A new data driven long-term solar yield analysis model of photovoltaic power plants
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
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- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
A secured framework for SDN-based edge computing in IoT-enabled healthcare system
- Authors: Li, Junxia , Cai, Jinjin , Khan, Fazlullah , Rehman, Ateeq , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 135479-135490
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- Description: The Internet of Things (IoT) consists of resource-constrained smart devices capable to sense and process data. It connects a huge number of smart sensing devices, i.e., things, and heterogeneous networks. The IoT is incorporated into different applications, such as smart health, smart home, smart grid, etc. The concept of smart healthcare has emerged in different countries, where pilot projects of healthcare facilities are analyzed. In IoT-enabled healthcare systems, the security of IoT devices and associated data is very important, whereas Edge computing is a promising architecture that solves their computational and processing problems. Edge computing is economical and has the potential to provide low latency data services by improving the communication and computation speed of IoT devices in a healthcare system. In Edge-based IoT-enabled healthcare systems, load balancing, network optimization, and efficient resource utilization are accurately performed using artificial intelligence (AI), i.e., intelligent software-defined network (SDN) controller. SDN-based Edge computing is helpful in the efficient utilization of limited resources of IoT devices. However, these low powered devices and associated data (private sensitive data of patients) are prone to various security threats. Therefore, in this paper, we design a secure framework for SDN-based Edge computing in IoT-enabled healthcare system. In the proposed framework, the IoT devices are authenticated by the Edge servers using a lightweight authentication scheme. After authentication, these devices collect data from the patients and send them to the Edge servers for storage, processing, and analyses. The Edge servers are connected with an SDN controller, which performs load balancing, network optimization, and efficient resource utilization in the healthcare system. The proposed framework is evaluated using computer-based simulations. The results demonstrate that the proposed framework provides better solutions for IoT-enabled healthcare systems. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramaniam” is provided in this record**
A Survey on Behavioral Pattern Mining from Sensor Data in Internet of Things
- Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
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- Description: The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services. The sensor data streams generated from these applications are largely dynamic, heterogeneous, and often geographically distributed over large areas. For high-value use in business, industry and services, these data streams must be mined to extract insightful knowledge, such as about monitoring (e.g., discovering certain behaviors over a deployed area) or network diagnostics (e.g., predicting faulty sensor nodes). However, due to the inherent constraints of sensor networks and application requirements, traditional data mining techniques cannot be directly used to mine IoT data streams efficiently and accurately in real-time. In the last decade, a number of works have been reported in the literature proposing behavioral pattern mining algorithms for sensor networks. This paper presents the technical challenges that need to be considered for mining sensor data. It then provides a thorough review of the mining techniques proposed in the recent literature to mine behavioral patterns from sensor data in IoT, and their characteristics and differences are highlighted and compared. We also propose a behavioral pattern mining framework for IoT and discuss possible future research directions in this area. © 2013 IEEE.
An adaptive and flexible brain energized full body exoskeleton with IoT edge for assisting the paralyzed patients
- Authors: Jacob, Sunil , Alagirisamy, Mukil , Menon, Varun , Kumar, B. Manoj , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 100721-100731
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- Description: The paralyzed population is increasing worldwide due to stroke, spinal code injury, post-polio, and other related diseases. Different assistive technologies are used to improve the physical and mental health of the affected patients. Exoskeletons have emerged as one of the most promising technology to provide movement and rehabilitation for the paralyzed. But exoskeletons are limited by the constraints of weight, flexibility, and adaptability. To resolve these issues, we propose an adaptive and flexible Brain Energized Full Body Exoskeleton (BFBE) for assisting the paralyzed people. This paper describes the design, control, and testing of BFBE with 15 degrees of freedom (DoF) for assisting the users in their daily activities. The flexibility is incorporated into the system by a modular design approach. The brain signals captured by the Electroencephalogram (EEG) sensors are used for controlling the movements of BFBE. The processing happens at the edge, reducing delay in decision making and the system is further integrated with an IoT module that helps to send an alert message to multiple caregivers in case of an emergency. The potential energy harvesting is used in the system to solve the power issues related to the exoskeleton. The stability in the gait cycle is ensured by using adaptive sensory feedback. The system validation is done by using six natural movements on ten different paralyzed persons. The system recognizes human intensions with an accuracy of 85%. The result shows that BFBE can be an efficient method for providing assistance and rehabilitation for paralyzed patients. © 2013 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**
An efficient forward propagation of multiple random fields using a stochastic Galerkin scaled boundary finite element method
- Authors: Mathew, Tittu , Pramod, A. L. N. , Ooi, Ean Tat , Natarajan, Sundararajan
- Date: 2020
- Type: Text , Journal article
- Relation: Computer Methods in Applied Mechanics and Engineering Vol. 367, no. (2020), p.
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- Description: This paper serves to extend the existing literature on the Stochastic Galerkin Scaled Boundary Finite Element Method (SGSBFEM) in two ways. The first part of this work deals with the formulation of multiple non-correlated Gaussian random fields using the conventional Karhunen–Loéve expansion technique and its forward propagation through the Spectral Stochastic Scaled Boundary Finite Element setting using the polynomial surface fit method in terms of the scaled boundary coordinates. The advantages in adopting such a forward propagation technique in capturing the statistical moments of Quantities of Interest (QoI) across the domain, are highlighted using carefully chosen linear elastic problems having large to least correlated random fields as inputs. The second contribution is the extension of the proposed forward Uncertainty Quantification (UQ) to take into account multiple independent random fields, followed by Polynomial Chaos Expansion (PCE) based sensitivity analysis. Both the computational efficiency and the accuracy of the proposed framework under different input random field correlation settings are elaborated upon by comparing their results against that obtained using the current existing SGSBFEM in the literature. Moreover, the stochastic results are validated for all the numerical examples using the Monte Carlo method. © 2020 Elsevier B.V.
An enhancement to the spatial pyramid matching for image classification and retrieval
- Authors: Karmakar, Priyabrata , Teng, Shyh , Lu, Guojun , Zhang, Dengsheng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 22463-22472
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- Description: Spatial pyramid matching (SPM) is one of the widely used methods to incorporate spatial information into the image representation. Despite its effectiveness, the traditional SPM is not rotation invariant. A rotation invariant SPM has been proposed in the literature but it has many limitations regarding the effectiveness. In this paper, we investigate how to make SPM robust to rotation by addressing those limitations. In an SPM framework, an image is divided into an increasing number of partitions at different pyramid levels. In this paper, our main focus is on how to partition images in such a way that the resulting structure can deal with image-level rotations. To do that, we investigate three concentric ring partitioning schemes. Apart from image partitioning, another important component of the SPM framework is a weight function. To apportion the contribution of each pyramid level to the final matching between two images, the weight function is needed. In this paper, we propose a new weight function which is suitable for the rotation-invariant SPM structure. Experiments based on image classification and retrieval are performed on five image databases. The detailed result analysis shows that we are successful in enhancing the effectiveness of SPM for image classification and retrieval. © 2013 IEEE.
Application of scaled boundary finite element method for delamination analysis of composite laminates using cohesive zone modelling
- Authors: Garg, Nikhil , Prusty, Gangadhara , Ooi, Ean Tat , Song, Chongmin , Pearce, Garth , Phillips, Andrew
- Date: 2020
- Type: Text , Journal article
- Relation: Composite Structures Vol. 253, no. (2020), p. 1-10
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- Description: In this paper, the scaled boundary finite element method (SBFEM) is evaluated for two-dimensional delamination analysis of composite laminates. The delamination phenomenon was studied using cohesive zone modelling (CZM). A bi-linear (triangular) traction-separation law was used to describe the interface behaviour, which was modelled using zero-thickness interface elements. Local arc-length solution technique was used to solve the non-linearity due to the interface behaviour. In this research, pure Mode I and Mode II as well as mixed mode delamination studies have been conducted using the SBFEM formulation. A variety of numerical experiments were performed. Good agreement was observed between the SBFEM simulation and the available numerical and experimental results in the open literature. A comparison between the SBFEM and other traditional methods shows that the presented formulation can solve the same physical problem with a reduction in the computational cost by more than half. The study highlights the advantages of SBFEM over other methods for modelling delamination in composite laminates using CZM.
- Description: This project is conducted within the ARC Training Centre for Automated Manufacture of Advanced Composites (IC160100040), supported by the Commonwealth of Australia under the Australian Research Council's Industrial Transformation Research Program.
Dual cost function model predictive direct speed control with duty ratio optimization for PMSM drives
- Authors: Liu, Ming , Hu, Jiefeng , Chan, Ka , Or, Siu , Ho, Siu , Xu, Wenzheng , Zhang, Xian
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 126637-126647
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- Description: Traditional speed control of permanent magnet synchronous motors (PMSMs) includes a cascaded speed loop with proportional-integral (PI) regulators. The output of this outer speed loop, i.e. electromagnetic torque reference, is in turn fed to either the inner current controller or the direct torque controller. This cascaded control structure leads to relatively slow dynamic response, and more importantly, larger speed ripples. This paper presents a new dual cost function model predictive direct speed control (DCF-MPDSC) with duty ratio optimization for PMSM drives. By employing accurate system status prediction, optimized duty ratios between one zero voltage vector and one active voltage vector are firstly deduced based on the deadbeat criterion. Then, two separate cost functions are formulated sequentially to refine the combinations of voltage vectors, which provide two-degree-of-freedom control capability. Specifically, the first cost function results in better dynamic response, while the second one contributes to speed ripple reduction and steady-state offset elimination. The proposed control strategy has been validated by both Simulink simulation and hardware-in-the-loop (HIL) experiment. Compared to existing control methods, the proposed DCF-MPDSC can reach the speed reference rapidly with very small speed ripple and offset. © 2013 IEEE.
- Description: This work was supported in part by the Research Grants Council of the Hong Kong Special Administrative Region (HKSAR) Government under Grant R5020-18, and in part by the Innovation and Technology Commission of the HKSAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center under Grant K-BBY1.
Electric vehicle participated electricity market model considering flexible ramping product provisions
- Authors: Zhang, Xian , Hu, Jiefeng , Wang, Huaizhi , Wang, Guibin , Chan, Ka , Qiu, Jing
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 56, no. 5 (2020), p. 5868-5879
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- Description: This article studies electric vehicle (EV) potential to participate in the energy market and provide flexible ramping products (FRPs). EV traffic flows are predicted by the deep belief network, and the availability of flexible EVs is estimated based on the predicted EV traffic flows. Then, a novel market mechanism in distribution system is proposed to encourage the dispatchable EV demand to react to economic signals and provide ramping services. The designed market model is based on locational marginal pricing of energy and marginal pricing of FRPs. System ramping capacity constraints and EV operation constraints are incorporated in the proposed model to achieve the balance between the system social cost minimization and the EV traveling convenience. Moreover, typical uncertainties are considered by the scenario-based approach. Finally, simulations are conducted to verify the effectiveness of the established model and demonstrate the contributions of EVs to the system reliability and flexibility. © 1972-2012 IEEE.
- Description: ITIAC: Funding details: JCYJ20170817100412438, 2019-AAAE-1307, JCYJ20190808141019317
Epidemiology of injury and illness in 153 Australian international-level rowers over eight international seasons
- Authors: Trease, Larissa , Wilkie, Kellie , Lovell, Greg , Drew, Michael , Hooper, Ivan
- Date: 2020
- Type: Text , Journal article
- Relation: British Journal of Sports Medicine Vol. 54, no. 21 (2020), p. 1288-1293
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- Description: Aim To report the epidemiology of injury and illness in elite rowers over eight seasons (two Olympiads). Methods All athletes selected to the Australian Rowing Team between 2009 and 2016 were monitored prospectively under surveillance for injury and illness. The incidence and burden of injury and illness were calculated per 1000 athlete days (ADs). The body area, mechanism and type of all injuries were recorded and followed until the resumption of full training. We used interrupted time series analyses to examine the association between fixed and dynamic ergometer testing on rowers' injury rates. Time lost from illness was also recorded. Results All 153 rowers selected over eight seasons were observed for 48 611 AD. 270 injuries occurred with an incidence of 4.1-6.4 injuries per 1000 AD. Training days lost totalled 4522 (9.2% AD). The most frequent area injured was the lumbar region (84 cases, 1.7% AD) but the greatest burden was from chest wall injuries (64 cases, 2.6% AD.) Overuse injuries (n=224, 83%) were more frequent than acute injuries (n=42, 15%). The most common activity at the time of injury was on-water rowing training (n=191, 68). Female rowers were at 1.4 times the relative risk of chest wall injuries than male rowers; they had half the relative risk of lumbar injuries of male rowers. The implementation of a dynamic ergometers testing policy (Concept II on sliders) was positively associated with a lower incidence and burden of low back injury compared with fixed ergometers (Concept II). Illness accounted for the greatest number of case presentations (128, 32.2% cases, 1.2% AD). Conclusions Chest wall and lumbar injuries caused training time loss. Policy decisions regarding ergometer testing modality were associated with lumbar injury rates. As in many sports, illness burden has been under-recognised in elite Australian rowers. ©
Extension of the scaled boundary finite element method to treat implicitly defined interfaces without enrichment
- Authors: Natarajan, Sundararajan , Dharmadhikari, Prasad , Annabattula, Ratna , Zhang, Junqi , Ooi, Ean , Song, Chongmin
- Date: 2020
- Type: Text , Journal article
- Relation: Computers and Structures Vol. 229, no. (2020), p.
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- Description: In this paper, the scaled boundary finite element method (SBFEM) is extended to solve the second order elliptic equation with discontinuous coefficients and to treat weak discontinuities. The salient feature of the proposed technique is that: (a) it requires only the boundary to be discretized and (b) does not require the interface to be discretized. The internal boundaries are represented implicitly by the level set method and the zero level sets are used to identify the different regions. In the regions containing the interface, edges along the boundary are assigned different material properties based on their location with respect to the zero level set. A detailed discussion is provided on the implementation aspects, followed by a few example problems in both two and three dimensions to show the robustness, accuracy and effectiveness of the proposed approach in modelling materials with interfaces. The proposed technique can easily be integrated to any existing finite element code. © 2019 Elsevier Ltd
Impact of PV plant and load models on system strength and voltage recovery of power systems
- Authors: Alshareef, Abdulrhman , Shah, Rakibuzzaman , Mithulananthan, Nadarajah
- Date: 2020
- Type: Text , Conference proceedings
- Relation: 2nd International Conference on Smart Power and Internet Energy Systems, SPIES 2020; Bangkok, Thailand; 15th-18th September 2020 p. 263-268
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- Description: In recent years, non-conventional inverter-based sources, namely, wind, PV, and others have emerged as excellent alternatives to the traditional synchronous machine for power generation. It has also been reported that the so-called system strength may be reduced with high penetration of non-conventional generations (NCGs). A number of methods have been used to assess system strength which may not reflect the interdependency or reciprocal influence of various factors affecting it. This paper presents a thorough assessment to quantify the implications of and the interaction of various factors affecting system strength, with the voltage recovery index being used as a quantification tool. © 2020 IEEE.
In vitro and in vivo toxicity and biodistribution of paclitaxel-loaded cubosomes as a drug delivery nanocarrier : a case study using an A431 skin cancer xenograft model
- Authors: Zhai, Jiali , Tan, Fiona , Luwor, Rodney , Srinivasa Reddy, T. , Ahmed, Nuzhat , Drummond, Calum , Tran, Nhiem
- Date: 2020
- Type: Text , Journal article
- Relation: ACS Applied Bio Materials Vol. 3, no. 7 (2020), p. 4198-4207
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- Description: Cubosomes with an internal three-dimensional (3D) periodic and porous particulate nanostructure have emerged as a promising drug delivery system for hydrophobic small molecules as well as large biomolecules over the past several decades. Limited understanding of their safety profiles and biodistribution, however, hinders clinical translation. This study used monoolein-based cubosomes stabilized by Pluronic F127 and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[maleimide(polyethylene glycol)] polymers to encapsulate paclitaxel (PTX) as a model drug and investigated the in vitro cytotoxicity, in vivo acute response, and whole body biodistribution of the developed nanoparticles. Comparison of the PTX and nanoparticle cytotoxicity in two-dimensional and 3D spheroid cell models revealed distinct differences, with the cells in the 3D model found to be more tolerable to unloaded PTX as well as the PTX-loaded nanoparticle form. One-time intraperitoneal (i.p.) injection of unloaded cubosomes were generally well tolerated up to 400 mg/kg. Using the A431 skin cancer xenograft model, in vivo imaging studies showed the preferential accumulation of PTX-loaded cubosomes at the tumor sites following i.p. injection. Lastly, average tumor size was reduced by approximately 50% in the nanoparticle-based treatment group compared to the unloaded PTX drug group. The study provides significant information on the biological response of cubosomes and highlights their potential as a versatile drug delivery platform for safe and effective delivery of chemotherapeutic drugs. © 2020 American Chemical Society.
- Description: The authors acknowledge the Capability Development Fund Scheme of RMIT University, the Maxwell Eagle Endowment Award and the CASS Foundation Science/Medicine Grant for financial support. N.T. is a recipient of an RMIT Vice-Chancellor’s Research Fellowship.
IR monitoring of absorbent composition and degradation during pilot plant operation
- Authors: Puxty, Graeme , Bennett, Robert , Conway, Will , Webster-Gardiner, Mike , Yang, Qi , Pearson, Pauline , Cottrell, Aaron , Huang, Sanger , Feron, Paul , Reynolds, Alicia , Verheyen, Vincent
- Date: 2020
- Type: Text , Journal article
- Relation: Industrial and Engineering Chemistry Research Vol. 59, no. 15 (2020), p. 7080-7086
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- Description: The monitoring of the absorbent during the operation of CO2 separation processes is a necessary and challenging task. The most common absorbent used is an aqueous amine solution. Traditional approaches to analysis such as titration and chromatography are time-consuming and only provide limited information. This hinders the ability of process operators to rapidly respond to changes in operating conditions. In this work, a combination of infrared (IR) spectroscopy and principle component regression (PCR) analyses have been demonstrated as a rapid and reliable technique to determine the composition of an absorbent during a pilot plant campaign at a brown coal power station. The concentration of amine, a degradation product, CO2, and water was monitored throughout the campaign by a method that provided results in minutes. The results were verified by independent sample analysis using acid-base titration, high-performance liquid chromatography (HPLC), and 13C NMR spectroscopy. It was necessary to use spectral windowing when building the IR-PCR model, but this resulted in a robust and reliable method that has been demonstrated to work in a real-world process environment. © 2019 American Chemical Society.
- Description: The authors wish to acknowledge the financial assistance provided by the Brown Coal Innovation Australia, Ltd., a private member-based company with funding contracts through the Australian National Low Emissions Coal Research and Development, Ltd. (ANLEC R&D) and the Victorian State Government. The work described here was made possible through the PICA project, a collaboration between AGL Loy Yang, IHI, and CSIRO that aims to advance post-combustion CO 2 -capture technology in Australia.
Low-power wide-area networks : design goals, architecture, suitability to use cases and research challenges
- Authors: Buurman, Ben , Kamruzzaman, Joarder , Karmakar, Gour , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 17179-17220
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- Description: Previous survey articles on Low-Powered Wide-Area Networks (LPWANs) lack a systematic analysis of the design goals of LPWAN and the design decisions adopted by various commercially available and emerging LPWAN technologies, and no study has analysed how their design decisions impact their ability to meet design goals. Assessing a technology's ability to meet design goals is essential in determining suitable technologies for a given application. To address these gaps, we have analysed six prominent design goals and identified the design decisions used to meet each goal in the eight LPWAN technologies, ranging from technical consideration to business model, and determined which specific technique in a design decision will help meet each goal to the greatest extent. System architecture and specifications are presented for those LPWAN solutions, and their ability to meet each design goal is evaluated. We outline seventeen use cases across twelve domains that require large low power network infrastructure and prioritise each design goal's importance to those applications as Low, Moderate, or High. Using these priorities and each technology's suitability for meeting design goals, we suggest appropriate LPWAN technologies for each use case. Finally, a number of research challenges are presented for current and future technologies. © 2013 IEEE.
Micro-scale heat transfer modelling of the contact line region of a boiling-sodium bubble
- Authors: Iyer, Siddharth , Kumar, Apurv , Coventry, Joe , Pye, John , Lipiński, Wojciech
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Heat and Mass Transfer Vol. 160, no. (2020), p.
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- Description: The use of boiling liquid metals such as sodium is attractive for providing a near-isothermal heat source for engineering applications. However, previous use of boiling sodium as a coolant in nuclear reactors and as a heat transfer fluid in solar thermal applications has shown that the boiling process is unstable. To stabilise the flow, it is imperative to gain a better understanding of the boiling phenomena. An integral part of the boiling process is the evaporation of the region where the liquid-vapour interface meets the heater wall, referred to as the contact line region. The heat transfer modelling of this region formed below a single bubble in nucleate pool boiling of sodium is considered in this study. A contact line model previously developed for high Prandtl number flows is extended by including the effect of an electron pressure component which is unique to liquid metals. The assumptions made in the model are critically assessed to determine their validity for modelling micro-scale evaporation in sodium. The model was used to show that the evaporative heat flux from the contact line region in sodium can be up to six times larger compared to a high Prandtl number fluid FC-72 for a superheat of 15 K, owing to the high thermal conductivity of sodium. Furthermore, a study on the influence of specific characteristics of sodium — high boiling superheat and presence of an electron pressure — showed that the evaporative heat flux increases with increasing superheat and decreases with increasing electron pressure. © 2020 Elsevier Ltd
- Description: We gratefully acknowledge the financial support from the Australian Research Council (grant no. LP150101189 ). We thank our project partner Vast Solar Pty Ltd for their support and contributions.
Mobility based network lifetime in wireless sensor networks: A review
- Authors: Nguyen, Linh , Nguyen, Hoc
- Date: 2020
- Type: Text , Journal article
- Relation: Computer Networks Vol. 174, no. (2020), p.
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- Description: Increasingly emerging technologies in micro-electromechanical systems and wireless communications allows mobile wireless sensor networks (MWSNs) to be a more and more powerful mean in many applications such as habitat and environmental monitoring, traffic observing, battlefield surveillance, smart homes and smart cities. Nevertheless, due to sensor battery constraints, energy-efficiently operating an MWSN is paramount importance in those applications; and a plethora of approaches have been proposed to elongate the network longevity at most possible. Therefore, this paper provides a comprehensive review on the developed methods that exploit mobility of sensor nodes and/or sink(s) to effectively maximize the lifetime of an MWSN. The survey systematically classifies the algorithms into categories where the MWSN is equipped with mobile sensor nodes, one mobile sink or multiple mobile sinks. How to drive the mobile sink(s) for energy efficiency in the network is also fully reviewed and reported. © 2020
Network representation learning: From traditional feature learning to deep learning
- Authors: Sun, Ke , Wang, Lei , Xu, Bo , Zhao, Wenhong , Teng, Shyh , Xia, Feng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 205600-205617
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- Description: Network representation learning (NRL) is an effective graph analytics technique and promotes users to deeply understand the hidden characteristics of graph data. It has been successfully applied in many real-world tasks related to network science, such as social network data processing, biological information processing, and recommender systems. Deep Learning is a powerful tool to learn data features. However, it is non-trivial to generalize deep learning to graph-structured data since it is different from the regular data such as pictures having spatial information and sounds having temporal information. Recently, researchers proposed many deep learning-based methods in the area of NRL. In this survey, we investigate classical NRL from traditional feature learning method to the deep learning-based model, analyze relationships between them, and summarize the latest progress. Finally, we discuss open issues considering NRL and point out the future directions in this field. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
Numerical modelling of radiation absorption in a novel multi-stage free-falling particle receiver
- Authors: Kumar, Apurv , Lipinski, Wojciech , Kim, Jin-Soo
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Heat and Mass Transfer Vol. 146, no. (Jan 2020), p. 11
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- Description: A novel multi-stage free-falling particle receiver design is proposed to improve the simple free-falling concept by enhancing the hydrodynamic stability and improving the radiation absorption of the particle curtain. The multi-stage design arising from repeated re-initialisation of the particle curtain by using intermediate troughs in the receiver results in an increased average volume fraction and residence time of the particles. The present work numerically solves the mass, momentum and radiative transfer equation for an isothermal two dimensional Eulerian-Eulerian particle-gas multiphase flow equations to estimate the absorption characteristics of the particle curtain. The multi-stage receiver concept significantly improves the absorptance of the curtain and reduces the reflection losses by over 50%. The reflection losses are seen to be insensitive to increase in size of the receiver making the multi-stage concept highly scalable. (C) 2019 Elsevier Ltd. All rights reserved.
Prediction of gold-bearing localised occurrences from limited exploration data
- Authors: Grigoryev, Igor , Bagirov, Adil , Tuck, Michael
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Computational Science and Engineering Vol. 21, no. 4 (2020), p. 503-512
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- Description: Inaccurate drill-core assay interpretation in the exploration stage presents challenges to long-term profit of gold mining operations. Predicting the gold distribution within a deposit as precisely as possible is one of the most important aspects of the methodologies employed to avoid problems associated with financial expectations. The prediction of the variability of gold using a very limited number of drill-core samples is a very challenging problem. This is often intractable using traditional statistical tools where with less than complete spatial information certain assumptions are made about gold distribution and mineralisation. The decision-support predictive modelling methodology based on the unsupervised machine learning technique, presented in this paper avoids some of the restrictive limitations of traditional methods. It identifies promising exploration targets missed during exploration and recovers hidden spatial and physical characteristics of the explored deposit using information directly from drill hole database. Copyright © 2020 Inderscience Enterprises Ltd.