Articles authored by UoM staff (Publish in scimago's Q1 journals)

Permanent URI for this collectionhttp://192.248.9.226/handle/123/19622

Note: These articles were published in scimago Q1 journals, which were Q1 journals at the time the article was published.

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Now showing 1 - 20 of 758

item: Article-Full-text
A 3-D coupled Smoothed Particle Hydrodynamics and Coarse-Grained model to simulate drying mechanisms of small cell aggregates
(Elsevier, 2019) Rathnayaka, CM; Karunasena, HCP; Senadeera, W; Polwaththe-Gallage, HN; Gu, YT
Recently, meshfree-based computational modelling approaches have become popular in modelling biological phenomena due to their superior ability to simulate large deforma- tions, multiphase phenomena and complex physics compared to the conventional grid- based methods. In this article, small plant cell aggregates were simulated using a three di- mensional (3-D) Smoothed Particle Hydrodynamics (SPH) and Coarse-Grained (CG) coupled computational approach to predict the morphological behaviour during drying. The model predictions of these cell aggregate models have been compared qualitatively and quantita- tively through comparisons with experimental findings. The results show that the shrink- age and wrinkling behaviour of cell cluster models are in fairly good agreement with real cellular structures. The agreement between the cell aggregate model predictions and the experimental findings are closer in the high and medium moisture content values ( X / X 0 ≥0.3), than highly dried stages ( X / X 0 < 0.3). Further, optimisation and sensitivity studies have been conducted on model parameters such as particle resolution, smoothing length, mass transfer characteristics and wall forces. Overall, the 3-D nature of this model allows it to predict real 3-D morphological changes more realistically compared to the previous meshfree based 2-D cellular drying models. The proposed 3-D modelling approach has a higher potential to be used to model larger plant tissues with complicated physical and mechanical interactions as well as their multiscale interactions.
item: Article-Full-text
A 3-D sparse FIR frustum filter for enhancing broadband plane waves
(IEEE, 2019) Wijesekara, RT; Edussooriya, CUS; Bruton, LT; Agathoklis, P
A 3-D FIR frustum filter having sparse coefficients is proposed for enhancing broadband plane waves received by uniform aperture arrays. Motivated by the design technique of 1-D interpolated FIR filters, the proposed filter is realized by cascading a spatially-upsampled 3-D FIR prototype filter having a frustum-shaped passband and a 3-D FIR masking filter having a parallelepiped passband. Sparsity of the filter coefficients is achieved through the spatial upsampling of the coefficients of the prototype filter and by hard-thresholding the coefficients of both prototype and masking filters. The proposed 3-D FIR frustum filter saves 39:5% multiplications and 66:6% additions compared to the state-of-the-art 3-D FIR frustum filters without degrading the performance in enhancing broadband plane waves.
item: Article-Abstract
A sub-structure condensation technique in finite element analysis for the optimal use of computer memory
Fonseka, MCM
Application of the finite element method in structural analysis frequently involves manipulation of a large amount of data which is obviously a heavy burden on the computer. ‘Condensation’ is a popular technique adopted in such situations to avoid large systems of equations having to be solved, but condensed data may have to be stored for subsequent use at some stage in the analysis. In this regard, it is important to use an efficient condensation technique in the analysis for the proper use of available computer power and avoid any detrimental effects on the computer system. The condensation technique presented here has been developed to accomplish this in incorporating sub-structures in shells of revolution. This technique has the ability of using fixed-size arrays in the computer program irrespective of the size of the sub-structure, thus allowing the optimum use of computer memory.
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Academic research in emerging knowledge-based economies: The case of Sri Lankan construction industry
(Emerald Publishing Limited, 2018) Hadiwattege, C.; Senaratne, S; Sandanayake, Y; Fernando, NG
Purpose – Knowledge-based economies are popular in the present world. Simultaneously, universities are becoming more responsible for leading economic development through research. As a key contributor to the national economy, it is vital for the construction industry to move beyond outdated practices, and hence, reviewing the role of academic research in empowering the construction industry with knowledge is essential. The purpose of this paper is to focus on how relevant theories conceptualise the expected role of academic research in the innovative development of an industry and the specific location in the Sri Lankan construction industry. Design/methodology/approach – Following a comprehensive literature review, empirical data were collected from the Sri Lankan context with a mixed approach informed by a pragmatist philosophical stance. The perspective of academia and industry practitioners were deductively obtained through surveys and inductively explored through qualitative interviews. Findings – This study provides evidence that academic research in Sri Lanka does not contribute effectively to innovative construction management. Due to the absence of industry-focussed knowledge dissemination strategies, the academic–industry relationships are mostly non-research based. The industry lacks in research-informed-decision making, leading to lesser innovations. Research limitations/implications – The research conclusions are more applicable to the developing country construction industry contexts. Practical implications – The research urges the need for improved academic–industry research collaborations and strategic knowledge dissemination movements. Originality/value – The research confirms that academic research is a major integral part of the developing construction industry in a knowledge-based economy. In establishing the expected role of academic research, the research revealed the current practice to be under-located. Hence, the research prescribes the necessary actions; research collaborations in major and subsequent requirements.
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Accurate decision-making for timely washing of substation insulators, based on a pollution model
(Elsevier, 1997) Goto, S; Nakamura, M; Nannyakkara, N; Taniguchi, T
Substation insulators near coastal areas rapidly become polluted due to the salty wind blowing in from the sea. Hazardous levels of pollution deposit cause higher leakage currents under damp conditions, resulting in system blackouts and damage to substations due to flash-overs. This research is aimed at developing a method of reliable decision-making to determine the time at which to wash polluted insulators to avert detrimental conditions. The proposed method consists of modelling the pollution deposits, and deciding on the best time to wash the insulators by using the actual data related to pollution deposits and weather information. The effectiveness of the proposed method is demonstrated by applying it to actual data taken at the Karatsu substation in Japan.
item: Article-Full-text
Accurate whole-night sleep monitoring with dry-contact ear-EEG
(Nature Portfolio, 2019) Mikkelsen, KB; Tabar, YR; Kappel, SL; Christensen, CB; Toft, HO; Hemmsen, MC; Rank, ML; Otto, M; Kidmose, P
Sleep is a key phenomenon to both understanding, diagnosing and treatment of many illnesses, as well as for studying health and well being in general. Today, the only widely accepted method for clinically monitoring sleep is the polysomnography (PSG), which is, however, both expensive to perform and influences the sleep. This has led to investigations into light weight electroencephalography (EEG) alternatives. However, there has been a substantial performance gap between proposed alternatives and PSG. Here we show results from an extensive study of 80 full night recordings of healthy participants wearing both PSG equipment and ear-EEG. We obtain automatic sleep scoring with an accuracy close to that achieved by manual scoring of scalp EEG (the current gold standard), using only ear-EEG as input, attaining an average Cohen's kappa of 0.73. In addition, this high performance is present for all 20 subjects. Finally, 19/20 subjects found that the ear-EEG had little to no negative effect on their sleep, and subjects were generally able to apply the equipment without supervision. This finding marks a turning point on the road to clinical long term sleep monitoring: the question should no longer be whether ear-EEG could ever be used for clinical home sleep monitoring, but rather when it will be.
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Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification
(Springer, 2022) Rathnayake, H; Sumanapala, J; Rukshani, R; Ranathunga, S
Code-mixing and code-switching are frequent features in online conversations. Classification of such text is challenging if one of the languages is low-resourced. Fine-tuning pre-trained multilingual language models is a promising avenue for code-mixed text classification. In this paper, we explore adapter-based fine-tuning of PMLMs for CMCS text classification. We introduce sequential and parallel stacking of adapters, continuous fine-tuning of adapters, and training adapters without freezing the original model as novel techniques with respect to single-task CMCS text classification. We also present a newly annotated dataset for the classification of Sinhala–English code-mixed and code-switched text data, where Sinhala is a low-resourced language. Our dataset of 10000 user comments has been manually annotated for five classification tasks: sentiment analysis, humor detection, hate speech detection, language identification, and aspect identification, thus making it the first publicly available Sinhala–English CMCS dataset with the largest number of task annotation types. In addition to this dataset, we also tested our proposed techniques on Kannada–English and Hindi–English datasets. These experiments confirm that our adapter-based PMLM fine-tuning techniques outperform or are on par with the basic fine-tuning of PMLM models.
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Adapting approaching proxemics of a service robot based on physical user behavior and user feedback
(Springer Netherlands, 2022) Samarakoon, SMBP; Muthugala, MAVJ; Jayasekara, AGBP; Elara, MR
Service robots with social interactive features are developed to cater to the demand in various application domains. These robots often need to approach toward users to accomplish typical day-to-day services. Thereby, the approaching behavior of a service robot is a crucial factor in developing social interactivity between users and the robot. In this regard, a robot should be capable of maintaining proper proxemics at the termination position of an approach that improves the comfort of users. Proxemics preferences of humans depend on physical user behavior as well as personal factors. Therefore, this paper proposes a novel method to adapt the termination position of an approach based on physical user behavior and user feedback. Physical behavior of a user is perceived by the robot through analyzing skeletal joint movements of the user. These parameters are taken as inputs for a fuzzy neural network that determines the appropriate interpersonal distance. The preference of a user is learnt by modifying the internal parameters of the fuzzy neural network based on user feedback. A user study has been conducted to compare and contrast behavior of the proposed system over the existing approaches. The outcomes of the user study confirm a significant improvement in user satisfaction due to the adaptation toward users based on feedback.
item: Article-Full-text
Adaptive linear prediction for optimal control of wind turbines
(IEEE, 2017) Narayana, M; Sunderland, KM; Putrus, G; Conlon, MF
In order to obtain maximum power output of a Wind Energy Conversion System (WECS), the rotor speed needs to be optimised for a particular wind speed. However, due to inherent inertia, the rotor of a WECS cannot react instantaneously according to wind speed variations. As a consequence, the performance of the system and consequently the wind energy conversion capability of the rotor are negatively affected. This study considers the use of a time series Adaptive Linear Prediction (ALP) technique as a means to improve the performance and conversion efficiency of wind4 turbines. The ALP technique is introduced as a real time control reference to improve optimal control of wind turbines. In this study, a wind turbine emulator is developed to evaluate the performance of the predictive control strategy. In this regard, the ALP reference control method was applied as a means to control the torque/speed of the emulator. The results show that the employment of a predictive technique increases energy yield by almost 5%.
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Additive manufacturing of recycled plastics
(Springer, 2023-05) Jayawardane, H; Davies, IJ; Gamage, JR; John, M; Biswas, WK
Plastic materials have been widely used to replace metals in functional parts due to their lower cost and comparable technical properties. However, the increasing use of virgin plastic material in consumer and industrial applications has placed a significant burden on waste management due to the volume of waste created and the potential negative effects of its end-of-life processing. There is a need to adopt circular economy strategies such as plastic recycling within industrial applications in order to reduce this significant waste management pressure. The present study used recycled polylactic acid (PLA) material as a feedstock for the 3D printing of a centrifugal semi-open pump impeller. The technical performance of 3D printed recycled PLA material and virgin PLA material was compared in this study. The environmental impacts for technically feasible impellers were assessed through the environmental life cycle assessment, while costs were evaluated by life cycle costing. The results were incorporated into a techno-eco-efficiency framework to compare the technical properties, environmental impacts, and costs. The social impacts of additive manufacturing and recycled feedstock material were also explored. The technical assessment results indicated that tensile strength, fatigue strength, density, and hardness decreased with recycled material content compared to virgin material. Microscopy of the fracture surfaces revealed the presence of slightly higher porosity and defects in recycled specimens, which could result in slightly lower technical properties. However, the recycled material was accepted for further ecological analysis as it offered higher pumping performance when compared to the original component and could reduce the burden on virgin material-based production and waste material disposal. Importantly, the results showed that 3D printed recycled PLA impellers are more eco-efficient when compared to 3D printed virgin PLA impellers.
item: Article-Full-text
Adequacy evaluation of composite power systems using an evolutionary swarm algorithm
(IEEE, 2022) Amarasinghe, PAGM; Abeygunawardane, SK; Singh, C
The generation and transmission capacities of many power systems in the world are significantly increasing due to the escalating global electricity demand. Therefore, the adequacy evaluation of power systems has become a computationally challenging and time-consuming task. Recently, population-based intelligent search methods such as Genetic Algorithms (GAs) and Binary Particle Swarm Optimization (BPSO) have been successfully employed for evaluating the adequacy of power generation systems. In this work, the authors propose a novel Evolutionary Swarm Algorithm (ESA) for the adequacy evaluation of composite generation and transmission systems. The random search guiding mechanism of the ESA is based on the underlying philosophies of GAs and BPSO. The main objective of the ESA is to find out the most probable system failure states that significantly affect the adequacy of composite systems. The identified system failure states can be directly used to estimate the system adequacy indices. The proposed ESA-based framework is used to evaluate the adequacy of the IEEE Reliability Test System (RTS). The estimated annualized and annual adequacy indices such as Probability of Load Curtailments (PLC), Expected Duration of Load Curtailments (EDLC), Expected Energy Not Supplied (EENS) and Expected Frequency of Load Curtailments (EFLC) are compared with those obtained using Sequential Monte Carlo Simulation (SMCS), GA and BPSO. The results show that the accuracy, computational efficiency, convergence characteristics, and precision of the ESA outperform those of GA and BPSO. Moreover, compared to SMCS, the ESA can estimate the adequacy indices in a more time-efficient manner.
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An Advisor-Based Architecture for a Sample-Efficient Training of Autonomous Navigation Agents with Reinforcement Learning
(2023) Wijesinghe, R. D.; Tissera, D.; Vithanage, M. K.; Xavier, A.; Fernando, S; Samarawickrama, J.
Recent advancements in artificial intelligence have enabled reinforcement learning (RL) agents to exceed human-level performance in various gaming tasks. However, despite the state-of-the-art performance demonstrated by model-free RL algorithms, they suffer from high sample complexity. Hence, it is uncommon to find their applications in robotics, autonomous navigation, and self-driving, as gathering many samples is impractical in real-world hardware systems. Therefore, developing sample-efficient learning algorithms for RL agents is crucial in deploying them in real-world tasks without sacrificing performance. This paper presents an advisor-based learning algorithm, incorporating prior knowledge into the training by modifying the deep deterministic policy gradient algorithm to reduce the sample complexity. Also, we propose an effective method of employing an advisor in data collection to train autonomous navigation agents to maneuver physical platforms, minimizing the risk of collision. We analyze the performance of our methods with the support of simulation and physical experimental setups. Experiments reveal that incorporating an advisor into the training phase significantly reduces the sample complexity without compromising the agent’s performance compared to various benchmark approaches. Also, they show that the advisor’s constant involvement in the data collection process diminishes the agent’s performance, while the limited involvement makes training more effective.
item: Article-Full-text
Aesthetics and ethics in engineering: Insights from polanyi
(Springer Science+Business Media., 2011) Dias, P
Polanyi insisted that scientific knowledge was intensely personal in nature, though held with universal intent. His insights regarding the personal values of beauty and morality in science are first enunciated. These are then explored for their relevance to engineering. It is shown that the practice of engineering is also governed by aesthetics and ethics. For example, Polanyi’s three spheres of morality in science—that of the individual scientist, the scientific community and the wider society—has parallel entities in engineering. The existence of shared values in engineering is also demonstrated, in aesthetics through an example that shows convergence of practitioner opinion to solutions that represent accepted models of aesthetics; and in ethics through the recognition that many professional engineering institutions hold that the safety of the public supersedes the interests of the client. Such professional consensus can be seen as justification for studying engineering aesthetics and ethics as inter-subjective disciplines.
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After-sales services of home appliances: Evidence from Sri Lanka
(Wiley-Blackwell Publishing Ltd, 2016) Wickramasinghe, V; Mathusinghe, K
The provision of after-sales services is considered as a source of product differentiation leading to competitive advantage of a firm. As a consequence, there is a need of monitoring and measuring the activities of after-sales service departments to ensure that the objectives of their existence are satisfied. Yet, it is very rare to find previous studies that investigated after-sales service provision. We investigated different dimensions of after-sales service provision of home appliances in the Sri Lankan context. The study operationalized different dimensions of after-sales service provision from three different perspectives and used multiple parameters to evaluate the nature of provision. Introduction In the present day, the retailers of home appliances do not consider their active role end with an actual sale of a product (Levitt, 1983); they provide a set of supporting after-sales services to customers. After-sales services include support services that are provided to the customer after the product has been sold and delivered such as technical advice for use, maintenance and the provision of spare parts and repair services (Vitasek, 2006; Saccani et al., 2007; Low, 2013) to ensure a trouble-free use over the useful lifespan of the appliance (Loomba, 1998; Rigopoulou et al., 2008). Previous research identifies after-sales services as a part of customer relationship management (Ramaswamy et al., 2002; Vitasek, 2006; Shaharudin et al., 2009) leading to increased customer loyalty and brand reputation (Saccani et al., 2006; Shaharudin et al., 2009). According to some previous research (such as Alexander et al., 2002; Wise and Baumgartner, 1999), profit margin that can be generated with the provision of aftersales services is higher compared to a product sale without it. Hence, the provision of after-sales services is considered as a source of product differentiation leading to competitive advantage of a firm (Levitt, 1983; Mathe and Shapiro, 1990; Ramaswamy et al., 2002; Low, 2013). Due to this emergent importance of the provision of after-sales services, there is a trend of after-sales service departments to evolve as a strategic driver ensuring increased customer satisfaction, retention, and market growth (Cavalieri et al., 2007). As a consequence, there is a need of monitoring and measuring the activities of aftersales service departments to ensure that the objectives of their existence are
item: Article-Full-text
An agent-based approach for modeling and simulation of human resource management as a complex system: Management strategy evaluation
(Elsevier, 2020) Somarathna, KUS
Human resources management (HRM) is the strategic approach of managing people in organizations. HRM can be naturally represented as a complex system of autonomous human agents, whose interactions are influenced by mutually reinforcing HRM strategies, policies, and practices. Stochastic and dynamic human interactions could lead to emergent phenomena of organizational performance in the long-term. Therefore, decision-making in the HRM complex system could be challenging for the human mind due to its limited capacity to map multiple relationships, execute stochastic and dynamic interactions, consider trade-offs arising from competing objectives, integrate intermediate information generated by feedback loops, and visualize the impact on multiple performance metrics. Existing HRM decision-making models rely on analytical methods, survey-based statistical approaches, and aggregate rate-based System Dynamics simulation, assuming homogeneous populations, which leads to limitations in capturing dynamics of heterogeneous populations arising from micro-level interactions. Therefore, we propose an agent-based methodology to model HRM as a complex system, in which alternate management strategies could be simulated by way of agent interactions while observing the emergence of organizational performance. The model has been simulated to observe the long-term influences of alternate recruitment strategies on workforce fluctuations, demographics, skill profile, loyalty, and costs under distinct employee turnover rates. We propose that an agent-based methodology is more realistic in modeling micro-level employee interactions of an HRM system and possibly the ideal avenue to rehearse management strategy when experimentation on the real system is constrained. Fundamentally, the proposed model serves as a decision support system for HRM decision-making.
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An aggregate demand model for intercity passenger travel in Sri Lanka
(Kluwer Academic Publishers, 1998) Wirasinghe, SC; Kumarage, AS
Inspite of the inherent weaknesses in aggregate demand models, they continue to be used in everyday applications, especially in developing countries. The largely data intensive disaggregate model preclude its application in many cases. This paper attempts the formulation and calibration of an aggregate total demand model for estimating inter-district passenger travel by public transport in Sri Lanka. In its process, an investigation is made of the common problems in the aggregate approach while examining possible remedial measures to improve the accuracy and (hence) the usability of the aggregate model. It is argued that commonly used variables and functional forms are inappropriate for making accurate estimates in developing countries. Consequently, the model calibration is shown to incorporate variables representing urbanisation, under-development, transfers, a mode-abstract cost function and intrinsic features. The necessity for functional form for each variable to be based on behavioral assumptions that are tested using the Box-Cox transformation for ensuring the best fit of the data is also observed. Although, the model form was calibrated for Sri Lanka, the model is generalised in order for its applications to other countries as well as, both, inter-district and intercity travel demand estimation.
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Agricultural biomass-based power generation potential in Sri Lanka: A techno-economic analysis
(MDPI, 2022) Illankoon, WAMAN; Milanese, C; Girella, A; Rathnasiri, PG; Sudesh, KHM; Llamas, MM; Collivignarelli, MC; Sorlini, S
Worldwide energy costs have grown in recent years due to the dwindling global fossil fuel resources and the increased reliance on them for global energy production. This is a common scenario in many nations, including Sri Lanka. As a developing country, Sri Lanka should encourage the diversification of its renewable energy supplies using locally available resources. In this regard, Sri Lanka can promote the use of agricultural residues for energy generation. The present work explores the energy potential of the solid waste generated by the rice industry: rice straw (RS) and rice husk (RH). A new approach was developed using statistical data on rice production and paddy cultivation in each district of the island. The obtained data were integrated into a geographic information system (GIS) to provide geo-referenced results. A physico-chemical characterization of the RS and RH was conducted to correlate the properties of raw materials to their potential energy generation. As an energy generation technology, the grate-fired combustion boiler accompanied by steam turbine cycle (GFC/ST) was selected. Our findings show that the total energy capacity using by-products of the rice industry is estimated to be 2129.24 ktoe/year of primary energy, with a capacity of 977 Mwe, producing 5.65 TWh of electricity annually. An economic analysis shows ten districts have a high profit index (PI > 1). The districts with the highest PI values are Anuradhapura, Ampara, Polonnaruwa, and Kurunegala, with annual energy potentials of 286 ktoe, 279 ktoe, 231 ktoe, and 160 ktoe, respectively. This work aims to aid future policy decisions by identifying potential districts in which to develop infrastructure for energy generation using agricultural waste, thus reducing net greenhouse gas emissions (GHG) of Sri Lanka.
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Air pollutant dispersion around high-rise building cluster forms: the case of Port City, Colombo, Sri Lanka Malithie Vidanapathirana
(National Library of Medicine, 2023) Vidanapathirana, M; Perera, N; Emmanuel, R; Coorey, S
Air quality in dense urban environments is a growing concern, especially in rapidly developing cities. In the face of growing traffic associated with urbanization, there is evidence for high levels of pollutant concentration at street level which is influenced by building forms. In this paper, we examine the potential effects of high-rise, cluster developments permitted by the local planning authorities in the newly established Port City development in Colombo, Sri Lanka. We designed possible building forms based on specific guidelines for the development in terms of plot coverage, floor area ratio, and maximum height. The three-dimensional building clusters were simulated using the RANS k-epsilon turbulence model, to determine pollutant dispersion of a complex street formation in a high dense high-rise building cluster, within the development and the surrounding context (existing Colombo). Results show that in a complex building cluster there is no single building form which will provide uniformly better pollution dispersion across the development. Flow patterns are significantly affected by the building morphology, context, and ambient wind direction. Thus, individual building permits should be considered in their contexts and surrounding geometries need to be accounted for.
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All-organic, conductive and biodegradable yarns from core-shell nanofibers through electrospinning
(RSC Advance, 2020) Weerasinghe, VT; Dissanayake, DGK; Tissera, ND; Wijesena, RN; Wanasekara, ND; Perera, WPTD
Electrically conductive and biodegradable materials are desired for a range of applications in wearable electronics to address the growing ecological problem of e-waste. Herein, we report on the design and fabrication of all-organic, conductive and biodegradable nanofibrous core–shell yarn produced by in situ polymerization of aniline on the surface of electrospun poly(ε-caprolactone) nanofibers. The effect of concentration of aniline monomer on the morphology and resistivity of deposited polyaniline layer was investigated. The electrical resistance changed almost instantaneously with the strain for multiple stretch and recovery cycles. This rapid and sensitive response to mechanical loading and unloading is promising to validate the possibility of using the conductive yarns as strain sensors for monitoring human motion. Increasing the number of plies of yarn to three resulted in a three-fold reduction of the resistance. The twisted plied yarns were incorporated into fabric by stitching to demonstrate their use as a wearable electrode for capacitive sensors. This approach presents an early step in realizing all-organic conductive biodegradable nanofibrous yarns for biodegradable smart textiles.
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Analyses of structural robustness of prefabricated modular buildings: A case study on mid-rise building configurationm
(MDPI, 2022) Munmulla, T; Navaratnam, S; Thamboo, J; Ponnampalam, T; Damruwan, H-GH; Tsavdaridis, KD; Zhang, G
The limited knowledge of the behaviour of modular buildings subjected to different loading scenarios and thereby lack of design guidelines hinder the growth of modular construction practices despite its widespread benefits. In order to understand the robustness of modular building systems, a case study was carried out using the numerical analysis method to evaluate the robustness of ten-storey braced frame modular buildings with different modular systems. Two types of modules with different span lengths were used in the assessments. Then, three different column removal scenarios involving (1) removal of a corner column, (2) an edge column, and (3) an interior column were employed to assess the robustness of modular building cases considered. The forces generated in the elements in close proximity to the removed column were verified to assess the robustness of each building case analysed. The results showed that the change in damping ratio from 1% to 5% has no significant influence on the robustness of the modular building cases considered, where the zero-damping leads to collapse. Corner column removal has not considerably affected the robustness of the braced modular building cases studied. The axial capacity ratio of columns is 0.8 in dynamic column removal in the building subjected to corner column removal, while in interior column removal capacity ratio reached up to 1.2, making it the most vulnerable failure scenario. Doubling the span of the modules (from 2.5 m to 5 m) has influenced the robustness of the buildings by increasing the axial forces of columns up to 30% in the interior column removal scenario. Thus, this study highlights that proper guidelines should be made available to assess the robustness of modular building systems to effectively design against progressive collapse.