A novel Y-function based strategy for parameter extraction in S/D asymmetric devices is proposed. This novel strategy allows the estimation of the value of each access resistance, from source and from drain sides, respectively, and allows overcoming the device asymmetry to provide an accurate extraction of the main DC parameters. The low-frequency noise studies on forward and reverse operation mode, demonstrate that the 1/f noise in both modes can be explained by the correlated carrier number (Δn) and mobility fluctuation (Δμ) mechanisms, with additional contribution of the access resistance noise in strong inversion.

Forward Osmosis Process for the Treatment of Wastewater from Textile Industries

This paper was aimed to study the efficiency of forward osmosis (FO) process as a new application for the treatment of wastewater from textile effluent and the factors affecting the performance of forward osmosis process.The draw solutions used were magnesium chloride (MgCl2), and aluminum sulphate (Al2 ( SO4)3 .18 H2O), and the feed solutions used were reactive red, and disperse blue dyes.Experimental work were includes operating the forward osmosis process using thin film composite (TFC) membrane as flat sheet for different draw solutions and feed solutions. The operating parameters studied were : draw solutions concentration (10 – 90 g/l), feed solutions concentration (5 – 30 mg/l), draw solutions flow rate (10 – 50 l/hr), feed solutions flow rate (20-60 l/hr), constant pressure and temperature were maintained at 0.5 bar and 30ºC respectively. And includes operating the forward osmosis process using cellulose triacetate (CTA) membrane as flat sheet for different draw solutions and feed solutions. The operating parameters studied were : draw solutions concentration (10 – 90 g/l), and feed solutions concentration (5 – 30 mg/l), constant temperature at 30ºC. It was found that water flux increases with increasing draw solution concentration, and feed solution flow rate and decreases with increasing draw solution flow rate and feed solution concentration for TFC and CTA. It was found MgCl2 given water flux larger than Alum. And also found that reactive red given water flux larger than disperse blue.The experiments also show that CTA membrane gives higher water flux than TFC membrane for forward osmosis operation. The increase in water flux for CTA is about 12.85% than TFC.