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1

Delamination analysis in single-point incremental forming of steel/steel bi-layer sheet metal

Hassan M., Hussain G., Ilyas M., Ali A.

Archives of Civil and Mechanical Engineering

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2020

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Vol. 20, no. 2

124--137

EN

Layered metallic materials (LMMs) offer superior properties in comparison to their counterpart monolithic sheets. Single-point incremental forming (SPIF) has emerged as an economical solution to produce LMM parts. However, delamination can limit the formability of such parts. In this study, the delamination analysis during SPIF of layered sheets was performed. Steel/steel bi-layer sheets were fabricated by roll bonding. These sheets were produced at thickness reduction ratios of 47%, 58% and 70%. The bond strength and fracture toughness in mode I and mode II were determined by T-peel and tensile shear tests, respectively. When the thickness reduction ratio was increased from 47 to 70%, an increase in bond strength was observed with 572% increase in mode I and 15.6% in mode II, respectively. On the other hand, with the same percent increase in thickness reduction, the critical strain energy release showed an increase of 3992% in mode I and 20% decrease in mode II. Surface-based cohesive zone model was used to define the interface between layers during numerical simulation of SPIF for delamination analysis. To validate the numerical results, SPIF of given bi-layer sheet was performed experimentally and a good agreement between the numerical and experimental results was observed.

2

Effects of aluminum (Al) incorporation on structural, optical and thermal properties of ZnO nanoparticles

Ahammed N., Hassan M. S., Hassan M.

Materials Science Poland

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2018

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Vol. 36, No. 3

419--426

EN

In this research article, pure and 1 %, 3 % and 5 % aluminium doped zinc oxide nanoparticles (NPs) were prepared via sol-gel method and then calcined at 500 °C. X-ray diffraction (XRD), scanning electron microscope (SEM), Fourier transform infrared (FT-IR) spectroscopy, UV-Vis spectroscopy, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) techniques were used to investigate the structural, optical and thermal properties of synthesized pure and Al doped ZnO nanoparticles. Energy dispersive X-ray spectroscopy (EDX) analysis revealed high purity of nanoparticles in the synthesized products without any impurity peaks. Mean dimension of the nanoparticles was ~28 nm and they were hexagonal in shape, according to the images analyzed by transmission electron microscope (TEM). The optical absorption spectra of pure and Al doped ZnO samples studied using UV-Vis spectrometry have been presented and we have observed that the band gap increases with increasing Al concentration. In FT-IR spectra, the broad absorption peaks around 485 cm-1 and 670 cm cm-1 were assigned to Zn–O vibration. Above 450 °C, the TG curve became flat what means there was no weight loss. In the DSC curve it is seen that the transition at 150 °C was highly exothermic because of structural relaxation and on doping the exothermic peaks became shifted to the lower value of temperature. These types of materials are very useful in optoelectronics applications.

3

Intelligent machining: real-time tool condition monitoring and intelligent adaptive control systems

Hassan M., Sadek A., Attia M. H., Thomson V.

Journal of Machine Engineering

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2018

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Vol. 18, No. 1

5--17

EN

Unmanned manufacturing systems has recently gained great interest due to the ever increasing requirements of optimized machining for the realization of the fourth industrial revolution in manufacturing ‘Industry 4.0’. Real-time tool condition monitoring (TCM) and adaptive control (AC) machining system are essential technologies to achieve the required industrial competitive advantage, in terms of reducing cost, increasing productivity, improving quality, and preventing damage to the machined part. New AC systems aim at controlling the process parameters, based on estimating the effects of the sensed real-time machining load on the tool and part integrity. Such an aspect cannot be directly monitored during the machining operation in an industrial environment, which necessitates developing new intelligent model-based process controllers. The new generations of TCM systems target accurate detection of systematic tool wear growth, as well as the prediction of sudden tool failure before damage to the part takes place. This requires applying advanced signal processing techniques to multi-sensor feedback signals, in addition to using ultra-high speed controllers to facilitate robust online decision making within the very short time span (in the order of 10 ms) for high speed machining processes. The development of new generations of Intelligent AC and TCM systems involves developing robust and swift communication of such systems with the CNC machine controller. However, further research is needed to develop the industrial internet of things (IIOT) readiness of such systems, which provides a tremendous potential for increased process reliability, efficiency and sustainability.

4

Developing nonlinear models for sediment load estimation in an irrigation canal

Ahmed F., Hassan M., Hashmi H. N.

Acta Geophysica

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2018

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Vol. 66, no. 6

1485--1494

EN

The study was performed to estimate the weekly sediment load in Thal canal located in Mianwali district Punjab, Pakistan. Past records of sediments and discharge have been considered as the input parameters. The best input combinations have been identified with the help of advanced algorithms including full, sequential and increasing embedding, genetic algorithm and hill climbing in combination with the gamma test. Model training has been carried out using two artificial neural networkbased algorithms, namely Broyden–Fletcher–Goldfarb–Shanno (BFGS), back-propagation and a local linear regression technique. A variety of statistical parameters including R square, root mean squared error, mean square error and mean bias error (MBE) has been calculated in order to evaluate the best models. The results strongly suggested that BFGS-based model performed better than all other models with remarkably low values of MBE. Significantly high values of correlation coefficient (R square) in both training and testing evidenced a close similarity between actual and predicted sediment load values for the same model.

5

Integrated Computer Vision and Soft Computing System for Classifying the Pilling Resistance of Knitted Fabrics

Eldessouki M, Bukhari H A, Hassan M, Qashqary K

Fibres & Textiles in Eastern Europe

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2014

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Vol. 22, no. 6 (108)

106--112

EN

Fabric pilling is one of the important properties that affect fabric appearance. The testing of fabric pilling using the standard methods available, however, depends on subjective sample evaluation. Objective fabric pilling evaluation using image processing techniques comprises four main stages that include binarisation, segmentation, quantisation, and classification. Literature on the topic focuses only on one or more of these stages while there is a growing need for an integrated system that combines the most effective techniques of each stage and introduces them in a way that does not depend on the subjective evaluation of human operators. This work tries to tackle this problem and creates an integrated system for classifying the pilling resistance of knitted fabrics. The system introduced a new method for generating an image library based on photographs of the EMPA Standards to allow the training and testing of a soft-computing classifier. The method suggested was tested using knitted samples of different structures and colours and the results show their high robustness performance. The quantitative pilling classification produced from the system suggested shows high agreement with the subjective operators’ evaluation with a Spearman’s correlation coefficient of +0.85.

PL

Dotychczasowe metody oceny pilingu zależą od subiektywnej oceny oceniającego. Obiektywne oceny pilingu za pomocą analizy obrazu zawierają cztery główne stadia: binaryzację, segmentację, kwantyzacją i klasyfikację. Dostępna literatura podaja na ogół omówienie tylko jednego lub więcej z czterech stopni, natomiast istnieje potrzeba zintegrowanego systemu, który umożliwiałby ogólną ocenę bez subiektywnej ingerencji oceniającego. W pracy postarano się rozwiązać ten problem i stworzono zintegrowany system dla klasyfikacji odporności na piling. System zawiera bazę zdjęć różnych struktur poddanym różnym etapom pilingu. Wyniki uzyskiwane z opracowanego systemu klasyfikacji są w dużej mierze zgodne z wynikami podawanymi przez etatowych subiektywnych klasyfikatorów.

6

Application of Principal Component Analysis to Boost the Performance of an Automated Fabric Fault Detector and Classifier

Eldessouki M, Hassan M, Qashqary K, Shady E

Fibres & Textiles in Eastern Europe

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2014

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Vol. 22, no. 4 (106)

51--57

EN

There is a growing need to replace visual fabric inspection with automated systems that detect and classify fabric defects. The digital processing of fabric images utilises different methods that offer a large set of image features. The correlation between those features lead to problems during fabric fault classification and reduces the performance of the classifiers. This work extracted a combination of statistical (spatial) and Fourier transform (spectral) features from fabric images of the most frequent faults. Principal component analysis (PCA) was implemented to reduce the dimensionality of the input feature dataset, which achieved a reduction to 36% of the original data size while preserving 99% of information in the original dataset. The features processed using the PCA were fed to an artificial neural network (ANN) to classify the fault categories and then compared to another ANN that worked with the whole feature dataset. The performance of the network that was implemented after application of the PCA increased to 90% of the correct classification rate as compared to 73.3% for the other network.

PL

Istnieje wzrastająca potrzeba zamiany wizualnej inspekcji płaskich wyrobów włókienniczych automatyzowanymi systemami , które będą w stanie rozpoznać i sklasyfikować defekty materiału. Dla cyfrowej obróbki obrazów tkanin stosuje się różne metody oferujące identyfikacje całego zestawu właściwości obrazu. Korelacja pomiędzy tymi właściwościami prowadzi do problemów podczas identyfikacji i klasyfikacji błędów materiałów i redukuje sprawność klasyfikacji. W pracy wyselekcjonowano kombinacje statystycznych (przestrzennych) i fourierowskch (spektralnych) transformacji pozwalających na wyróżnienie zobrazów materiałów najczęściej występujących błędów. W dalszej części pracy usiłowano zredukować ilość danych wejściowych oraz zastosowano dwa różne systemy sztucznych sieci neuronowych. Wynikiem wszystkich poczynań było zdecydowane zwiększenie skuteczności wykrywania błędów.

7

Influence of Sportswear Fabric Properties on the Health and Performance of Athletes

Hassan M., Qashqary K., Hassan H. A., Shady E., Alansary M.

Fibres & Textiles in Eastern Europe

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2012

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Vol. 20, no. 4 (93)

82--88

EN

The main goal of this work was to study the Influence of sportswear fabric properties on the physiological responses and performance of athletes. The influence of three different types of sportswear fabrics on the physiological response and performance of volunteers in sports conditions was investigated. The fabrics and garments tested were made of 100% cotton, a 65/35 polyester/cotton blend and 100% polyester fibres. Seven volunteer were selected to wear the sportswear during the physical exercise assigned and their physiological responses were tested. The results of the study show a statistically significant effect on the athletes' physiological responses and performance parameters measured for the different types of sportswear tested. The sample with 100% polyester produced the best physiological responses and performance from the athletes. This effect can be related to better moisture management, which reflects the amount of relative water vapour permeability (68%) and lower thermal conductivity. This will enhance the body's temperature regulation leading to increase athletes' cardiorespiratory fitness and performance. The results also show the high correlation between the sportswear fabrics properties and athletes' physiological responses and performance, except the relationship between the end-tidal partial pressure of oxygen (PETO2) and fabric thickness (h), air permeability (AP) and thermal resistance (r), which are not highly correlated. The other correlation values vary between (š0.62 and (š1).

PL

Badano właściwości ubiorów sportowych na fizjologiczną odpowiedź oraz wytrzymałość organizmu. Przebadano trzy rożne rodzaje ubiorów wykonanych z 100% bawełny, mieszanki 65/35 poliester/bawełna oraz 100% poliestru. Wytypowano 7 ochotników, którzy w przygotowanych ubiorach wykonywali zaprogramowane ćwiczenia a następnie poddano ich badaniom. Wyniki opracowano statystycznie i wykazano, że najkorzystniejsze właściwości posiada odzież wykonana ze 100% poliestru. Wynik ten można tłumaczyć lepszymi właściwościami transportu wilgoci wynikającymi z poziomu przepuszczalności pary wodnej i niższą przewodnością termiczną. Właściwości te wpływają na zachowanie się organizmu a zwłaszcza na sprawność układu krążeniowo-oddechowego, a tym samym wydolność organizmu. Wykazano korelację pomiędzy właściwościami ubioru a wydolnością organizmu za wyjątkiem korelacji pomiędzy grubością materiału a wydechowym cieśnieniem parcjalnym tlenu (PETO2) oraz przepuszczalnością powietrza i opornością cieplną.

8

Image Processing Based Method Evaluating Fabric Structure Characteristics

Shady E., Qashqary K., Hassan M., Militky J.

Fibres & Textiles in Eastern Europe

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2012

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Vol. 20, no. 6A (95)

86--90

EN

A digital image processing approach was developed to evaluate fabric structure characteristics and to recognise the weave pattern utilising a Wiener filter. Images of six different groups were obtained and used for analysis. The groups included three different fabric structures with two different constructions for each. The approach developed decomposed the fabric image into two images, each of which included either warp or weft yarns. Yarn boundaries were outlined to evaluate the fabric surface characteristics and further used to identify the areas of interlaces to detect the fabric structure. The results showed success in evaluating the surface fabric characteristics and detecting the fabric structure for types of fabrics having the same colors of warp and weft yarns. The approach was also able to obtain a more accurate evaluation for yarn spacing and the rational fabric cover factor compared to the analytical techniques used to estimate these characteristics.

PL

Przy zastosowaniu filtra Winera opracowano cyfrową metodę analizy obrazu umożliwiającą ocenę struktury tkanin oraz rozpoznawanie splotu. Zbadano obraz sześciu zróżnicowanych grup tkanin, o 3 rożnych splotach i 2 strukturach, uzyskując dwa obrazy dla każdej tkaniny, z których każdy obejmuje przędze osnowy lub wątku. Wyznaczono wizualne granice nitek osnowy i wątku w celu oceny właściwości powierzchni tkaniny i identyfikacji obszarów przeplotów dla zbadania struktury tkaniny. Badania dla oceny właściwości powierzchni tkaniny i jej struktury dla tkanin o takich samych kolorach przędz wątku i osnowy zakończyły się sukcesem. Dokonano również oceny rozstawu przędzy i współczynnika pokrycia tkaniny i stwierdzono, że metoda ta jest dokładniejsza niż dotychczas stosowane metody analityczne.

9

Measurement of thermal properties of the skin

Togawa T., Otsuka K., Hassan M.

Biocybernetics and Biomedical Engineering

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2002

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Vol. 22, no. 4

55-68

EN

The skin is the boundary between the body and its thermal environment, and heat dissipation from the body depends on the thermal properties of the skin such as thermal conductivity and specific heat as well as emissivity when radiation heat transfer is involved. Such parameters can vary with physiological conditions, especially, thermal conductivity of the skin depends largely on the blood perfusion, and thus in vivo measurement is required. The authors have developed a method of non-contact measurement of emissivity and thermal inertia that is defined as square root of the product of thermal conductivity, density and specific heat. The principle of this method is based on measurement at a transient when a constant heat load is applied abruptly to the skin surface by changing the ambient radiation temperature in step-wise fashion. Emissivity and thermal inertia can be determined from the change in radiation from the skin surface at the transient and the slope of the gradual change of the skin surface temperature. By this principle, imaging of thermal parameters was realized. While accurate measurement of small surface temperature change is required, it was shown that high precision thermography systems could be used for this purpose, and we obtained thermal parameters of the skin under normal and suppressed or enhanced blood perfusion. A convenient calibration method was also proposed in which effective ambient radiation temperature can be computed from simultaneously-measured apparent temperatures of two test plates maintained at different temperatures and having two or more different emissivity areas in each plate. In this paper, various in vivo measurement methods of thermal properties of the skin are reviewed briefly, and the method recently developed and improved by authors was shown in detail.