Showing papers by "Universiti Teknologi Malaysia published in 2021"

A Review on Natural Fiber Reinforced Polymer Composite for Bullet Proof and Ballistic Applications.

Abstract: Even though natural fiber reinforced polymer composites (NFRPCs) have been widely used in automotive and building industries, there is still a room to promote them to high-level structural applications such as primary structural component specifically for bullet proof and ballistic applications. The promising performance of Kevlar fabrics and aramid had widely implemented in numerous ballistic and bullet proof applications including for bullet proof helmets, vest, and other armor parts provides an acceptable range of protection to soldiers. However, disposal of used Kevlar products would affect the disruption of the ecosystem and pollutes the environment. Replacing the current Kevlar fabric and aramid in the protective equipment with natural fibers with enhanced kinetic energy absorption and dissipation has been significant effort to upgrade the ballistic performance of the composite structure with green and renewable resources. The vast availability, low cost and ease of manufacturing of natural fibers have grasped the attention of researchers around the globe in order to study them in heavy armory equipment and high durable products. The possibility in enhancement of natural fiber’s mechanical properties has led the extension of research studies toward the application of NFRPCs for structural and ballistic applications. Hence, this article established a state-of-the-art review on the influence of utilizing various natural fibers as an alternative material to Kevlar fabric for armor structure system. The article also focuses on the effect of layering and sequencing of natural fiber fabric in the composites to advance the current armor structure system.

Polylactic Acid (PLA) Biocomposite: Processing, Additive Manufacturing and Advanced Applications.

Abstract: Over recent years, enthusiasm towards the manufacturing of biopolymers has attracted considerable attention due to the rising concern about depleting resources and worsening pollution. Among the biopolymers available in the world, polylactic acid (PLA) is one of the highest biopolymers produced globally and thus, making it suitable for product commercialisation. Therefore, the effectiveness of natural fibre reinforced PLA composite as an alternative material to substitute the non-renewable petroleum-based materials has been examined by researchers. The type of fibre used in fibre/matrix adhesion is very important because it influences the biocomposites’ mechanical properties. Besides that, an outline of the present circumstance of natural fibre-reinforced PLA 3D printing, as well as its functions in 4D printing for applications of stimuli-responsive polymers were also discussed. This research paper aims to present the development and conducted studies on PLA-based natural fibre bio-composites over the last decade. This work reviews recent PLA-derived bio-composite research related to PLA synthesis and biodegradation, its properties, processes, challenges and prospects.

Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

Abstract: The type of materials used in designing and constructing structures significantly affects the way the structures behave. The performance of concrete and steel, which are used as a composite in columns, has a considerable effect upon the structure behavior under different loading conditions. In this paper, several advanced methods were applied and developed to predict the bearing capacity of the concrete-filled steel tube (CFST) columns in two phases of prediction and optimization. In the prediction phase, bearing capacity values of CFST columns were estimated through developing gene expression programming (GEP)-based tree equation; then, the results were compared with the results obtained from a hybrid model of artificial neural network (ANN) and particle swarm optimization (PSO). In the modeling process, the outer diameter, concrete compressive strength, tensile yield stress of the steel column, thickness of steel cover, and the length of the samples were considered as the model inputs. After a series of analyses, the best predictive models were selected based on the coefficient of determination (R2) results. R2 values of 0.928 and 0.939 for training and testing datasets of the selected GEP-based tree equation, respectively, demonstrated that GEP was able to provide higher performance capacity compared to PSO–ANN model with R2 values of 0.910 and 0.904 and ANN with R2 values of 0.895 and 0.881. In the optimization phase, whale optimization algorithm (WOA), which has not yet been applied in structural engineering, was selected and developed to maximize the results of the bearing capacity. Based on the obtained results, WOA, by increasing bearing capacity to 23436.63 kN, was able to maximize significantly the bearing capacity of CFST columns.

Fabrication, Functionalization, and Application of Carbon Nanotube-Reinforced Polymer Composite: An Overview.

Abstract: A novel class of carbon nanotube (CNT)-based nanomaterials has been surging since 1991 due to their noticeable mechanical and electrical properties, as well as their good electron transport properties. This is evidence that the development of CNT-reinforced polymer composites could contribute in expanding many areas of use, from energy-related devices to structural components. As a promising material with a wide range of applications, their poor solubility in aqueous and organic solvents has hindered the utilizations of CNTs. The current state of research in CNTs—both single-wall carbon nanotubes (SWCNT) and multiwalled carbon nanotube (MWCNT)-reinforced polymer composites—was reviewed in the context of the presently employed covalent and non-covalent functionalization. As such, this overview intends to provide a critical assessment of a surging class of composite materials and unveil the successful development associated with CNT-incorporated polymer composites. The mechanisms related to the mechanical, thermal, and electrical performance of CNT-reinforced polymer composites is also discussed. It is vital to understand how the addition of CNTs in a polymer composite alters the microstructure at the micro- and nano-scale, as well as how these modifications influence overall structural behavior, not only in its as fabricated form but also its functionalization techniques. The technological superiority gained with CNT addition to polymer composites may be advantageous, but scientific values are here to be critically explored for reliable, sustainable, and structural reliability in different industrial needs.

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Abstract: Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

The International Soil Moisture Network: Serving Earth system science for over a decade

Abstract: . In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements ( Dorigo et al. , 2011 b , a ) . The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal ( https://ismn.earth/en/ , last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70 % of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.

A novel Harris hawks’ optimization and k-fold cross-validation predicting slope stability

Abstract: Stability of the soil slopes is one of the most challenging issues in civil engineering projects. Due to the complexity and non-linearity of this threat, utilizing simple predictive models does not satisfy the required accuracy in analysing the stability of the slopes. Hence, the main objective of this study is to introduce a novel metaheuristic optimization namely Harris hawks’ optimization (HHO) for enhancing the accuracy of the conventional multilayer perceptron technique in predicting the factor of safety in the presence of rigid foundations. In this way, four slope stability conditioning factors, namely slope angle, the position of the rigid foundation, the strength of the soil, and applied surcharge are considered. Remarkably, the main contribution of this algorithm to the problem of slope stability lies in adjusting the computational weights of these conditioning factors. The results showed that using the HHO increases the prediction accuracy of the ANN for analysing slopes with unseen conditions. In this regard, it led to reducing the root mean square error and mean absolute error criteria by 20.47% and 26.97%, respectively. Moreover, the correlation between the actual values of the safety factor and the outputs of the HHO–ANN (R2 = 0.9253) was more significant than the ANN (R2 = 0.8220). Finally, an HHO-based predictive formula is also presented to be used for similar applications.

Recent advances in butanol production by acetone-butanol-ethanol (ABE) fermentation

Abstract: Butanol can be produced from renewable sources via the acetone-butanol-ethanol (ABE) fermentation route to create biobutanol or from fossil fuel to create petrobutanol. Despite the similar chemical properties of these two forms of butanol, the market penetration of biobutanol is still hindered due to its higher production costs compared to those for petrobutanol. This review article traces the history of the butanol industry and discusses recent advances in butanol production by ABE fermentation, with several novel approaches being highlighted. These approaches include searching for abundant and inexpensive substrates and optimising upstream and downstream processes. As butanol production by ABE fermentation consists of several critical stages, this review article divides the whole process into five significant steps: (1) feedstock selection, (2) upstream, (3) midstream, (4) downstream and (5) final products. Recent progress involving all stages along with their challenges and potential research routes are summarised. Recent progresses in the direct use of ABE as a biofuel are also reviewed in brief. Low butanol yield and end-product toxicity remain the major drawbacks of a typical butanol production by ABE fermentation. For successful biobutanol production, a number of critical issues should be considered. These include the development of clostridial and non-clostridial strains as well as innovative in-situ recovery methods integrated with the ABE fermentation process. Finally, future research direction of butanol production by ABE fermentation is presented in the last section of this article.

Nudging toward diversity in the boardroom: A systematic literature review of board diversity of financial institutions

Abstract: Going beyond the mere gender diversity in the boardroom, this systematic review comprehensively covers the research on board diversity of financial institutions. More specifically, we cover gender diversity, as well as other characteristics of diversity, such as nationality, age, tenure, experience, education, ethnicity, and religion. A systematic literature review was employed using Scopus and Web of Science databases, covering all publications until May 2020, which resulted in 91 studies from 66 top-ranked journals in accounting, finance, and economic fields. We analyze them based on the journal, methodology, research construct questions, and theoretical perspectives. Our results highlight the substantial knowledge gaps and the inconsistent findings of prior studies on several aspects of the field, suggesting avenues for further studies in terms of research designs, settings, scope, and theories. We argue that there is a need to explore other board diversity attributes rather than focusing on the gender diversity of the boards of financial institutions to achieve sustainable development. Also, more work is outlined on topics related to board diversity of financial firms that receive limited attention from scholars, such as (but not limited to) environmental performance, capital structure, intellectual capital, innovation and earnings quality of financial institutions, as well as the indirect effect of policy settings.

Well-designed 2D/2D Ti3C2TA/R MXene coupled g-C3N4 heterojunction with in-situ growth of anatase/rutile TiO2 nucleates to boost photocatalytic dry-reforming of methane (DRM) for syngas production under visible light

Abstract: Well-designed fabrication of 2D/2D g-C3N4/Ti3C2TA/R (CN/TCT) MXene heterojunction with in-situ growth of TiO2-nucleates for boosting photocatalytic dry reforming of methane (DRM) has been investigated. Samples were synthesized through controlled chemical etching process to construct a TiO2 (anatase/rutile) embedded Ti3C2 (TCT) with layer by layer construction of g-C3N4, resulting in higher visible light absorption and proficient charges separation. Etching Ti3AlC2 with HF (49 vol. %) produces more TiO2 compared with HF (39 vol. %), whereas, amount of TiO2 produced was dependent on reaction time. The CN/TCT composite exhibited H2 and CO rate of 51.24 and 73.31 μmole g-1 h-1, much higher than using CN and TCT. This reveals layered Ti3C2 sheets embedded anatase/rutile TiO2, enabling proficient charge carrier separation with light absorption. The effect of feed ratio (CO2/CH4) further confirmed efficient sorption process with good recyclability and would be beneficial to promote the conversion of CO2 and CH4 to syngas under visible light.

Deep neural network and whale optimization algorithm to assess flyrock induced by blasting

Abstract: A wide variety of artificial intelligence methods have been utilized in the prediction of flyrock induced by blasting. This study focuses on developing a model based on deep neural network (DNN) which is an advanced version of artificial neural network (ANN) for the prediction of flyrock based on the data obtained from the Ulu Thiram quarry that is located in Malaysia. To evaluate and document the success and reliability of the new DNN model, an ANN model based on five different data categories from the established database, was also developed and then compared with the DNN model. Based on the obtained results [i.e. coefficient of determination (R2) = 0.9829 and 0.9781, root mean square error (RMSE) = 8.2690 and 9.1119 for DNN and R2 = 0.9093 and 0.8539, RMSE = 19.0795 and 25.05120 for ANN], a significant increase in predicting flyrock is achieved by developing this DNN predictive model. Then, the DNN model was selected as a function for optimizing flyrock by a powerful optimization technique namely whale optimization algorithm (WOA). The WOA was able to minimize the flyrock resulting from blasting and provide a suitable pattern for blasting operations in mines.

A critical review in recent developments of metal-organic-frameworks (MOFs) with band engineering alteration for photocatalytic CO2 reduction to solar fuels

Abstract: Photocatalytic CO2 reduction into valuable chemicals and fuels using solar energy is an attractive approach to solve environmental pollution caused by the emissions of greenhouse gases (mainly CO2) and the fossil fuels depletion. Photocatalysis has been recognized as a solar fuel production system due to its prospective applications in both reducing carbon dioxide emissions and producing of valuable chemicals under solar light. Recently, new, low-cost, crystalline porous materials known as metal-organic frameworks (MOFs) have been introduced as photocatalysts. However, they still face some challenges in terms of synthesis, sunlight utilization and some difficulties in understanding the structure–activity relationship. In this work, recent developments of metal-organic frameworks (MOFs) as a photocatalyst owing to their promising photochemical and unique textural properties for photocatalytic CO2 reduction has been explored. The main objective is to explore the main fundamentals such as the principle, thermodynamics and the mechanism including the heterostructures of charges transfer.The mass transfer theory for photocatalytic CO2 reduction have also been clearly deliberated. The recent developments in synthesis and classifications of MOF-based photocatalysts for increasing the photocatalytic CO2 conversion are discussed in details. Finally, future perspectives of MOF-assisted photocatalytic CO2 reduction have been suggested to provide an insight and important step forward to enhance efficiency with an economic and environmentally sustainable system.

A Comprehensive Review on Advanced Sustainable Woven Natural Fibre Polymer Composites

Abstract: Over the last decade, the progressive application of natural fibres in polymer composites has had a major effect in alleviating environmental impacts. Recently, there is a growing interest in the development of green materials in a woven form by utilising natural fibres from lignocellulosic materials for many applications such as structural, non-structural composites, household utilities, automobile parts, aerospace components, flooring, and ballistic materials. Woven materials are one of the most promising materials for substituting or hybridising with synthetic polymeric materials in the production of natural fibre polymer composites (NFPCs). These woven materials are flexible, able to be tailored to the specific needs and have better mechanical properties due to their weaving structures. Seeing that the potential advantages of woven materials in the fabrication of NFPC, this paper presents a detailed review of studies related to woven materials. A variety of factors that influence the properties of the resultant woven NFRC such as yarn characteristics, fabric properties as well as manufacturing parameters were discussed. Past and current research efforts on the development of woven NFPCs from various polymer matrices including polypropylene, polylactic acid, epoxy and polyester and the properties of the resultant composites were also compiled. Last but not least, the applications, challenges, and prospects in the field also were highlighted.

Thermogravimetric Analysis Properties of Cellulosic Natural Fiber Polymer Composites: A Review on Influence of Chemical Treatments.

Abstract: Natural fiber such as bamboo fiber, oil palm empty fruit bunch (OPEFB) fiber, kenaf fiber, and sugar palm fiber-reinforced polymer composites are being increasingly developed for lightweight structures with high specific strength in the automotive, marine, aerospace, and construction industries with significant economic benefits, sustainability, and environmental benefits. The plant-based natural fibers are hydrophilic, which is incompatible with hydrophobic polymer matrices. This leads to a reduction of their interfacial bonding and to the poor thermal stability performance of the resulting fiber-reinforced polymer composite. Based on the literature, the effect of chemical treatment of natural fiber-reinforced polymer composites had significantly influenced the thermogravimetric analysis (TGA) together with the thermal stability performance of the composite structure. In this review, the effect of chemical treatments used on cellulose natural fiber-reinforced thermoplastic and thermosetting polymer composites has been reviewed. From the present review, the TGA data are useful as guidance in determining the purity and composition of the composites’ structures, drying, and the ignition temperatures of materials. Knowing the stability temperatures of compounds based on their weight, changes in the temperature dependence is another factor to consider regarding the effectiveness of chemical treatments for the purpose of synergizing the chemical bonding between the natural fiber with polymer matrix or with the synthetic fibers.

Comparison of dragonfly algorithm and Harris hawks optimization evolutionary data mining techniques for the assessment of bearing capacity of footings over two-layer foundation soils

Abstract: By assist of novel evolutionary science, the classification accuracy of neural computing is improved in analyzing the bearing capacity of footings over two-layer foundation soils. To this end, Harris hawks optimization (HHO) and dragonfly algorithm (DA) are applied to a multi-layer perceptron (MLP) predictive tool for adjusting the connecting weights and biases in predicting the failure probability using seven settlement key factors, namely unit weight, friction angle, elastic modulus, dilation angle, Poisson’s ratio, applied stress, and setback distance. As the first result, incorporating both HHO and DA metaheuristic algorithms resulted in higher efficiency of the MLP. Moreover, referring to the calculated area under the receiving operating characteristic curve (AUC), as well as the calculated mean square error, the DA-MLP (AUC = 0.942 and MSE = 0.1171) outperforms the HHO-MLP (AUC = 0.915 and MSE = 0.1350) and typical MLP (AUC = 0.890 and MSE = 0.1416). Furthermore, the DA surpassed the HHO in terms of time-effectiveness.

Recent trends in developments of active metals and heterogenous materials for catalytic CO2 hydrogenation to renewable methane: A review

Abstract: Carbon dioxide is a greenhouse gas that is abundantly found in the atmosphere. Therefore, by utilizing carbon dioxide to produce methane would not only reduce the concentration of greenhouse gas in the atmosphere but would also be able to partially fulfill the energy demand. This review highlights current trends in various active metals and heterogeneous catalyst supports used for thermal hydrogenation of CO2 to methane. Initially, the fundamentals, challenges and thermodynamic analysis are discussed to understand the limitations as well as the nature and thermodynamics of the possible reactions. In the mainstream, various classification of active metals, heterogeneous supports and structured materials with their role in selective methane production are discussed. In addition, various operating parameters, engineering aspects, morphologies and physiochemical properties have been thoroughly discussed on the catalytic performance and stability for the methanation reaction. The active metals as well as structure of catalyst have been reported to reduce the activation energy for the CO2 methanation, which is highly beneficial for the progression of the hydrogenation reaction. Finally, the mechanism of the hydrogenation reaction was also reviewed to determine its relationship with the catalyst active site structures.

The Effect of Bottom Profile Dimples on the Femoral Head on Wear in Metal-on-Metal Total Hip Arthroplasty.

Abstract: Wear and wear-induced debris is a significant factor in causing failure in implants. Reducing contact pressure by using a textured surface between the femoral head and acetabular cup is crucial to improving the implant’s life. This study presented the effect of surface texturing as dimples on the wear evolution of total hip arthroplasty. It was implemented by developing finite element analysis from the prediction model without dimples and with bottom profile dimples of flat, drill, and ball types. Simulations were carried out by performing 3D physiological loading of the hip joint under normal walking conditions. A geometry update was initiated based on the patient’s daily routine activities. Our results showed that the addition of dimples reduced contact pressure and wear. The bottom profile dimples of the ball type had the best ability to reduce wear relative to the other types, reducing cumulative linear wear by 24.3% and cumulative volumetric wear by 31% compared to no dimples. The findings demonstrated that surface texturing with appropriate dimple bottom geometry on a bearing surface is able to extend the lifetime of hip implants.

Mapping the research trends on blockchain technology in food and agriculture industry: A bibliometric analysis

Abstract: Blockchain is an undeniably ingenious leading technology that has attracted the attention of academics and practitioners in different industries and disciplines. Due to the increasing interest of academic scholars in agri-food supply chain, this research aims to examine blockchain technology with a focus on the food and agriculture studies. Therefore, a bibliometric technique was adopted to detect the prominent trends and themes in this domain through analysing the substantial articles, authors, countries, and keywords. This research attempts to expand a graphical mapping of the bibliographic information of food and agriculture research using the R package bibliometrix and Visualisation of Similarities (VOS) viewer application. Thus, the present research performed the following analyses: the co-occurrence of author keywords, multiple correspondence analysis, bibliographic coupling analysis, co-citation analysis, and network view map analysis. The findings of the network view map revealed that food and agriculture studies have been categorised into three clusters, and the terms mostly used in the title and abstract of the articles were traceability, transaction, Internet of Things (IoT), safety, and food supply chain.

A Survey of Free Space Optics (FSO) Communication Systems, Links, and Networks

Abstract: The next generation (NG) optical technologies will unveil certain unique features, namely ultra-high data rate, broadband multiple services, scalable bandwidth, and flexible communications for manifold end-users. Among the optical technologies, free space optical (FSO) technology is a key element to achieve free space data transmission according to the requirements of the future technologies, which is due to its cost effective, easy deployment, high bandwidth enabler, and high secured. In this article, we give the overview of the recent progress on FSO technology and the factors that will lead the technology towards ubiquitous application. As part of the review, we provided fundamental concepts across all types of FSO system, including system architecture comprising of single beam and multiple beams. The review is further expanded into the investigation of rain and haze effects toward FSO signal propagation. The final objective that we cover is the scalability of an FSO network via the implementations of hybrid multi-beam FSO system with wavelength division multiplexing (WDM) technology.