In this paper existing STHE will studied in detail and from which size of the **shell** and input and output temperature of fluids held constant as input parameter to size the modified STHE. Unknown parameters (decision variables) can be either dependent or independent variables. Then the whole STHE correlations are defined in terms of independent variables. For different independent variable variations, values of **heat** transfer rate and cost of STHE are different. In a **case** of **optimization** using Microsoft Excel, more influential independent variables on values of **heat** transfer rate and cost will considered in a specified ranges to decrease analysis complexity. But in MATLAB programing all independent variables will be considered. Finally, for each methods one best value will be selected in order to have satisfactory **heat** transfer rate and total cost. Of which, by compression one solution will take as a final modified STHE.

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B.V. Babu, S.A. Munawarb:[6]- in the present **study** for the first time DE, an improved version of genetic algorithms (GAs), has been successfully applied with different strategies for 1,61,280 design configurations using Bell’s method to find the **heat** transfer area. In the application of DE, 9680 combinations of the key parameters are considered. For comparison, GAs are also applied for the same **case** **study** with 1080 combinations of its parameters. For this optimal design problem, it is found that DE, an exceptionally simple evolution strategy, is significantly faster compared to GA and yields the global optimum for a wide range of the key parameters.

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find the **heat** transfer area. In the application of DE, 9680combinations of the key parameters are considered. For comparison, GAs are also applied for the same **case** **study** with 1080 combinations of its parameters. For this optimal design problem, it is found that DE, an exceptionally simple evolution strategy, is significantly faster compared to GA and yields the global optimum for a wide range of the key parameters. This paper demonstrates the first successful application of DE for the optimal design of **shell**-and-**tube** HEs. A generalized procedure has been developed to run the DE algorithm coupled with a function that uses Bell’s method of HED, to find the global minimum HE area. For the **case** **study** taken up, application of all the 10 different working strategies of DE are explored. The performance of DE and GA is compared. From this **study** we conclude that the population-based algorithms such as GAs and DE provide significant improvement in the optimal designs, by achieving the global optimum, compared to the traditional designs. For the given optimal **shell**-and-**tube** HED problem the best population size, using both DE and GA, is about seven times the number of design variables. From ‘more likeliness’ as well as ‘speed’ point of view, DE/best/1/. . . strategy is found to be the best out of the presently available 10 strategies of DE.DE, a simple evolution strategy, is significantly faster compared to GA and it achieves the global minimum over a wide range of its key parameters—indicating the ‘likeliness’ of achieving the true global optimum.DE proves to be a potential source for accurate and faster **optimization**. B. Khalifeh Soltan, M. Saffar-Avval *, E. Damangir There is no precise criterion to determine baffle spacing in the presented procedure for condenser design in the **Heat** **Exchanger** Design Handbook (HEDH

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Abstract: This paper will present an over view on the different types failures occurring in **heat** exchangers and the maintenance procedure adopted for smooth operation of the **heat** **exchanger**. **Heat** **exchanger** is present as a static equipment at Hindustan Organic Chemicals Limited. The operation of this **heat** **exchanger** involves the production of Phenol from TAR COLUMN. The **case** **study** deals with the failure analysis of **heat** **exchanger** in which its design is checked. In HOCL, a **shell** and **tube** **heat** **exchanger** is used in the production line of phenol. Hot oil at 328°C and 10.5 kg/cm2 is passing through the **exchanger** tubes. SS316 material is used in the tubes. 120 tubes at the top of the **heat** **exchanger** fails regularly and hence the plant have to be closed down for at least 2 days on each failure. The failure causes loss of hot oil (therminol) which cost approximately Rs 850 per litre. About 1cm drop in oil level costs about 5 lakhs. In order to overcome this problem, the design of this **heat** **exchanger** is analysed for finding out the reason behind this failure.

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Andre L.H. Costa and Eduardo M. Queiroz [1] presented a paper which deals with **study** about the design **optimization** of **shell**-and-**tube** **heat** exchangers. The formulated problem consists of the minimization of the thermal surface area for a certain service, involving discrete decision variables. Additional constraints represent geometrical features and velocity conditions which must be complied in order to reach a more realistic solution for the process task.

A **heat** **exchanger** is a device built for efficient **heat** transfer from one medium to another. Many a times some issues occurred in the **heat** **exchanger**. Out of which this paper is concerned with the thermo-mechanical issue that is thermal expansion of tubesheet due to high temperature. It is necessary to make a optimize design which is safe, economical and accurate. Due to high temperature and high pressure fluids tubesheet of **heat** **exchanger** expands which results expansion of **shell** which causes deformation of **heat** **exchanger**. To avoid this deformation, analysis of effect of temperature variation and associated stresses in the tubesheet is necessary. **Objective** of this paper is to analyse the temperature variation at the junction of **shell** to tubesheet junction in **shell** and **tube** **heat** **exchanger** and **optimization** of tubesheet thickness.

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In this paper a simplified approach to optimize the design of **Shell** **Tube** **Heat** **Exchanger** [STHE] by flow induced vibration analysis [FVA] is presented. The vibration analysis of STHE helps in achieving optimiza- tion in design by prevention of **tube** failure caused due to flow induced vibration. The main reason for **tube** failure due to flow induced vibration is increased size of STHE. It is found that in **case** of increased size of STHE, the surface area and number of tubes increases, thus the understanding and analysis of vibration be- comes a very difficult task. Again it is found that flow induced vibration analysis is considered as an integral part of mechanical & thermal design of STHE. The detailed design, fabrication, testing and analysis work was carried out at Alfa Laval (India), Ltd., Pune-10.

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Our **study** aims at studying simple un-baffled **heat** **exchanger**, which is more similar to the double pipe **heat** exchangers. Almost no **study** is found for an un-baffled **shell** and **tube** **heat** **exchanger**. Thus general correlations of **heat** transfer and pressure drop for straight pipes can be useful to get an idea of the design. Generally there has been lot of work done on **heat** transfer [7] and pressure drop [8] in **heat** exchangers. Pressure drop in a **heat** **exchanger** can be divided in three parts. Mainly it occurs due to fanning friction along the pipe. In addition to this it also occurs due to geometrical changes in the flow i.e. contraction and expansion at inlet and outlet of **heat** **exchanger** [9]. Handbook of hydraulic resistance pro- vides the correlations for the pressure losses in these three regions separately by introducing the pressure loss coefficients.

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The temperature and pressure levels, as well as differences often impose several problems. The corrosiveness, toxicity and scale forming tendency in addition to thermal properties of substances must be considered. There are also economic considerations, which include factor such as initial cost of the **exchanger**, necessary space, and required life of the unit cases of maintenance.

control algorithm which is delivered by J.Richalet etc. in 1978, and has advanced a lot over the years [8]. The model of DMC control algorithm is based on step response prediction model. Traditional autocorrecting of single step prediction is extended to multiple step prediction. Based on the practical feedback information, repeating **optimization** of the algorithm restrains effectively the algorithm sensitive to parameter change of the model. Based on combining the features of prediction function in DMC with feedback structure of PID, a dynamic matrix control with PID structure (PID-DMC) is derived. Using DMC algorithm it requires the inversion computation of higher dimensional matrix and the computation required for the PID-DMC algorithm complicated than that in traditional DMC algorithm. Traditional feedback control algorithm-PID control is simple in principle, easy to understand and implement in engineering, which is still widely used for controlling temperature of **heat** **exchanger**. Many advanced control algorithm is based on PID control algorithm. **Heat** **exchanger** process is highly nonlinear and time varying function. Using conventional PID control for **heat** **exchanger**, it cannot achieve ideal control effect because of its nonlinear and time varying behavior. In order to solve these problems, the predictive PID controller has derived. Using simplified DMC-PID algorithm for controlling temperature of **shell** and **tube** **heat** **exchanger**. The steady state and transient response of **shell** and **tube** **heat** **exchanger** using simplified DMC-PID control is simulated and compared with Conventional DMC-PID algorithms. It is found that the simplified DMC-PID performs well than the conventional PID, DMC-PID and results are tabulated.

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In present day **shell** and **tube** **heat** **exchanger** is the most common type **heat** **exchanger** widely use in oil refinery and other large chemical process, because it suits high pressure application. Firstly modeling done on CATIA software and the process in solving simulation consists of modeling and meshing the basic geometry of **shell** and **tube** **heat** **exchanger** using CFX package ANSYS 19.2. The **objective** of the project is design of **shell** and **tube** **heat** **exchanger** with series of baffles and **study** the flow and temperature field inside the **shell** using ANSYS software tools. The process in solving simulation consists of modeling and meshing the basic geometry of **shell** and **tube** **heat** **exchanger** using CFD package ANSYS 19.2. The **objective** of the project is design of **shell** and **tube** **heat** **exchanger** with baffle and **study** the flow and temperature field inside the **shell** using ANSYS software tools. The **heat** **exchanger** contains 5 tubes and 600 mm length **shell** diameter 90 mm. The helix angle of baffle will be varied from 90 0 , 30 0 to 45 0 . In simulation will show how the pressure vary in **shell** due to different helix angle and flow rate. The flow pattern in the **shell** side of the **heat** **exchanger** with continuous baffles was forced to be rotational and Baffles Series due to the geometry of the continuous baffles, which results in a significant increase in **heat** transfer coefficient per unit pressure drop in the **heat** **exchanger**.

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(STHX) is the most common type of **heat** **exchanger** broadly used in marine ships, due to its high pressure application. The AC plants fitted on-board Marine ships consist of a Chiller i.e. parallel flow **heat** **exchanger** with single segmental baffles. The make of the Chiller is Alfa Laval Ltd. and that of AC plant is Heinen and Hopman ltd. Kolkata. The **heat** **exchanger** contains 234 tubes and 2692 mm length. The water is cooled by using refrigerant R134a in this chiller. This project mainly deals with modelling the prototype of basic geometry of **shell** and **tube** **heat** **exchanger** using Solidworks and Space claim 2017, meshing using ICEM CFD and simulation run using CFD package ANSYS 17.0. The **objective** of the project is to model the **shell** and **tube** **heat** **exchanger** with single segmental baffles and to achieve the temperature outputs as that factory acceptance trials (FATs) and to **study** the flow and temperature distribution inside the **shell** and **tube** using ANSYS software tools with parallel flow. In CFD analysis we will show how the temperature varies in **shell** due to different mass flow rates. The stream pattern in the **shell** with single segmental baffles was required to be rotational, which outcomes in a significant increase in **heat** transfer coefficient per unit pressure drop in the **heat** **exchanger**. The CFD outcomes will be compared with that of actual readings obtained from marine ship.

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The main purpose of **heat** **exchanger** is the transfer of **heat** from one fluid to another. Among all type of **heat** **exchanger**, **shell** and **tube** **heat** **exchanger** most commonly used. . The performances of **shell** and **tube** **heat** **exchanger** mainly depend on baffle geometry and **tube** geometry. Also fouling consideration and the fluids used in **shell** and **tube** have large effect on **heat** **exchanger** performance. The effect of fouling is considered in **heat** **exchanger** design by including **shell** side **tube** side fouling resistance. The **tube** side fluid should be corrosive and have high fouling resistance. Baffle is one of the major parts of **shell** **tube** **heat** **exchanger**. Baffles are designed to direct **shell** side fluid across the **tube** bundle efficiently as possible. The most common type of baffle is the single segmental baffle which changes the direction of **shell** fluid to archive cross flow. Now a day’s helical baffles and flower baffles are used in **shell** and **tube** **heat** **exchanger** instead of segmental baffles and got better results. There were lots of experiments conducted in baffle plate in order to increase **heat** **exchanger** performance. M.M. Elias[1] experimentally investigated the effect of different nano particle shape on the overall **heat** transfer coefficient and **shell** and **tube** **heat** **exchanger** with different baffle angle (0, 10, 20, 30, 40, and 50). Boehmite alumina used as nano particle. In all shapes cylindrical nano particle show grater over all **heat** transfer coefficient .20° baffle angle show better **heat** transfer than other angles Arjun K.S [2 ] investigated the performance of one **shell** and **tube** **heat** **exchanger** model with helical angle vary from 0 to 40° .They got an effective **heat** transfer hike by the impact of helical angle and helix baffle inclination angle 20°makes the best performance of **shell** and **tube** **heat** **exchanger** .Yonghua you [3] solved a numerical model **shell** and **tube** **heat** **exchanger** with flower baffles for Reynold number ranging from 6813 to 22326.They found that, the mean **heat** transfer coefficient and convective **heat** transfer coefficient increase with increase of Reynolds number. Also they found that over all thermal hydraulic behaviour h sm /Δp decreases with increase of Reynolds number. Xiaoming xiao [4] investigated the **heat** transfer performance of fluid with different prandel number fluid in the **shell** side of helical baffle side of **heat** **exchanger**. The value of ‘pr’ ranges from 5 to 15000 and helical tilt angle from 10° to 50°. High prandel number fluid with small helical angle reveals to be optimum choice. In this **study** **optimization** of **shell** and **tube** **heat** **exchanger** have done for maximum **heat** transfer. **Optimization** mainly on for **tube** arrangement and baffle angle .

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In present day **shell** and **tube** **heat** **exchanger** is the most common type **heat** **exchanger** widely use in oil refinery and other large chemical process, because it suits high pressure application. Firstly modeling done on CATIA software and the process in solving simulation consists of modeling and meshing the basic geometry of **shell** and **tube** **heat** **exchanger** using CFD package ANSYS 14.0. The **objective** of the project is design of **shell** and **tube** **heat** **exchanger** with series of baffles and **study** the flow and temperature field inside the **shell** using ANSYS software tools. The process in solving simulation consists of modeling and meshing the basic geometry of **shell** and **tube** **heat** **exchanger** using CFD package ANSYS 14.0. The **objective** of the project is design of **shell** and **tube** **heat** **exchanger** with baffle and **study** the flow and temperature field inside the **shell** using ANSYS software tools. The **heat** **exchanger** contains 5 tubes and 600 mm length **shell** diameter 90 mm. The helix angle of baffle will be varied from 10 0 to 20 0 . In simulation will show how the pressure vary in **shell** due to different helix angle and flow rate. The flow pattern in the **shell** side of the **heat** **exchanger** with continuous baffles was forced to be rotational and Baffles Series due to the geometry of the continuous baffles, which results in a significant increase in **heat** transfer coefficient per unit pressure drop in the **heat** **exchanger**.

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IV. G ENETIC A LGORITHMS F OR PID C ONTROLLER T UNING Genetic Algorithms (GAs) is a search **optimization** technique based on the mechanism of Darwin’s principle of natural selection. The searching process is similar to that in nature where a biological process in which stronger individual is likely to be winner in a competing environment. GAs must be initialized with set of solutions represented by chromosomes called a population.

In a typical SSHE (Fig.), fluid is slowly pumped along the annulus between a stationary heated or cooled outer cylinder and a rotating inner cylinder. Moving blades attached to the inner cylinder scrape the outer cylinder surface periodically to prevent film formation and promote mixing and **heat** transfer. The blades are often manufactured with holes or gaps to allow mass flow through the scrapers and to reduce the power required for rotation. In comparison with the axial flow, the rotational flow dominates the mixing process. The high shear region close to the tips of the blades and the significant thermal effects due to viscous dissipation imply that it is crucial to understand the local shear and thermal effects in order to predict **heat** transfer performance. [5]

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In this **shell** and **tube** type **heat** **exchanger**, both the fluids flow in opposite directions. The hot and cold fluids(water) enter at the opposite ends. The temperature difference between the two fluids remains more or less nearly constant. This type of **heat** **exchanger**, due to counter flow, gives maximum rate of **heat** transfer for a given surface area. Hence such **heat** exchangers are most favored for heating and cooling of fluids.