bluuebunny/crossref_metadata_2025 huggingface dataset:
DCRL‐RPL: Dual context‐based routing and load balancing in RPL for IoT networks
Authors: Kumar Ajay , Hariharan Narayanan
Published: April 2020

Routing Protocol for Low power lossy network (RPL) is emerged to evade the energy issues in the Internet of Things (IoT) network. Although, RPL noticeably satisfies the requirement of the IoT network, still there exist certain open issues to resolve. This paper addresses the problem of routing overhead, packet losses and load imbalance in RPL based IoT network. These downsides are solved using the proposed Dual Context‐based Routing and Load Balancing in RPL based Network (DCRL‐RPL). Primarily, we implement the grid construction where the network area is split into a different level of the unequal grid. The ranking based Grid Selection process is executed to select the optimal grid head node in each grid. The grid head node in the network schedules its member node using the Reputation based Scheduling method. The elected grid head classifies the data received from its member using Adam Deep Neural Network (ADNN) to provide better routing performance. Here, the sensitive and non‐sensitive data are considered as context for objective function selection. At last, the efficacy of the DCRL‐RPL is analyzed using the Network Simulator 3.26 (NS3) tool. From comprehensive validation results, we show that DCRL‐RPL acquires better results.
Accurate scale estimation for visual tracking with significant deformation
Authors: Chu Lutao , Li Huiyun , Yang Zhiheng
Published: April 2020

Scale variation of a target frequently appears in tasks of visual tracking. Accurate scale estimation is challenging due to deformation, occlusion, rotation, change in the view angle and diversity of tracking object categories. Most tracking methods employ an exhaustive search of scales to estimate the target scales. However, only finite and discrete scales are usually searched due to the expensive computation requirement. Here, the authors propose a novel scale estimation method based on bounding box regression (BBR). They first formulate the scale tracking as a regression problem, and search for the entire continuous scale space without being limited by a manually specified number of scales. Then they extend the original single‐channel BBR to multi‐channel situations, to allow for better employment of multi‐channel features. To further take advantage of the time prior information of training samples, they derive a time‐related sample weighted multi‐channel BBR. Besides, they propose a quantitative measurement, scale divergence degree, to reflect the diversity of sampling strategy. Experimental results on OTB‐2015D dataset demonstrate that the proposed approach achieves outstanding scale estimation performance for visual tracking with significant deformation.
Current‐based directional relaying scheme to protect series compensated transmission lines used to transmit bulk power produced by power electronics interfaced renewable energy power plants
Authors: Jalilian Amin , Muttaqi Kashem M.
Published: April 2020

Exploiting series compensated transmission lines (SCTLs) to transfer bulk power produced by power electronics‐interfaced renewable energy power plants (PE‐REPPs) to the load canters has been accepted as an economical solution as well as the practical approach. However, SCTLs impose some difficulties on protective relays, especially conventional directional relaying which mainly employ phase angle difference between voltage and current signals to discriminate between forward and reverse faults and can jeopardize their operation, leading to a false trip and unjustified isolation of REPPs. To solve this problem, an efficient current‐based directional relaying scheme is presented for the protection of SCTLs. In SCTLs due to the presence of series capacitance in the fault loop, voltage inversion (VI) and current inversion (CI) phenomena occur. The proposed directional relaying scheme can tackle CI and VI problems. Since the proposed method merely uses the phase angle of fault current, it can retain its proper operation during close‐in faults where conventional directional relaying lose their proposer performance due to CCVT transients as well. Therefore, the resilience offered by SCTLs during the integration of REPPs will be attained. The performance of the proposed relaying scheme is evaluated under various operating conditions, and obtained results prove its efficiency.
Finite‐time convergence of group flocking for multi‐agent systems with mismatched/matched disturbances
Authors: Yang Yi‐ze , Yang Hong‐yong , Li Yuling
Published: April 2020

In this study, the problem of grouping motion for a second‐order multi‐agent network with both matched disturbances and mismatched disturbances is investigated, and finite‐time convergent algorithm of the dynamic system is proposed. By designing the disturbance observers to eliminate disturbances in the multi‐agent systems, a compound communication protocol with active disturbance compensation is presented by means of the sliding‐mode control. By applying finite‐time stable theory and input‐to‐state stable theory, the finite‐time group convergence of multi‐agent systems with multiple disturbances is analysed, and group flocking can be achieved asymptotically with the cooperative controller. The numerical simulations demonstrate the validity of the results.
Scalable and efficient authentication scheme for secure smart grid communication
Authors: Hammami Hamza , Ben Yahia Sadok , Obaidat Mohammad S.
Published: April 2020

Smart grids represent the latest trend that has disrupted the energy supplier sector. They are in the form of smart meters that automatically communicate power consumption data to the power grid operator. In fact, the smart‐grid technology is a great solution for energy suppliers and their end customers, enabling them to perform more frequent measurements of energy, monitor their consumption and thus control the amount of their energy bills. Although the smart‐grid technology brings significant gains in performance and economy to its users. However, this advanced technology immediately raises different types of attacks that can adversely affect the operation of smart grids by falsifying electricity consumption data transmitted between smart meters and the power distribution server and therefore through the generation of incorrect energy billing invoices. The reflection carried out in the proposed approach is part of this problem. It is particularly concerned with realising a new privacy‐protected authenticated key agreement scheme for secure communication between smart meters and energy providers. The conducted experiments show that the proposed authentication scheme exceeds its competitors in terms of calculation costs and resistance to various types of attacks.
Radar code design to optimise detection under whitened similarity constraint
Authors: Majdolashrafi Pirouz , ArdebiliPour Mehrdad , Ghasimi Mohsen
Published: April 2020

An active sensing system, such as radar, extracts the useful features of the targets of interest, by transmitting a certain waveform to a particular area and analysing the returned signal. There are two factors that are critical to the system performance, namely the receive filter and the transmitted waveform. Transmitted signal is among the most interesting factor affecting the radar system performance in complex environments. The waveform design problem is an important stage in the performance of cognitive radars. Here, the matched illumination approach is studied which specially addresses the issue of adaptive waveform design to maximise the signal‐to‐disturbance ratio that finally leads to an increased probability of detection. Different constraints on the designed waveform have been introduced in the literature. However, the focus is on the similarity constraint that controls the ambiguity function and modulus variations of the devised code. In more details, it is shown that this kind of constraint should be written based on the estimated background covariance matrix leading to a proposed whitened similarity constraint. It is shown by simulation that the proposed whitened constraint outperforms the well‐known similarity one in resultant ambiguity function properties and probability of detection, assuming the same environmental conditions.
Bidirectional hash chains generically enhances resilience of key predistribution schemes
Authors: Kumar Dalai Deepak , Sarkar Pinaki
Published: April 2020

Key predistribution is an adequate technique to solve the (symmetric) key management problem in distributed systems. Owing to the large network size and limited memory (z) in devices, a given key is shared by a number of nodes (r). This leads to a generic degradation of a network's resilience. Several works dedicate to reduce this deterioration by applications of lightweight mechanisms. Few such prominent approaches are the q‐ composite method by Chan et al., hashed random preloaded subset by Ramkumar et al. and one‐way function iterates by Cichoń et al. or its special case of hash chains (HCs) by Bechkit et al. The authors introduce the generic concepts of bidirectional HCs (2HCs) and q ‐composite 2HCs. A thorough qualitative investigations of vital system parameters indicate trade‐offs between significant improvement in a network's resilience and nominal increment in space and computational overheads in constituent devices. In the process, they correct an error in resilience computations in the works of Bechkit et al. Instantiations of their indigenous concepts to three prominent schemes that represent individual types of key predistribution schemes (one random and two deterministic) concretely quantify their analyses.
Online Monitoring Solutions of Efficiency for Automotive EGR Heat Exchangers
Authors: Maria Vaglieco Bianca , Silvia Merola Simona , Irimescu Adrian , Zollo Vasco , De Marinis Raffaele
Published: April 2020

Internal combustion engines are the dominating technology in the automotive transport sector. Within this context, even incremental improvements in efficiency are essential for reducing overall environmental impact. Maintaining rated specifications is also an important issue, with monitoring solutions being more and more the focus of development. Cooled exhaust gas recirculation (EGR) is a well established technology that allows improvements in efficiency and reduction of emissions. The present work looks at different solutions focused on the integration of a digital sensor directly into EGR valves, thus ensuring continuous monitoring and extensive diagnostics. As an initial stage, an evaluation of gas cooling efficiency was performed and different routes were identified to allow this parameter to be monitored online. Measurement of flow was discarded as a solution, mainly due to cost issues and complications of its application. Temperature based evaluation of efficiency was found to ensure the best compromise, with acceptable accuracy and practically no integration difficulties. This initial evaluation allowed the definition of basic principles of operation for the sensor, so as to ensure the final goal of more efficient and longerlasting EGR modules through continuous performance monitoring.
Dynamics of COVID-19 pandemic at constant and time-dependent contact rates
Authors: Kochańczyk Marek , Grabowski Frederic , Lipniacki Tomasz
Published: April 2020

We constructed a simple Susceptible−Exposed–Infectious–Removed model of the spread of COVID-19. The model is parametrised only by the average incubation period,τ, and two rate parameters: contact rate,β, and exclusion rate,γ. The rates depend on nontherapeutic interventions and determine the basic reproduction number,R0=β/γ, and, together withτ, the daily multiplication coefficient in the early exponential phase,θ. InitialR0determines the reduction ofβrequired to contain the spread of the epidemic. We demonstrate that introduction of a cascade of multiple exposed states enables the model to reproduce the distributions of the incubation period and the serial interval reported by epidemiologists. Using the model, we consider a hypothetical scenario in whichβis modulated solely by anticipated changes of social behaviours: first,βdecreases in response to a surge of daily new cases, pressuring people to self-isolate, and then, over longer time scale,βincreases as people gradually accept the risk. In this scenario, initial abrupt epidemic spread is followed by a plateau and slow regression, which, although economically and socially devastating, grants time to develop and deploy vaccine or at least limit daily cases to a manageable number.
Antiviral Potential of Spondias mombin L. Leaves Extract Against Herpes Simplex Virus Type-1 Replication Using In Vitro and In Silico Approaches
Authors: Siqueira Emerson M. da S. , Lima Tábata L. C. , Boff Laurita , Lima Sarah G. M. , Lourenço Estela M. G. , Ferreira Éder G. , Barbosa Euzébio G. , Machado Paula R. L. , Farias Kléber J. S. , Ferreira Leandro de S. , Rocha Hugo A. de O. , Simões Cláudia M. O. , Zucolotto Silvana M.
Published: April 2020

Spondias mobin leaves have been traditionally used for treating cold sores. The study investigated the mechanism of antiherpes action of S. mombin extract, fractions, and geraniin. Different concentrations of samples were used to evaluate the in vitro antiherpes activity (anti-HSV-1) in virucidal, post-infection, attachment, and penetration assays. The mechanism of action of geraniin was investigated considering the glycoproteins gB and gD of HSV-1 surface as potential molecular targets. Molecular docking simulations were carried out for both in order to determine the possible binding mode position of geraniin at the activity sites. The binding mode position was posteriorly optimized considering the flexibility of the glycoproteins. The chemical analysis of samples was performed by LC-MS and revealed the presence of 22 substances, which are hydrolysable tannins, O-glycosylated flavonoids, phenolic acids, and a carbohydrate. The extract, tannin-rich fraction and geraniin showed important in vitro virucidal activity through blocking viral attachment but showed no relevant inhibition of viral penetration. The in silico approaches demonstrated a high number of potential strong intermolecular interactions as hydrogen bonds between geraniin and the activity site of the glycoproteins, particularly the glycoprotein gB. In silico experiments indicated that geraniin is at least partially responsible for the anti-herpes activity through interaction with the viral surface glycoprotein gB, which is responsible for viral adsorption. These results highlight the therapeutic potential of S. mombin anti-herpes treatment and provides support for its traditional purposes. However, further studies are required to validate the antiviral activities in vivo, as well as efficacy in humans.
Textural features in FDG-PET/CT can predict outcome in melanoma patients to treatment with Vemurafenib and Ipililumab
Authors: Dittrich Daniela , Pyka Thomas , Scheidhauer Klemens , Lütje Susanne , Essler Markus , Bundschuh Ralph A.
Published: April 2020

Aim Recently, textural parameters assessed in FDG-PET/CT as surrogate marker for tumor heterogeneity have been shown to provide prognostic power. Therefore, we investigated the use of such parameters in FDG-PET/CT examinations before the start of immunotherapy with vemurafenib or ipilimumab in patients with malignant melanoma.

Methods In this retrospective analysis 26 patients with histologically proven advanced melanoma were included. FGD-PET/CT was performed before the start of treatment either with vemurafenib (n = 9) or ipilimumab (n = 17) and tumors were analyzed for textural parameters as well as conventional PET features. Lesions were classified as responding or not responding following PERCIST criteria. ROC analysis was performed to analyze the predictive power and cut-off values. In addition, the change of maximum SUV of the lesions between pretherapeutic PET/CT and another PET/CT performed about 12 weeks after start of treatment was evaluated and correlated with the pretreatment parameters.

Results In both groups, six textural parameters showed statistically significant predictive power as well as the metabolic tumor volume. In the group treated with vemurafenib eight additional textural parameters as well as the maximum and mean SUV and the TLG showed significance. A statistically significant correlation between the change of maximum SUV in the course of treatment and the pretherapeutic parameters was found in both treatment groups for three textural features.

Conclusion In patients with malignant melanoma textural parameters in pretherapeutic FDG-PET/CT examinations seem to have prognostic power for treatment response of immunotherapy with vemurafenib and ipilimumab. This can be an important step towards personalized tumor therapy.
Thrombocytopenia in Pregnancy: Approach to Diagnosis and Management
Authors: Fogerty Annemarie E.
Published: April 2020

The impact of thrombocytopenia varies widely depending on the underlying pathophysiology driving it. The biggest challenge in managing thrombocytopenia in pregnancy is accurately identifying the responsible pathophysiology—a task made difficult given the tremendous overlap in clinical and laboratory abnormalities associated with different thrombocytopenia processes. The most common etiologies of thrombocytopenia in pregnancy range from physiology deemed benign to those that are life-threatening to the mother and fetus. Even in cases in which the responsible etiology is deemed benign, such as gestational thrombocytopenia, there are still implications for the management of labor and delivery, a time where hemostatic challenges may prove life-threatening. In most institutions, a minimum platelet count will be mandated for epidural anesthesia to be deemed a safe option. The causes of thrombocytopenia can also include diagnoses that are pregnancy-specific (such as preeclampsia or gestational thrombocytopenia), potentially triggered by pregnancy (such as thrombotic thrombocytopenic purpura), or unrelated to or predating the pregnancy (such as liver disease, infections, or immune thrombocytopenia purpura). It is imperative that the source of thrombocytopenia is identified accurately and expeditiously, as intervention can range from observation alone to urgent fetal delivery. In this review, the approach to diagnosis and the pathophysiological mechanisms of the most common etiologies of thrombocytopenia in pregnancy and associated management issues are presented.
Comparison of linear, hyperbolic and double‐hyperbolic models to assess the force–velocity relationship in multi‐joint exercises
Authors: Alcazar Julian , Pareja‐Blanco Fernando , Rodriguez‐Lopez Carlos , Navarro‐Cruz Roberto , Cornejo‐Daza Pedro J. , Ara Ignacio , Alegre Luis M.
Published: April 2020

This study assessed the validity of linear, hyperbolic and double‐hyperbolic models to fit measured force–velocity (F–V) data in multi‐joint exercises and the influence of muscle excitation on the F–V relationship. The force–joint angle and F–V relationships were assessed in 10 cross‐training athletes and 14 recreationally resistance‐trained subjects in the unilateral leg press (LP) and bilateral bench press (BP) exercises, respectively. A force plate and a linear encoder were installed to register external force and velocity, respectively. Muscle excitation was assessed by surface EMG recording of the quadriceps femoris, biceps femoris and gluteus maximus muscles during the unilateral LP. Linear, Hill's (hyperbolic) and Edman's (double‐hyperbolic) equations were fitted to the measured F–V data and compared. Measured F–V data were best fitted by double‐hyperbolic models in both exercises (p < 0.05). F–V data deviated from the rectangular hyperbola above a breakpoint located at 90% of measured isometric force (F 0) and from the linearity at ≤45% of F 0 (both p < 0.05). Hyperbolic equations overestimated F 0 values by 13 ± 11% and 6 ± 6% in the LP and BP, respectively (p < 0.05). No differences were found between muscle excitation levels below and above the breakpoint (p > 0.05). Large associations between variables obtained from linear and double‐hyperbolic models were noted for F 0, maximum muscle power, and velocity between 25% and 100% of F 0 (r = 0.70–0.99; all p < 0.05). The F–V relationship in multi‐joint exercises was double‐hyperbolic, which was unrelated with lower muscle excitation levels. However, linear models may be valid to assess F 0, maximal muscle power and velocity between 25% and 100% of F 0.
Microbial fuel cells with yeast biofilms anode and buckypaper cathode
Authors: Nguyen D-T , Iwai K , Ito Y , Tamura T , Taguchi K
Published: April 2020

Microbial fuel cells (MFCs) are expected to be the next green energy systems, which can harvest chemical energy existing in domestic waste. In this research, a two-chambered microbial fuel cell (MFC) was developed. On the anode side, an activated carbon-based electrode with biofilms of yeast cells was used as the anode. On the cathode side, potassium ferricyanide was used as catholyte, and buckypaper (BP) was used as the cathode electrode. Many researchers made BP by the chemical vapor deposition method, which is high-cost. In this research, the vacuum filtration method was used to reduce the fabrication cost of BP. The power density of the MFCs using different cathode materials was compared: (1) 2.8 µW/cm2 of carbon sheet, (2) 3.2 µW/cm2 of carbon sheet-coated carbon nanotubes (CNTs) and (3) 4.3 µW/cm2 of two-layer BP. Based on the experimental results, the surface area of BP might be much larger than that of the carbon sheet-coated CNTs.
Environmental impact prediction of microalgae to biofuels chains using artificial intelligence: A life cycle perspective
Authors: Mayol A P , San Juan J L G , Sybingco E , Bandala A , Dadios E , Ubando A T , Culaba A B , Chen W H , Chang J S
Published: April 2020

Biofuels derived from microalgae is an emerging technology that can supply fuel demand and alleviate greenhouse gas emissions. However, exclusively producing biofuels from microalgae remains to be commercially unsustainable because of its high investment and operating costs. A promising opportunity to address this are algal bio-refineries. Nonetheless, there is still a need to verify the environmental sustainability of this system along its entire process chain, from raw material acquisition to end-of-life. This study utilizes a life-cycle perspective approach to assess the sustainability of the algal bio-refinery and developed environmental impact prediction model using artificial intelligence, particularly adaptive neuro fuzzy inference system. Results will indicate the environmental impacts of a bio-refinery system identifying its major hotspots on different environmental impact categories. Results show that in the investigated proposed algal bio-refinery, the transesterification process had a huge contribution on the overall environmental impact having over 51.5 % of the total weight. In addition, ANFIS results showed the correlation of input parameters with respect to the environmental impact of the system. The model also indicated that there is a perfect correlation between the two parameters. The model and its accuracy should be further validated with the use of real data.
Factors affecting the quality of fuel pellets produced from waste biomass
Authors: Pradhan Priyabrata , Arora Amit , Mahajani Sanjay M.
Published: April 2020

The production of wood pellets has more than doubled between 2010 and 2015 to over 30 million metric tons. It is expected to grow to even more than 50 million metric tons by 2025. Thus, increasing demand for wood pellets for its energy utilization has prompted researchers to search for non-woody feedstocks. In this context, a potentially huge underutilized biomass such as garden waste can be explored as an alternative feedstock. The key factors affecting the quality of fuel pellets were evaluated during the garden waste pelletization process. Experiments were performed using a flat die pellet mill to investigate the effect of feedstock moisture content, die size, and milling size on pellet quality. Quality parameters such as pellet moisture, pellet length, bulk density, and durability were measured as per ASABE standards. Feed moisture content had a significant effect on durability and bulk density, with high quality pellets produced at the low feed moisture content (< 20%). The quality parameters of produced pellets were evaluated as per standards. It is concluded from the investigation that pellets produced at 5-10% feed moisture content using 15 mm die and fine shredded biomass satisfies the ISO standard and other norms.
The performance of thermoelectric exhaust heat recovery system considering different heat source’s fin arrangements
Authors: Sofyan Sarwo Edhy , Muhajir  , Khairil  , Jalaluddin  , Bahri Samsul
Published: April 2020

The IC engine converts the chemical energy of the fuels into the mechanic energy with the efficiency is around 35-40% depends on the type and operation condition of the engines. It means around 60-65% of the energy is wasted mostly in the form of heat (dissipated through the cooling process and exhaust gas) and friction. A thermoelectric exhaust heat recovery system can be used to harvest the waste heat which potentially could increase the efficiency of the IC engine indirectly. In this experimental study, the heat recovery system consists of a rectangular duct in which sixteen thermoelectric modules are attached to its sides (each side consist of four thermoelectric modules). The aluminium fins are mounted at the cold sides of thermoelectric modules (at the outer sides of the rectangular duct) and cooled by air supplied by computer fan coolers. To harvest the exhaust heat of the IC engine, the heat recovery system is connected to the exhaust pipe. The effect of aluminium fin arrangements, mounted on the inner surfaces of the rectangular duct of the heat recovery device, is investigated. The arrangements include mounting of the fins at the lateral sides, top and down sides, and the whole sides of the heat recovery device. Besides, the effect of the absence of the fins at the exhaust gas passage of the heat recovery device is examined. The performance of the heat recovery system is studied when the engine operates under the no-load condition at rotational speeds of 1300, 1600, 1900 and 2200 RPM. The experimental result reveals that the voltage and current generated by the thermoelectric exhaust gas recovery system increase in line with the increase of engine speed. In addition, it is found that the highest voltage and current are generated by the whole side fin arrangement, namely 12,52V and 122 mA respectively, at an engine speed of 2200 RPM. It is observed that the finless arrangement generates the lowest voltage and current among others, namely 5.36 V and 20.43 mA.
Analysis on the natural gas distributed energy system scheme of a hospital complex in Xi’an
Authors: Liu Siyan , Kong Qiongxiang , Liang Nan , Li Guoqing , Ma Zhendi
Published: April 2020

Natural gas distributed energy systems (NGDESs) have the advantages of peak load shifting and good economic benefits suitable situations, In the paper, the energy processes of NGDESs for large-scale hospitals in Xi’an are analyzed firstly, by considering the current policy of “grid-connected with no power injection” and the characteristics of prime mover, residual heat utilization equipment and energy consumption in hospital buildings. Secondly, the hourly cooling, heating and electrical loads of a hospital complex in one year are simulated by DesignBuilder software. Based on the further analysis of hourly loads in the year and its changes on typical days, the main devices of the NGDES are chosen optimally. The number of internal combustion engines is determined after comparing their economic benefits of different number of internal combustion engines. Finally, through comparing their initial investment and annual operating cost of the NGDES with that of the separating supply system, the results show that the annual average energy utilization rate of the NGDES is 80%, and its energy saving rate is 34.4% compared with that of the separating supply system.
A deep learning framework for energy management and optimisation of HVAC systems
Authors: Tien Paige Wenbin , Calautit John Kaiser , Darkwa Jo , Wood Christopher , Wei Shuangyu , Jay Pantua Conrad Allan , Xu Weijie
Published: April 2020

To enable heating, ventilation and air-conditioning systems to effectively work for the next generation-built environment by reducing unnecessary energy loads while also maintaining satisfactory thermal comfort conditions, this present work introduces a demand-driven deep learning-based framework, which can be integrated with building energy management systems and provide accurate predictions of occupancy activities. The developed framework utilises a deep learning algorithm and an artificial intelligence-powered camera. Tests are performed with new data fed into the framework which enables predictions of typical activities in buildings; walking, standing sitting and napping. Building energy simulation was used with various occupancy profile schedules: two typical static office occupancy profiles, a schedule generated via the deep learning framework and an actual prediction profile. An office space within a case study building was modelled. Initial results showed that the overall occupancy heat gains were up to 30.56% lower when the deep learning generated profile was used; as compared to the static office occupancy profile. This indicated a 0.015 kW decrease in occupancy gains, which also influenced the increase in building heating loads. Analysis indicates the occupancy detection-based framework is a potential solution for the development of effective heating, ventilation and air-conditioning systems. Additionally, the requirement for the deep learning framework to work for multiple occupancy activity detection and recognition was identified.
Numerical study of waste heat recovery by direct heat exchanger systems
Authors: Kalantari Hosein , Ghoreishi-Madiseh Seyed Ali , Amiri Leyla , Sasmito Agus P. , Hassani Ferri
Published: April 2020

Dependency on fossil fuel and associated carbon footprints have increased the urge to look for methods to increase the thermal efficiency of heating and cooling systems. Exhaust air heat recovery system is one of the promising solutions with viable potential in industrial applications such as mine ventilation and so on. Direct contact heat exchangers can be feasibly used in these applications due to their characteristic advantages such as the ability to exchange at low temperature differences. Given the numerous advantages of such systems, there is a need for thorough understanding of the complex fluid flow and heat transfer performance of these heat exchangers. While water spray is commonly used for capturing the heat from exhaust air in direct heat exchange systems, performance of such system is highly dependent on the various operating parameters such as droplet size distribution, continuous phase temperature, velocity and relative humidity, spray nozzle angle and discrete phase temperature and velocity which is required to be studied in greater depth. Computational Fluid Dynamics can play a key role to investigate the performance of these two-phase flow systems. In this paper, a three-dimensional two-phase model has been presented to study heat recovery from exhaust air by using direct spray water heat recovery systems. Also, an analytical model has been developed using a self-written MATLAB code and compared to the numerical one. The results of the study show that the analytical model can capture the CFD runs outcomes with a high degree of accuracy. Also, the conducted parametric study confirms the dominant impacts of droplet size distribution and air flow rate on the performance of the system.
Urban road and pavement solar collector system for heat island mitigation: assessing the beneficial impact on outdoor temperature
Authors: Nasir Siti Diana , Xu Weijie , Vital Becky , Pantua Conrad , Zhou Bochao , Calautit John , Hughes Ben
Published: April 2020

Road renewable energy system has raised much attention from both industrial and academic research on how abundant solar radiation absorbed by road surfaces can be collected while reducing the impact of high surface temperature towards urban environment. Cities consume about 3% of total global land mass with road and parking lots consuming around 35 to 50% of land use footprint. These urban road networks permit the dynamic movement of human activities and physical development of the cities. Remarkably, researches have given much spaces to explore on how roads can contribute to make cities more sustainable. Therefore, ideas on road renewable energy system have surfaced to its audiences. The heat island effect has been reported to raise temperature up to 12°C in urban areas which affects building cooling energy load and simultaneously the people comfort. High discomfort can lead to high energy and cost utilisation, which further worsens the issue. This study assessed the beneficial impacts of urban road pavement solar collector towards reducing outdoor temperature by carrying out de-coupled numerical modelling of an urban canyon model integrated with the pavement solar collector in ANSYS FLUENT, validated with experimental data. Numerical results showed up to 4.67 °C air temperature reduction and up to 27.0 % surface temperature reduction after the U-RPSC application. When applying to street canyon with different heights, the concern was highlighted on the system performance in reducing potential UHI effect in deeper canyon during less windy condition and during the night-time. The study also presents the experimental work on the performance of a laboratory-scale U-RPSC system.
Development of an immersed boundary-thermal lattice boltzmann solver for fluid-particle interaction in energy management systems
Authors: Majumder Sambit , Ghosh Arnab , Basu Dipankar N , Natarajan Ganesh
Published: April 2020

Computer simulations of a wide range of applications like materials processing, thermal energy storage and conversion systems, nuclear reactors, solar energy, and pollution control, etc. are of high importance in this era. In many of these applications, strong thermofluidic interactions between fluid and structures exist. Efficient and accurate numerical modelling of these interactions provide initial predictions of the process, but at times, it becomes challenging where complex shape of the structures is involved. To address this issue, often numerical methods that are proposed suffer lower computational accuracy and complex algorithms to capture interfacial predictions. In this paper, development, accuracy study and robustness of an in-house openMP parallelized Immersed Boundary-Thermal Lattice-Boltzmann (IB-TLB) solver are presented, which is capable of simulating complex boundary problems involving thermal interactions and accurately capture interfacial predictions. The solver showed excellent agreement with literature for a natural convection problem involving eccentrically placed stationary heated cylinder inside a cold square enclosure and forced convection around an iso-thermal circular cylinder. The numerical simulation of moving bodies is already quite a complex problem and the complexity increases further when we introduce heat transfer phenomena in it. Spatial order of accuracy test revealed, the IB-TLB algorithm exhibits first-order accuracy for velocity and temperature errors while pressure error retained second-order accuracy for moving boundary problems. It is also observed that the present algorithm can accurately predict local parameters like coefficient of pressure and Nusselt number with good accuracy and thus possesses promising potential to simulate complex moving boundary problems. The present solver will find its application in a wide range of areas such as heat exchangers, solar energy systems and chemical and food industries etc.
ASEAN power grid 20 years after: An overview of its progress and achievements
Authors: Aris Hazleen , Jørgensen Bo Nørregaard
Published: April 2020

ASEAN Power Grid (APG) is one of the six programme areas initially identified in the first ASEAN Plan of Action for Energy Cooperation (APAEC) series, APAEC 1999-2004. It is an initiative to ensure security and sustainability of energy in the region, particularly the electricity. In each series, the APG objectives, strategies and actions are revised and updated to reflect its current state and progress. It has been twenty years since the first APAEC series and a lot of APG strategies and actions have been implemented to achieve the stated objectives. It is therefore timely to review the current state of its implementation to gain insight on its progress. In this paper, the action plans are presented and their current states of implementation are reviewed with the aim to determine their progress and achievements to date. Most of the information needed for this study was obtained from the official APAEC reports, related documents and news cuttings. To the best of our knowledge, this is the first ever work that comprehensively review the progress and achievement of the APG to date. Existing reports are usually written per timeframe rather than per programme area, making it difficult to delve deeper into a specific programme area. Among others, findings from the review show that most of the implemented actions were focusing on the physical interconnections of the power grid and a lot still need to be done with regards to the trading. However, encouraging progress with regards to trading is also seen lately. Findings from this study would provide useful insight on the current state of the APG implementation, particularly when the relevant committees are currently drafting the second phase of the APAEC 2016-2025 that will cover the period from 2021 to 2025.
High performance iron-based oxygen reduction catalyst supported on sengon wood-derived reduced graphene oxide in acidic medium
Authors: Sudarsono W , Wong W Y , Loh K S , Majlan E H , Syarif N , Kok K Y , Yunus R M , Lim K L
Published: April 2020

Non-precious metals (NPM) such as iron and nitrogen-doped carbon (Fe-N-C) have been actively studied as alternative electrocatalysts to platinum for oxygen reduction reaction (ORR) in proton exchange membrane fuel cell (PEMFC). However, its low stability is associated to the structural morphology of the electrode made of Fe-N-C and its support that has restricted the mass transfer of fuel and product. In this work, it was attempted to assess the role of RGO derived from sengon wood as catalyst support to Fe-N-C catalyst, and study the effect of the Fe-N-C to RGO ratio, on the ORR activity and durability in acidic medium. This work revealed that Fe-N-C/RGO at the weight ratio of 2:0.2 demonstrated the highest onset potential of 0.91 V, with high limiting current density of 5.7 mA/cm2, owing to the uniform active site distribution on the Fe-N-C/RGO surface compared to other samples with different weight ratio. It was indicated in this work that an improve in the kinetic activity was observed with increase operating temperature from 25 to 80 °C. An electron transfer number of 3.91 indicating a complete oxygen reduction process took place on the catalyst. The durability test showed that Fe-N-C/RGO 2:0.2 retained 89 % of its current density at 0.25 V over a duration of 16000 s, higher than that of the benchmark Pt/C. These results have collectively demonstrated a high performance sustainable noble metal-free ORR catalyst for PEMFC applications with proper tailoring the mass ratio of Fe-N-C to RGO support.
Enhanced oil recovery: Potential for oil production development in Fang oilfield, Thailand
Authors: Maneeintr Kreangkrai , Chewaroungroaj Jirawat , Boonpramote Thitisak
Published: April 2020

Fang oilfield is a small onshore reservoir in Thailand containing oil with gravity ranging from 20-40 °API and viscosity of approximately 10-120 cp. The depth of this field is from 300-1,200 meters and the sand thickness is varied from of 1 to 7 meters. For over 60 years of natural production, the field has low oil recovery. The difficulty has been attributed to the unfavorable production. Waterflooding, a secondary recovery, has been studied and the results show that the recovery can increase 4-6%. However, the production can be enhanced more with the tertiary recovery methods or enhanced oil recovery (EOR) which are recommended to increase oil production in this challenging field. However, the proper technologies have not been studied for commercial production yet. These technologies can be thermal recovery, gas injection, microbial enhanced oil recovery and chemical methods. Therefore, it will be the objective of this work to review and screen the EOR method to fit well with oil production in Fang oilfield in order to increase oil production. From this EOR screening, the main results from this study reveal that chemical injection is more appropriate for this field than other techniques because of reservoir characteristics and reservoir fluids. Based on the types of oil and composition in the oil, adding alkaline solution and surfactant can improve oil recovery because they can reduce interfacial tension of oil and to make the mobility higher. On the other hand, for other techniques, thermal recovery can increase mobility because of wax formation but it has higher cost. CO2 injection can increase more oil production. Nevertheless, the sources of CO2 has less supply and is expensive. Now, microbial enhanced oil recovery is on the beginning state and can provide the good potential. Consequently, based on the revision and screening method, the chemical method provide the higher commercial potential and feasibility to enhance oil production in Fang oilfield and the result of this study can be applied to design the plan of oil production operation in the oilfield in the future.
Solvent and non-solvent selection for the chemical recycling of waste Polyethylene (PE) and Polypropylene (PP) metallized film packaging materials
Authors: Gorre Regino C. , Tumolva Terence P.
Published: April 2020

A solvent and non-solvent selection method for the chemical recycling through selective dissolution and precipitation of multi-component waste metallized film wrapper is studied to recover Polyethylene (PE), Polypropylene (PP), and the metal film separately. Pre-selection of solvent for dissolution and non-solvent for precipitation is based on the similarity and compatibility of polymer and solvent molecules measured in terms of solubility parameter and calculated using group contribution approach through Hoftyzer and Van Krevelen method. Toxicity, cost, and availability of the solvent are also considered on the selection. A Hansen sphere model is developed for the prediction of polymer solubility in which p-cymene, a low-cost and naturally derived solvent is chosen as solvent and acetone as non-solvent. PE was first recovered through dissolution at a given temperature, followed by precipitation. PP which remained undissolved together with the metal film was extracted through the same technique but with different dissolution temperature. FTIR spectra of the recovered polymers showed similarity compared to virgin PE and PP films. The melting point of the recovered PE and PP using p-cymene determined in the DSC curves were 107.37 °C and 164.55 °C, respectively. Furthermore, the simplicity of the process, high recovery yield obtained, and the application of p-cymene would make the recycling economical and environment-friendly.
A deformation-based approach to the SoH estimation of collided lithium-ion batteries
Authors: Zhang Jian , Liu Xiangyang , Simeone Alessandro , Lv Dian
Published: April 2020

Extensive research work has been carried out mainly focusing on the assessment and prediction of battery cell State of Health (SoH) under operating conditions, however limited contributions focus on SoH following collision impacts. This paper proposes a method for estimating the battery cell SoH from collision deformation features. Experimental tests of collision impact were designed and realized on brand new battery cells to investigate deformation features. Deformed battery cells were subject to a 3D scanning procedure to retrieve the contour data, subsequently a number of geometrical features were extracted from the 3D image instances. The battery cells damage characterization was carried out by characterizing both physical and electrical performances following the collision impact tests. An intelligent assessment was carried out by adopting a neural network-based supervised machine learning paradigm for classification of deformed battery cells into safe, latent danger and unsafe cells respectively. Training and testing results show a clear pattern between geometrical deformation features and battery cells SoH, with classification accuracy up to 96.7% demonstrating the suitability of the proposed method for an effective assessment. Within electric vehicles applications, such method can provide a basis for safety design enhancement of lithium-ion battery system via finite element simulation of collisions impacts.
Application of 3D laser scanning technology for preservation and monitoring of Thai pagoda: A case study of Wat Krachee Ayutthaya
Authors: Sairuamyat Phasu , Mahasuwanchai Peerasit , Athisakul Chainarong , Leelataviwat Sutat , Chucheepsakul Somchai
Published: April 2020

3D laser scanning technology is one of the current technologies for developing a sustainable and smart city. This technology is applied to obtain the three-dimensional information of building in digital format. To preserve the historic structure, the current structural information is required for structural assessment, monitoring, and conservation planning. The data obtained by the 3D laser scanner is normally used to generate the three-dimensional point cloud data of the building surface. The high-density point cloud data represented the dimension, shape, and size of the building in the current state can be acquired in more accurate and faster than another technique. This paper aims to present the application of 3D laser scanning technology for preservation and monitoring of heritage pagoda in Thailand. The pagoda of Wat Krachee located in Ayutthaya province of Thailand was selected as a case study. The results obtained in this study are a part of Wat Krachee conservation project, which is led by UNESCO Bangkok and the Fine Arts Department, Thailand. One of the challenges in Wat Krachee project is how to preserve the masonry pagoda with two intertwined trees growing inside and become a part of pagoda structure. The terrestrial 3D laser scanner was applied to develop the digital data documentation and 3D model of pagoda in the current state. The 3D survey work has been started since February 2018. The analysis of data obtained in February 2018, Mar 2018, July 2018, and July 2019 was carried out. The significant dimensions and deformation of pagoda are monitored. According to the results, it is found that the 3D laser scanning technology is very effective for assessment and monitoring. The 3D point cloud model obtained in this study can be used to develop the assume original model of the Wat Krachee pagoda, which is the inverted bell-shape with a square base.