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3D CFD based optimization technique for muffler design of a motorcycle
(Department of Mechanical and Production Engineering, Islamic University of Technology, Gazipur, Bangladesh, 2015-11-15) Shadman, Sakib; Abir, Oneeruddho Hussain
In order to minimize the sound transmission due to exhaust gases, the most common and important part of the engine system is muffler. A back pressure on engine is always produced due to the use of the exhaust muffler. This back pressure represents the extra static pressure exerted by the muffler on the engine through the restriction in flow of exhaust gases. The back pressure mainly depends on the internal shape and overall design of the exhaust muffler. Design of muffler is a complex function that affects noise characteristics, emission and fuel efficiency of engine. In this study, a combined model of response surface methodology (RSM) and desirability analysis is used for optimizing the back pressure of a motorcycle reactive muffler, in order to improve the performance of the muffler. For this optimization process, the design variable parameters are size of perforation, number of perforation and partition chamber size. To measure the back pressure 3D CFD based CAE software has been used. Prediction of acoustics transmission loss virtually is an important analysis required for the development of muffler at an initial design stage. For this reason, for the optimized design virtual acoustics transmission loss analysis is conducted. It is found that after optimizing the design of the muffler, the back pressure is decreased and the acoustic transmission loss is increased that can ensure the improvement of the muffler efficiency.
3D Indoor Depth Mapping Using SIFT Feature Based ICP Registration
(Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Bangladesh, 2015-11-15) Sakib, Nazmus; Farayez, Araf
3D mapping is one of the challenging research areas of Computer Vision and Robotics. Mappings are often done with mobile robots. One of the best approach is the use of SLAM (Simultaneous Localization and Mapping) where a robot roams around and builds the map and also localizes its position on the currently built map. The robot needs the sense of depth of the environment and often equipped with depth sensor. It also needs Odometry data from the accelerometer or encoder set on the wheels. There are some other solutions where the map and localization is based on the features extracted and builds the map based on the depth images and use of loop closure by adjusting the error in perception. In this thesis work we used feature based mapping which does not need any Odometry data and the map can be built based on RGB image and Depth data. We used Kinect, a very popular depth sensor which is effective in this process under certain constraints. Here in our work we gathered the RGB and Depth data simultaneously and then chose suitable frames and found key features with SIFT algorithm. The extracted features in the RGB images has corresponding 3D co-ordinates. The 3d co-ordinates have been found through intensive experiments done on calibrating the Kinect sensor and finding the best fit value of parameters to give more accurate 2D spatial points corresponding to each frame captured. The matched 3D points were then applied in Iterative closest Point (ICP) algorithm as initial points to merge the two depth images. When two images are merged they were saved in separated storages and another frame is extracted and registered with the previous ones. In this methodology multiple frames were stitched in 3D spatial co-ordinates. After forming the indoor map the map was evaluated with respect to the lengths of the objects formed in the map and the shape of the map along different 2D planes by comparing their area. Different version of ICP give different result in time complexity and accuracy. It was found IRLS (Iteratively Reweighted Least Square) ICP gave better results. The methodology we proposed can be implemented at faster time and fewer constraints and mapping do not depend on the movement noise of the robot. So the whole process is simpler and robust and can be used in indoor mapping, object detection and security purposes.
3d Numerical Analysis of The Effect of Various Geometric Parameters of Eathes Under Steady Operating Conditions
(Department of Mechanical and Production Engineering, Islamic University of Technology, Board Bazar, Gazipur, Bangladesh, 2018-11-15) Hero, Md. Kabbir Hossain; Moin, Md. Emran Hossain
Space heating and cooling is a comfort requirement which results in a significant amount of energy consumption. EATHE (Earth Air Thermal Heat Exchanger) is one of the passive ways of space heating and cooling that can reduce the energy consumption notably. In this paper, the effect of different geometric parameters; cross section of the pipe, inclusion of fins on the pipe, pitch of multiple pipe arrangements on the thermal performance of EATHEs under steady and transient conditions were analyzed. Since, the performance deteriorates over the continuous operation of the EATHEs, their performance under periodic operations were studied. A validated three- dimensional, transient numerical model was used to carry out the analysis. The governing equations, based on the k–Ɛ model and energy equation were used to describe the turbulence and heat transfer phenomena. The results are compared in terms of the outlet temperature of air and heat transfer rate.
3d Numerical Investigation of Flow and Heat Transfer Characteristics in Smooth Wavy Fin and Elliptical Tube Heat Exchangers Using ARW Vortex Generator
(Department of Mechanical and Production Engineering (MPE),Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh, 2017-11-15) Sabbir, Shah Mohammad; Chowdhury, Sadat Hasan
3D computational analysis was performed to investigate heat transfer and pressure drop characteristics of flow in SWFET (Smooth Wavy Fin-and-Elliptical Tube) heat exchanger with VGs (vortex generators). The numerical model was well validated with the available experimental results. Numerical results illustrate that adding vortex generators and changing the shape of tube can bring about further heat transfer enhancement. Through careful adjustment of the position with respect to the elliptical tube, type and attack angle of vortex generators. Numerical study shows that adding vortex generator and elliptical shape of tube enhances heat transfer characteristics.
3D Object Detection with Stereo Vision and Transformer
(Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh, 2022-05-30) Samin, Abid Ahsan; Hassan, Abdullah; Khan, Md. Rakib Hossain
Identifying 3D objects with computer vision in a precise manner has been a challenging task in the field of autonomous driving. Partly because it requires proper depth estimation. Until now, Li-DAR technology has been used to achieve this task which is precise but also expensive. The introduction of pseudo Li-DAR promises an alternative approach which is cheaper with fairly good precision. However, pseudo Li-DAR can be replaced with 2D image representation with similar precision. Transformer is another technology which is widely used to process sequential data. Recent studies show that transformer can also be used for object detection purposes. In this literature, we look into the concept of pseudo Li-DAR, image representation of depth and detection transformer(DETR). Later, we introduce a new approach of using image based depth output with DETR to achieve accurate object detection. Finally, we compare our results with other available methods used for object detection in order to establish a benchmark.
4G Data Analysis and Downlink Throughput Predictive Modelling Around The Geographic Region of Gazipur and Dhaka
(Department of Electrical and Elecrtonics Engineering(EEE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-06-22) Chowdhury, Shafi Muhtasim; Islam, Safwan; Islam, Rafrafin
This project presents a comprehensive study on optimizing 4G data analysis and downlink throughput modelling, integrating technical rigor with societal considerations. As 4G networks continue to serve as a backbone for modern telecommunications, enhancing their efficiency and performance is crucial for meeting growing data demands and supporting emerging applications. This project aims to develop advanced models and algorithms that improve network performance while addressing broader impacts on safety and societal aspects. The methodology involves the use of diverse resources, including datasets that were collected by hand from selected regions of interests in Gazipur and Dhaka, specialized software tools for model simulation, data analysis and network performance data collection, and case studies of real-world 4G network deployments. Advanced statistical methods, machine learning algorithms, and optimization techniques are employed to analyze data and model throughput. The project tries to emphasize the importance of data anonymization, security, and compliance with data protection regulations in an attempt to address ethical and privacy concerns. The results demonstrate that machine learning models are able to simulate and predict network downlink throughput with acceptable standards of accuracy, validated through rigorous analysis and evaluation. Detailed data analysis reveals patterns and trends that inform the optimization models, while comparative analysis with existing studies highlights the advancements achieved. In addition, this project underscores the role of engineering in society, addressing the ethical and societal implications of 4G technology. The findings contribute to the technical field of telecommunications while promoting sustainable and inclusive connectivity solutions.
A Benchmark for Detection and Recognition of Bangladeshi Traffic Signs in Real-world Images
(Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh, 2022-05-30) Khan, Rizwanul Haque; Shanto, Md Saimul Haque; Ashik, Ahmed Nusayer
Traffic sign detection is an indispensable part of autonomous driving and transportation safety systems. However, the accurate detection and recognition of traffic signs remain challenging, especially under extreme conditions, such as various weather and geo-social features. Though a lot of work has been done in the domain of Traffic Sign Detection and Recognition (TSDR) systems, only a few of them focus on a dataset that comprises the real-world challenges. Moreover, in the context of Bangladesh, there is no well-defined public dataset, let alone one that focuses on real-life challenges. The geo-social features of Bangladesh add some unique challenges that are not seen in most parts of the world. This proposal aims to address the lack of quality Bangla traffic sign detection dataset. To accomplish this task, traffic sign images will be extracted from videos collected from Bangladeshi roads. A performance benchmark will be presented by applying state-of-the-art methods to the said dataset. Using the best-performing method, an autonomous driver notification system will be developed to alert the drivers on the go.
A Blockchain - Based Secure Model for Automobile Supply Chain with IoT
(Department of Mechanical and Production Engineering(MPE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2023-05-30) Arnab, Tawsif Zaman; Noor, Ekra Binta
"AutoChain," a blockchain-based solution designed to enhance transparency and trust within the global automotive supply chain. Traditional supply chains often face challenges such as disruptions and difficulties in identifying reliable partners. AutoChain addresses these issues by leveraging decentralized record-keeping of manufacturers, suppliers, and customers. By utilizing blockchain technology, AutoChain ensures the security, tamper-proofing, and traceability of transactions, with Layer 1 of the Ethereum Blockchain recording supply chain transactions among key stakeholders and Layer 2 capturing real-time data from IoT devices. To promote trust among participants, AutoChain implements an authentication system to validate the authenticity of stakeholders. Additionally, a reputation management system is incorporated, enabling the rating of end users based on the services provided. In cases of disruptions within the supply chain, AutoChain utilizes a game theory algorithm to identify the most suitable replacement participant. This novel approach separates the blockchain for global automobile supply chain transactions, offering a dedicated layer for addressing disruptions through game theory-based participant selection.
A brief review of phase change materials and CFD study of thermal management technique for electronic cooling using phase change material (PCM)
(Department of Mechanical and Production Engineering, 2021-03-30) Khan, Basit; khan, Muhammad Wasim; Almojamer, Momen; Khan, Muhammad Asif Nawaz
In this project two different studies were performed, coupled with the review study a numerical study of (2D/3D) transient numerical simulation of a phase change material (PCM) based finned heat sink were performed to investigate the heat transfer performance for passive cooling of electronic devices. A 2D/3D computational domain of finned heat sinks of 2 mm and 3 mm fin thickness are employed with a constant fin volume fraction of 9%, acting as thermal conductivity enhancer (TCE). The n-eicosane is employed as a PCM inside the heat sink to store the heat generated from the electronic device applied at the heat sink base. Transient numerical simulations are performed using finite-volume-method and conjugate heat transfer and melting/solidification phenomenon are investigated by applying various power levels to both computational domain, while the main focused was given to 3D computational domain. The numerical results show that the employed PCM with low temperature keeps the heat sink base temperature in lower limits and uniform melting is observed inside the finned heat sink. With the increase of heating power level, the PCM melting time is decreased for fin thickness heat sinks. Hence, thermal performance of heat sink was significantly improved owing to the inclusion of rectangular fins and PCM.
A Brief Study of Nanowire FET Biosensor and Analysis of Electrical Properties of Si and ZnO Gate-all-around Nanowire FET
(IUT, EEE, 2016-11-20) Reza, Syed Zahin
The detection of biological and chemical species is central to many areas of healthcare and the life sciences, ranging from uncovering and diagnosing disease to the discovery and screening of new drug molecules. Hence, the development of new devices that enable direct, sensitive, and rapid analysis of these species could impact humankind in significant ways. Devices based on nanowires are emerging as a powerful and general class of ultrasensitive, electrical sensors for the direct detection of biological and chemical species. Development of nanobiosensor is one of the most recent advancement in the field of Nanotechnology. Research on optical nanobiosensors with submicron-sized dimensions has opened new horizons for intracellular measurements. Taking advantage of the unique properties of the nanomaterials, faster and sensitive nanobiosensors can be developed. Apart from being sensitive and fast, the studies related to nanobiosensors have geared their efforts towards the development of nanomaterial-based sensors that are affordable, robust and reproducible. The nanobiosensors are equipped with immobilized bioreceptor probes, e.g., antibodies, enzyme substrate. Laser excitation is transmitted to photometric system in the form of optical signal (fluorescence). Nanobiosensors will revolutionize the future of disease diagnosis. The present review discusses the basic concepts, developments and the biomedical applications of nanobiosensors.
A Case Study on the Successful Implementation of 5s Process and its benefits
(IUT, MCE, 2016-11-20) Hossain, Zilkad; Ashraf, SK. Riad Bin
5S is amongst the first and fundamental steps implemented by an enterprise towards the path of implementing Total Quality Management and continuous improvement at the operation level. 5S is a process designed to organize the workplace, keep it clean, maintain effective and standard conditions. It inspires the discipline required to enable each individual to achieve and maintain a world-class environment. Many enterprises have practiced the 5S and derived significant benefits from it. In particular, this technique has been widely practiced in Japan. Most Japanese 5S practitioners consider 5S useful not just for improving their physical environment, but also for improving their thinking processes too. In Japan it is also called ‘workplace management’.
A Case Study: Implementation of Lean Tools to Reduce Lead Time in a Cable Manufacturing Company in Bangladesh
(Department of Mechanical and Production Engineering, Islamic University of Technology, Gazipur, Bangladesh, 2019-11-15) Mahmud, Raihan
Every small scale company has an effect on the industrial economy of a country and the world if broadly speaking. Globalization, updating technology, and higher competition have a big impact on small scale companies. These companies need to update their production management methods to reach economic, social and environmental development without making extensive changes. Most small scale companies are even unaware of lean manufacturing tools that exist today. The target of this study is the implementation of ‘Lean tools’ in a small scale company to increase productivity through effective workplace management. The purpose of this study is to understand the effect of lean manufacturing tools like SMED, 5s in plant management, material movement in a cable manufacturing company to understand how productivity and efficiency is changing. The methodologies used in the study are SMED in wire-drawing RBD machine, 5s in workplace rearrangement, plant layout for reducing lead time. The study reveals that lean tools are vital for this cable company. After implementing SMED in wire-drawing RBD machines and optimizing the layout, lead time was reduced by 26% hence profit margin will grow. This literature adds value to the research of lean tools by giving an insight into the implementation of lean tools in cable companies. The tools are implemented only for a static working condition without taking any unforeseen causes into account for delay.
A Cellular Automata Model for Object Monitoring in Mobile Wireless Sensor Network in Hexagonal Grid
(Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2017-11-15) Dipu, Shahidullah Kaiser; Khan, Md. Rahat Hussein
A Cellular Automata Model for Object Monitoring in Mobile Wireless Sensor Network in Hexagonal Grid By Shahidullah Kaiser (134420), Md. Rahat Hussein Khan (134426) Mobile Wireless Sensor Networks (MWSN) is an ad-hoc network that comprises of a large number of sensors. The sensors usually have limited sensing and communication capabilities. We present a CA model that efficiently monitor a moving object in distributed mobile wireless sensor network. CA is a biologically inspired discrete model. Although there are works that have used CA for developing Object Monitoring in Distributed Mobile Wireless Sensor Network, they mostly used square grids which is not a good representation of the actual MWSN model. We focus on simulating the mobile wireless sensor networks for monitoring a moving object considering energyefficiency. In a general case, a number of objects need to be monitored by the sensors and the objects can be static or mobile. Monitoring mobile objects is considerably harder than monitoring static objects. Mobile sensor networks can be useful in monitoring animal behavior. In this case, animals can move randomly within a network and the mobile sensors can also move to monitor their behavior and other aspects.
A CFD Study on Comparison of Heat Transfer Performance of Water based Graphene Nanoplatelets Nanofluids and Multiwalled Carbon Nanotubes Nanofluids in a Concentric Tube Heat Exchanger
(Department of Mechanical and Production Engineering, Islamic University of Technology, Gazipur, Bangladesh, 2022-05-30) Hoq, MD Zahinul
For the next generation of nanofluids, carbon nanomaterials are of tremendous interest. CnT and GnP, in particular, are extremely thermally conductive, and their usage in heat transfer nanofluids is a significant field of study. Using a concentric tube annular heat exchanger in the same operating circumstances, the heat transfer performance of GnP-nanofluid and MWCNT-nanofluid was investigated in this study. In the inner tube, the manufactured nanofluid flowed as a hot fluid in the reverse direction of a colder water flow in the annulus tube. The flow rate (1.5 L/min – 2.5 L/min) and concentration (0.01% – 0.35%) of nanofluid were varied in the experiment. At the same flow rates and nanofluid concentrations, the heat transfer coefficient of GnP-nanofluid was found to be greater than that of MWCNT-nanofluid. When an appropriate volumetric concentration is attained in both nanofluids, the favorable influence on heat transfer performance increase is at its peak. In comparison to MWCNT, our research reveals that GnP can increase heat transfer coefficient at lower volumetric concentrations and flow rates
A CNN-based Pipeline using Plane-wise Ensemble Technique for Classifying Alzheimer’s Disease from 3D MRI Images
(Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2024-08-30) Fardin, Mahtab Nur; Rafio, Md. Irfanur Rahman; Islam, Md. Jubayer
Alzheimer’s disease (AD) is a chronic neurodegenerative condition that progressively damages brain cells, resulting in memory and cognitive decline and eventually imped ing basic functionalities. With over 55 million people worldwide affected by demen tia, a number anticipated to rise significantly, the urgency for early diagnosis becomes paramount. While a definitive cure remains elusive, early intervention is crucial in mitigating disease progression and enhancing patient outcomes. This research inves tigates the potential of deep learning models for classifying Alzheimer’s Disease, em phasizing the challenges in Mild Cognitive Impairment (MCI) classification, and in troduces a CNN-based pipeline utilizing a plane-wise ensemble technique for 3D MRI image classification. To manage the complex nature of 3D MRI data, a CNN-based pipeline is proposed that makes use of a plane-wise ensemble technique. Decompos ing the 3D image into axial, coronal, and sagittal planes, and using an ensemble of 2D CNN models trained on the axial, coronal, and sagittal planes, the system attempts to include multi-view data and improve classification accuracy. This methodology also leverages projector functions to map the 3D volumes into a series of 2D images and tackles the computational challenges presented by 3D data, resulting in a more efficient and practical process even with constrained computation resources.
A Cohesion Based Friend Recommendation System
(Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2012-11-15) Naser, Md. Abu; Hamid, Md. Nafiz
Social network sites have attracted millions of users with the social revolution in Web 2.0. A social network is composed by communities of individuals or organizations that are connected by a common interest. Online social networking sites like Twitter, Facebook and Orkut are among the most visited sites in the Internet. In the social network sites, a user can register other users as friends and enjoy communication. However, the large amount of online users and their diverse and dynamic interests possess great challenges to support such a novel feature in online social networks. In this paper, we design a general friend recommendation framework based on cohesion after analyzing the current method of friend recommendation. The main idea of the proposed method is consisted of the following stages- measuring the link strength in a network and find out possible link on this network that is yet to be established; detecting communities among the network using modularity and recommending friends
A Comparative Analysis of Predicting Seismic Liquefaction Susceptibility of Dhaka Subway Project with a Machine Learning Approach.
(Department of Civil and Environmental Engineering (CEE), Islamic University of Technology(IUT), 2022-05-30) Mannan, Raiyan; Seebtaien, Omor; Mukarroma, Fahmida
Seismic soil liquefaction is a dangerous phenomenon that occurs during seismic loading due to earthquakes. In this study, empirical formulas are used to assess liquefaction triggering based on the standard penetration test (SPT) data from the Dhaka Subway Project. After that three machine learning algorithms are applied to predict seismic liquefaction triggering of the obtained dataset. The first machine learning algorithm, Logistic regression, is a linear classification model. It implements the sigmoid function to generate binary outputs. The second machine learning algorithm is the Support Vector Machine (SVM) which represents supervised learning and is widely used as a classification and outliers detection algorithm. The third machine learning algorithm is the Artificial Neural Network (ANN) based on the Multi-layer Perceptron (MLP) theory, which uses a training algorithm called Levenberg-Marquardt backpropagation. Furthermore, this study also highlights the correlation between different soil parameters in triggering soil liquefaction. The developed models are then evaluated with confusion matrices which are later used to find out Overall Accuracy, Precision, Sensitivity, Recall (Specificity), F1 score, RMSE, and MAE. ROC curves are also used to evaluate these models and establish which model is the most effective.
A Comparative Analysis On Finding Out Electrolytes From Effective Data Sets In Human Sweat
(Department of Electrical and Electronic Engineering(EEE), Islamic University of Technology(IUT),, 2022-05-30) Sadid, Md. Shahriar; Shahriar, Sayef; Mahamat, Abba
This paper explores the non-invasive method of identifying electrolyte levels of human sweat. A non- invasive micro patch antenna-based sensor is used to determine the electrolyte level of human sweat. This device is designed to be wearable so as to have close proximity to the human skin in order to have great advantage in detecting the electrolyte (NaCl) level from sweat. A 1.8 mm thick copper patch antenna that operate in a frequency range of 0.5 GHz -3.5 GHz is used. Paper based substrate is preferred due to the fact that it’s a good absorber and cost effective. For testing the sensitivity, the antenna is structured to have a frequency of 1.57 GHz with several dielectric constants ranging between 1.0 F/m - 2.0 F/m, thereby allowing the substrate dielectric to be controlled by the properties of the absorbed sweat. The paper looks at the Shift in resonant frequency and also the magnitude of reflection coefficient which is employed on a concentration range of approximately 0.001 mol/L - 5 mol/L of NaCl. For various levels of electrolyte, the resonant frequency, the reflection magnitude are fluctuating, the first resonance is regarded for analysis of data.
A Comparative Analysis On Finding Out Electrolytes From Effective Data Sets In Human Sweat
(Department of Business and Technology Management(BTM), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh, 2022-05-30) Nihal, Tasin Mushfique
This paper explores the non-invasive method of identifying electrolyte levels of human sweat. A non- invasive micro patch antenna-based sensor is used to determine the electrolyte level of human sweat. This device is designed to be wearable so as to have close proximity to the human skin in order to have great advantage in detecting the electrolyte (NaCl) level from sweat. A 1.8 mm thick copper patch antenna that operate in a frequency range of 0.5 GHz -3.5 GHz is used. Paper based substrate is preferred due to the fact that it’s a good absorber and cost effective. For testing the sensitivity, the antenna is structured to have a frequency of 1.57 GHz with several dielectric constants ranging between 1.0 F/m - 2.0 F/m, thereby allowing the substrate dielectric to be controlled by the properties of the absorbed sweat. The paper looks at the Shift in resonant frequency and also the magnitude of reflection coefficient which is employed on a concentration range of approximately 0.001 mol/L - 5 mol/L of NaCl. For various levels of electrolyte, the resonant frequency, the reflection magnitude are fluctuating, the first resonance is regarded for analysis of data.
A comparative study of dielectric Materials and metals as Nanoplasmonic waveguides
(Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh, 2015-11-30) Azad, Ferdous S.; Hossain, Md. Sahabul; Ahmed, Mohammed Tanvir
The ability of Surface Plasmon Polaritons (SPPs) to overcome the diffraction limit has made it a field of great research interest. It is being predicted that next generation microchips will be produced using plasmonics-electronics hybrid technology. This will solve the RC delay issue of current electronic microchips and scaling issue of conventional integrated photonic devices. However, there are some shortcomings of SPP which are higher losses in the metallic layer and less propagation distance. Using current technology, propagation distance of SPP cannot exceed the benchmark of micrometers. The objective of this thesis is study the power transmission characteristics of different kinds of waveguides for several materials and analyze their performance using the FDTD method. SPP propagation characteristics through different optical nanostructures having different geometries have been investigated to analyze the performance of the materials. Waveguides with different kinds of bends have been investigated and compared with each other to see the effects of these bends on the efficiency of power transmission. All of the simulations have been done for a range of signal wavelength extending beyond the visible light spectrum.