MATLAB Workspace Research Articles

Hybrid solar-driven hydrogen generation by sorption enhanced–chemical looping and hydrocarbon reforming coupled with carbon capture and Rankine cycle

Hydrogen (H2) production from fossil fuels using Hydrocarbon Reforming Methods (HRM) accounts for nearly 95% of Global H2 production. Unlike hybrid Chemical Looping Steam Reforming (CL-SR) systems, the Integrated Solar-Driven Sorption Enhanced–Chemical Looping of Hydrocarbon Reforming (SE-CL-HR) utilises solar thermal energy from the Concentrating Solar Power (CSP) system to drive the endothermic decomposition of feedstocks. Furthermore, the simulated hybrid systems utilise recovered heat to generate electricity, reuse of by-product CO2 for more syngas production and finaly, CO2 capture by reaction of CaO to form CaCO3. This work focused on simulating hybrid CSP systems and SE-CL-HR plants with Heat Transfer Fluid (HTF) output temperatures between 750 and 1050 °C. In this study, System Advisor Model (SAM) and MATLAB software are used to develop the CSP system. While the CSP result saved in the MATLAB workspace gets exported to Simulink to feed SE-CL-SMR, SE-CL-POX and SE-CL-ATR Aspen plus models. The integrated system was fed with CH4 as the working fluid of the solar furnace. Stoichiometric and Gibbs free-energy minimisation were employed to investigate the effect of operating parameters. The output of the integrated system shows ≥9.5% exergy efficiency in comparison to conventional HRM. In addition, CO2 capture by CaO and high-pH water (Ca, Mg, Na+, O2, OH− and Cl−) to produce CaCO3, MgCO3 and other valuable products was also investigated in a process simulation. The research results revealed that for 8.1 tons/hr of CH4 and 277.1 tons/hrH2O (steam) flowrates, 62 tons/hr of H2 can be generated and 338.5 tons/hr of CO2 emission can be reused and captured by the adoption of these new innovative technologies.

Kurşun Asit Bataryalar için SOC Tahmini Yaklaşımını İçeren Bir Batarya Yönetim Sistemi Tasarımı

Storage is one of the most important issues of the last decades. In particular, storage systems are needed in order to benefit more effectively from renewable energy systems where production cannot be controlled. One of the most important problems in storage is that as the amount of energy desired to be stored increases, the need for space also increases. Therefore, it is of great importance to manage energy effectively in such systems. In this study, a battery management system (BMS) that can be used for lead acid batteries has been designed. This BMS has a measurement and control system based on STM 32 microcontroller and is controlled via an interface prepared in the MATLAB Simulink environment and the test data is imported into the MATLAB Workspace environment. The designed system can also perform battery charge-discharge experiments in accordance with the battery characteristics. Charge-discharge experiments were carried out using the designed system, and a model was developed to determine the state of charge (SOC) of the battery using the data collected during these experiments. With the model developed based on Elman Neural Networks, the SOC of battery could be estimated at an error level of less than 1%.

"Iris Recognition Based Data Security for Secure Transmission Over Internet of Things Network"

The biometric traits of any human being such as fingerprint, tongue prints, face recognition, Retina Scan, Iris recognition etc. are unique and cannot be replicated or fabricated using modern technologically advanced processes. These unique traits are used to identify individuals for grating access to sensitive data over the cloud. In this paper we propose a biometric authentication system based on Iris recognition to allow user identity based data to be pushed on to the cloud for global access, if the user Iris image is authenticated with the database. The real time Iris scanner captures the Iris image and same is imported to the MATLAB workspace for feature extraction and matching. Upon successful matching, the data is transmitted to the ThingSpeak Internet of Things (IoT) analytics platform. The IoT framework is a massive network of physical devices sharing data according to set protocols. Most of the IoT enabled devices lack security protocols. Thus, biometric authentication in general and iris recognition in particular finds a perfect fit for securing data over an IoT framework.

A modularized numerical framework for the process-based total system performance assessment of geological disposal systems

This study developed a safety assessment tool for geological disposal systems called APro, a systemically integrated modeling system based on modularizing and coupling the processes which need to be considered in a geological disposal system. Thermal, hydraulic, chemical, canister failure, radionuclide release and transport processes were considered in the current version of APro. Each of the unit processes in APro consists of a single Default Module, and several Alternative Modules which can increase the flexibility of the model. As an initial stage of developing the modularization concept and modeling interface, the Default Modules of each unit process were described, with one Alternative Module of chemical process. The computation part of APro is mainly a MATLAB workspace controlling COMSOL and PHREEQC, which are coupled by an operator splitting scheme. The APro model domain is a stylized geological disposal system employing the Swedish disposal concept (KBS-3 type), but the repository layout can be freely adjusted. In order to show the applicability of APro to the total system performance assessment of geological disposal system, some sample simulations were conducted. From the results, it was confirmed that coupling of the thermal and hydraulic processes and coupling of the canister failure and the radionuclide release processes were well reflected in APro. In addition, the technical connectivity between COMSOL and PHREEQC was also confirmed.

Comparisons of Soft Decision Decoding Algorithms Based LDPC Wireless Communication System

The Low Density Parity Check (LDPC) forward error correction code provides significant results that have been very close to Shannon limit. This paper compares the Bit Error Rate (BER) performance of soft decision decoding algorithms of LDPC codes on AWGN channel. Devising soft decision decoding algorithms which are good in BER performance requires a comparison of probabilistic, log domain and Min-Sum methods. Simulations are conducted with different parameters using MATLAB workspace to evaluate the LDPC system performance. Results have shown that Min-Sum has outperformed the algorithms of Log Domain and Prob. Domain with a considerable amount of the Signal to Noise Ratio (SNR). Finally, the optimal LDPC parameter values have been selected based on the achieved results which provide superior results.

Investigation on effective operating variables in gamma-type Stirling engine performance: a simulation approach

The Stirling engine is one of the engines that has become popular due to its many advantages. Nowadays, lack of fossil fuels has led to a lot of attention to the use of renewable energies. For this reason, solar energy has drawn a lot of attention to be used as the Stirling engine heat source. The purpose of this paper is to investigate the performance of a proposed Stirling engine in different engine speeds, pressures, and working fluids. The proposed Stirling engine is of gamma-type. This engine is simulated using the Nlog code which is written for this engine in MATLAB work space. This code was validated by experimental data in our previous works. The investigated fluids in this study are helium, nitrogen, and hydrogen. It was found that the best fluid for the proposed Stirling engine is hydrogen, and the best engine speed is 1300 rpm. Also, the higher the engine pressure, the more the output work will be.

Modeling of Automatic Sprinkler Irrigation Process Using Finite State Machine (FSM) and Proportional Integral Derivative (PID) Controller

In this paper, the real-time automatic irrigation system was designed to supply water to the root zone of plant only when soil moisture content goes below a certain level known as critical moisture content. Particularly, models for the DC motor driven centrifugal irrigation pump, sprinkler irrigation nozzle, plant water uptake process, a proportional-integral-derivative (PID) controller were obtained using analytical methods. Automatic control logic was designed using the finite state machine (FSM) concept to act as a supervisory controller for the real-time automatic irrigation system. The models for the different sections of the system were assembled on MATLAB workspace, and then simulated and tested to ascertain the workability of the system. Specifically, the model was simulated for 0.5 seconds and the step response and impulse response were also computed. The results showed that the system performance is quite suitable for the irrigation system because a response time of 2 seconds offer a 1.36 seconds rise time for the system to reach its peak unit amplitude of 1.06, although with a much longer settling time of 4.21seconds. The results also showed that 1.7145×105mm3H2O/mm3Soil was consumed by the plant within the simulation period. In all, the simulation results obtained showed that the irrigation system was able to supply the needed water to replenish the soil moisture deficit without frequent human intervention. The models presented in this research are useful for planning, designing and analysis of automatic irrigation system for mechanized farming.

SimpleDSFviewer: A tool to analyze and view differential scanning fluorimetry data for characterizing protein thermal stability and interactions.

Differential scanning fluorimetry (DSF) is a widely used thermal shift assay for measuring protein stability and protein-ligand interactions that are simple, cheap, and amenable to high throughput. However, data analysis remains a challenge, requiring improved methods. Here, the program SimpleDSFviewer, a user-friendly interface, is described to help the researchers who apply DSF technique in their studies. SimpleDSFviewer integrates melting curve (MC) normalization, smoothing, and melting temperature (Tm) analysis and directly previews analyzed data, providing an efficient analysis tool for DSF. SimpleDSFviewer is developed in Matlab, and it is freely available for all users to use in Matlab workspace or with Matlab Runtime. It is easy to use and an efficient tool for researchers to preview and analyze their data in a very short time.

Recognition and Classification of Power Quality Disturbances by DWT-MRA and SVM Classifier

Electrical power system is a large and complex network, where power quality disturbances (PQDs) must be monitored, analyzed and mitigated continuously in order to preserve and to re-establish the normal power supply without even slight interruption. Practically huge disturbance data is difficult to manage and requires the higher level of accuracy and time for the analysis and monitoring. Thus automatic and intelligent algorithm based methodologies are in practice for the detection, recognition and classification of power quality events. This approach may help to take preventive measures against abnormal operations and moreover, sudden fluctuations in supply can be handled accordingly. Disturbance types, causes, proper and appropriate extraction of features in single and multiple disturbances, classification model type and classifier performance, are still the main concerns and challenges. In this paper, an attempt has been made to present a different approach for recognition of PQDs with the synthetic model based generated disturbances, which are frequent in power system operations, and the proposed unique feature vector. Disturbances are generated in Matlab workspace environment whereas distinctive features of events are extracted through discrete wavelet transform (DWT) technique. Machine learning based Support vector machine classifier tool is implemented for the classification and recognition of disturbances. In relation to the results, the proposed methodology recognizes the PQDs with high accuracy, sensitivity and specificity. This study illustrates that the proposed approach is valid, efficient and applicable.

A cost-effective approach for chicken egg weight estimation through computer vision

Egg weighing and classification are among the most significant phases done in egg processing by industries which are tedious if done manually by poultry owners, and egg inspectors and graders. This study presented an alternative way of estimating chicken egg weight through computer vision minimizing human interaction during the process. In this study, fifteen eggs of white leghorn chicken layers of different sizes were tested. The eggs’ image was captured using an inexpensive yet reliable webcam which was then loaded onto the MatLab workspace for image processing and further image analysis. The center of gravity of the image was determined, and the extraction of minor axis length and major axis length followed. The obtained values were used to compute the egg’s weight mathematically. Through the different image processing methods, image dimensions were extracted and used to calculate the desired output. The results of this study showed 96.31% accuracy in estimating the egg’s weight and classification validated by manual egg weighing and classification procedure.

Autonomous Hybrid Priority Queueing for Scheduling Residential Energy Demands

The advent of smart grid technologies has opened up opportunities to manage the energy consumption of the users within a residential smart grid system. Demand response management is particularly being employed to reduce the overall load on an electricity network which could in turn reduce outages and electricity costs. The objective of this paper is to develop an intelligible scheduler to optimize the energy available to a micro grid through hybrid queueing algorithm centered around the consumers’ energy demands. This is achieved by shifting certain schedulable load appliances to light load hours. Various factors such as the type of demand, grid load, consumers’ energy usage patterns and preferences are considered while formulating the logical constraints required for the algorithm. The algorithm thus obtained is then implemented in MATLAB workspace to simulate its execution by an Energy Consumption Scheduler (ECS) found within smart meters, which automatically finds the optimal energy consumption schedule tailor made to fit each consumer within the micro grid network.

Optimising the design of tabular mean CUSUM control chart to enhance the detection of diminutive process shifts

Although the performance of the CUSUM chart in detecting small process shift is better than Shewhart chart, there exists cases in reality that require very quick response of detecting small process shift. This paper studies the influential factors that affect the CUSUM control chart design and its in-control and out-of-control average run length (ARL) values. The controllable factors studied are the slack value k; the decision interval h; and the Headstart or Fast Initial Response. These factors are varied at different values for the process expected shift (in standard deviation units) δ. Following this, a non-linear regression model is deduced to compute the ARL of the control chart at any combination of process and control chart variables. Optimisation model is utilised to achieve a specific value for the ARL through fixing the controllable factors. A computer program coded in Matlab workspace (Matlab and Statistics Toolbox Release, 2015) is used for the computation of the ARLs values.

Optimising the design of tabular mean CUSUM control chart to enhance the detection of diminutive process shifts

Although the performance of the CUSUM chart in detecting small process shift is better than Shewhart chart, there exists cases in reality that require very quick response of detecting small process shift. This paper studies the influential factors that affect the CUSUM control chart design and its in-control and out-of-control average run length (ARL) values. The controllable factors studied are the slack value k; the decision interval h; and the Headstart or Fast Initial Response. These factors are varied at different values for the process expected shift (in standard deviation units) δ. Following this, a non-linear regression model is deduced to compute the ARL of the control chart at any combination of process and control chart variables. Optimisation model is utilised to achieve a specific value for the ARL through fixing the controllable factors. A computer program coded in Matlab workspace (Matlab and Statistics Toolbox Release, 2015) is used for the computation of the ARLs values.

Computer Aided Design of Centrifugal Fan Impeller Using CATIA Software

In this paper, the 3D model of the centrifugal fan impeller will be obtained using CAD software (CATIA). The blade will be obtained with 4 design methods: constant blade width and variable blade angle; hyperbolic blade width and variable blade angle; hyperbolic blade width and constant blade angle; linear blade width and variable blade angle. A comparative analysis of the weight of the blade, as well as of the weight of the rotor composed by cascade of blades, front and rear shrouds will be presented. Two materials have been used for all the elements of the centrifugal fan impeller: steel and aluminium. For computational purposes the MATLAB programming language will be used. The centrifugal fan blade will be designed as untwisted geometry with =2 reference curves (one on the rear shroud and the other one on the front shroud) with different numbers of reference points ={5, 10, 20, 30, 40, 50}. After running the MATLAB script file, the coordinates of reference points of the blade will be obtained for all 4 blade design methods. The transfer of the reference points coordinates from MATLAB workspace to CATIA has been performed using the automatic surface generation method, via an EXCEL macro file. This is the recommended method especially for a big number of reference points.

A Matlab-based Monte Carlo algorithm for transport of gamma-rays in matter

Abstract Transport of gamma photons in many fields such as radiation detection, dosimetry, and treatment planning is used. The transport of 1 MeV and 5 MeV photons in a water phantom was simulated by using the Monte Carlo algorithm in Matlab work space. The result of KERMA calculation showed good agreement with Arqueros and Montesinos [American Journal of Physics 71 (2003), no. 1, 38–45], and MCNP4C. The proposed algorithm has ability to read out from different cross section libraries. As the future work, it also can be extend for the electron and visible photon transport.

Parameter Design of Tooth Profile for Internal Cycloid Gear Pump with Multi-Teeth Difference

Based on the principle of gear engagement, the equation of rotor tooth profile has been reduced in this paper and has drawn the actual cycloid tooth profile by MATLAB software, the data obtained from MATLAB Workspace is processed by EXCEL, so the parameter drawing of the full gear tooth profile curve is very easy in AutoCAD software platform. This design method has high accuracy and convenient to processing in CNC machining center.

Design and performance analysis of live model of Bessel beamformer for adaptive array system

Purpose – The purpose of this paper is to design and analyze the performance of live model of Bessel beamformer for thorough comprehension of beamforming in adaptive environment and compared with live model of least mean square (LMS) in terms of gain and mean square error (MSE). It presents the principal elements of communication system. The performance of designed live model is tested for its efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format into the MATLAB workspace. These adaptive techniques are illustrated by appropriate examples. Design/methodology/approach – The proposed algorithm framework relies on MATLAB software with the goal to obtain high efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format. It is assumed that this audio signal is only the message or the baseband signal received by the computer. Here the authors consider computer (laptop) as a base station containing adaptive signal processing algorithm and source (mobile phone) as a desired user, so the experiment setup is designed for uplink application (user to base station) to differentiate between desired signal, multipath and interfering signals as well as to calculate their directions of arrival. Findings – The presented adaptive live model is reliable, robust and lead to a substantial reduction of MSE, signal recovery in comparison with the LMS technique. The paper contains experimental data. Obtained results are presented clearly and the conclusion comes directly from the presented experimental data. The paper shows that the presented method leads to superior results in comparison with the popular LMS method and can be used as a better alternative in many practical applications. Research limitations/implications – The adaptive processes described in the paper are still limited to simulation. It is because of the non-availability of real system for testing, therefore chosen research approach that is platform of MATLAB is opted for simulation. Therefore, researchers are encouraged to test the proposed algorithms on real system if possible. Practical implications – The paper contains experimental data. The paper's impact on the society is acceptable. These implications are consistent with the findings and the conclusions of the paper. However, there is a need to extend this paper to a next level by implementing the proposed algorithms in the real time environment using FPGA technology. Social implications – This research will improve the signal quality of wireless cellular system by increasing capacity and will reduce the total cost of the system so that cost toward subscribers be decreased. Originality/value – The live model presented in this paper is shown to provide better results. It is the original work and can provide scientific contribution to signal processing community.

VMCK Transmission System Design for SDR Applications

Very minimum chirp keying (VMCK) as a novel high bandwidth efficiency modulation scheme is implemented on small form factor (SFF) software-defined radio (SDR). The VMCK transmission system model is elaborated based on Simulink within Matlab. Also, the final demodulation data stream at the output of the VMCK transmission system shows good performance in simulation. The transmitter and the receiver are designed on the SDR platform. The VMCK baseband signals with 2.5MHz are transmitted from Matlab workspace by ROM block, and then the VMCK signals are ratio frequency (RF) modulated with 432MHz. In addition, the RF receiving intermediate frequency (IF) signals with 30MHz on the SDR platform. The VMCK transmission model is easy to implement and has strong properties to resist synchronization error.

Test of the ENEA Joint With a NbTi Large CiC Conductor

This paper describes the results of the measurements performed in June 2011 on a NbTi cable-in-conduit conductor curved joint in the ENEA Superconductivity Laboratories (C.R. Frascati). The effectiveness of the joint design, patented by ENEA, had been already verified for the Nb3 Sn EDIPO conductor; in this case, it has been applied to a NbTi cable-in-conduit conductor. The joint was manufactured and instrumented by ENEA, using part of a JT-60SA toroidal field conductor sample (namely the TFCRS) produced by Luvata Italy and successfully tested in SULTAN. For testing purposes, the NbTi “shaking hands”-type joint was hosted in a variable temperature cryostat with a background superconducting magnet. The sample was used as the secondary coil of a transformer having the background magnet as primary coil. Measurements were preceded by preliminary code simulation studies computed in the Matlab workspace, and by 3-D finite element method analyses, to estimate the test requirements and its feasibility. The joint resistance value, found to be less than 2 nΩ has been derived both by the sample current decay time constant evaluation and by calorimetric calculations. After a short description of the joint design and fabrication, as well as of the test instrumentation and geometry, the joint resistance evaluation will be presented, together with the data analysis procedures and results.

Discordance in the anatomical locations between morphological and perfusion changes occurring with the progression of Alzheimer’s disease

The aim of this study was to clarify the difference between the morphological and perfusion changes occurring with the progression of Alzheimer's disease (AD). The study focused on 37 patients who were clinically diagnosed with AD and were examined by both MRI and perfusion SPECT twice during a 1- to 2-year clinical observation period. Twenty-four of the 37 patients showed a progression of cognitive deterioration during the 1.2(±0.4)-year period of clinical observation (rapidly progressing group: initial mean MMSE score = 23.3; second mean MMSE score = 20.2), while 13 patients showed no apparent progression of cognitive deterioration (slowly progressing group: initial mean MMSE score = 21.2; second mean MMSE score = 22.2). The morphological changes were evaluated using a voxel-based morphometric technique with segmented MRI images. Cerebral perfusion was measured by Tc-99m ECD SPECT. Data analysis was performed by SPM on a MATLAB work space (2007.a). There was no significant difference in either the perfusion or gray matter density between the rapidly progressing and slowly progressing groups at the initial examination. The rapidly progressing group showed an interval decrease of perfusion in the bilateral parieto-occipital cortex and a decrease of gray matter density in the bilateral temporal and cingulate cortex. The slowly progressing group did not show a significant interval change in either the cerebral perfusion or gray matter density. These results suggest that rapid symptomatic progression in AD patients accompanies rapid progression of both morphological and perfusion changes, although the regions of the changes differ between them.