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Low-order modeling of high-altitude relight of jet engine combustors
No full textA physics-based, low-order ignition model is used to assess the ignition performance of a kerosene-fueled gas-turbine combustor under high-altitude relight conditions. The ignition model used in this study is based on the motion of virtual flame particles and their extinction according to a Karlovitz number criterion, and a stochastic procedure is used to account for the effects of spray polydispersity on the flame’s extinction behavior. The effects of large droplets arising from poor fuel atomization at sub-idle conditions are then investigated in the context of the model parameters and the combustor’s ignition behavior. For that, a Reynolds-averaged Navier-Stokes simulation of the cold flow in the combustor was performed and used as an input for the ignition model. Ignition was possible with a Sauter mean diameter (SMD) of 50 μm, and was enhanced by increasing the spark volume. Although doubling the spark volume at larger SMDs (75 and 100 μm) resulted in the suppression of short-mode failure events, ignition was not achieved due to a reduction of the effective flammable volume in the combustor. Overall, a lower ignition probability is obtained when using the stochastic procedure for the spray, which is to be expected due to the additional detrimental effects associated with poor spray atomisation and high polydispersity
Emerging Indoor Photovoltaic Technologies for Sustainable Internet of Things
No full textThe Internet of Things (IoT) provides everyday objects and environments with “intelligence” and data connectivity to improve quality of life and the efficiency of a wide range of human activities. However, the ongoing exponential growth of the IoT device ecosystem—up to tens of billions of units to date—poses a challenge regarding how to power such devices. This Progress Report discusses how energy harvesting can address this challenge. It then discusses how indoor photovoltaics (IPV) constitutes an attractive energy harvesting solution, given its deployability, reliability, and power density. For IPV to provide an eco-friendly route to powering IoT devices, it is crucial that its underlying materials and fabrication processes are low-toxicity and not harmful to the environment over the product life cycle. A range of IPV technologies—both incumbent and emerging—developed to date is discussed, with an emphasis on their environmental sustainability. Finally, IPV based on emerging lead-free perovskite-inspired absorbers are examined, highlighting their status and prospects for low-cost, durable, and efficient energy harvesting that is not harmful to the end user and environment. By examining emerging avenues for eco-friendly IPV, timely insight is provided into promising directions toward IPV that can sustainably power the IoT revolution
Industrial and environmental significance of photonic zirconia nanoflakes: Influence of boron doping on structure and band states
No full textA unique zirconia nanomorphology possessing an enhanced photocatalytic efficiency was developed utilizing a convenient single-sol synthesis process which involved in-situ doping of zirconia by boron. The boron-doped zirconia exhibited a flake morphology as opposed to the spherical pure form and subsequent crystallographic investigations implied the phase conversion from binary to single-phase along with the shape due to the doping. Optical characterization indicated a modified band structure with newly generated isolated impurity states within the principle zirconia band edges. As per the X-ray spectroscopy data, boron was detected as chemically bound to oxygen while electron paramagnetic resonance indicated the presence of an adsorbed oxygen lattice. During UV and simulated solar irradiation trials, respective removal capabilities of 90% and 93% of the model compound were accomplished, hence the effectiveness of the photocatalyst was confirmed. The enhanced photoactivity observed in the UV region was attributed to combined effects of the boron-induced isolated impurity states within principle band edges of zirconia, the defect-rich planer morphology, favorable interfacial interactions and the greater availability of oxygen on the lattice. Developed nanoflakes are stable, inert, and efficient hence exhibiting compelling suitability in the remediation of harmful industrial organic compounds
A high-performance free-standing Zn anode for flexible zinc-ion batteries
No full textZinc-ion batteries (ZIBs) have attracted significant attention owing to their high safety, high energy density, and low cost. ZIBs have been studied as a potential energy device for portable and flexible electronics. Here, a highly flexible free-standing Zn anode is fabricated using a simple spin-coating technique, and its application in ZIBs is demonstrated. The free-standing Zn anode precursor is formed by mixing Zn particles with carbon nanotubes and poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP). The hexafluoropropylene group in PVDF-HFP improves the mechanical properties of the free-standing Zn anode, whereas the carbon nanotubes created percolation conduction in the composite electrode, leading to an increased electrical conductivity of the anode. Owing to the excellent electrical conductivity and high specific surface area of the free-standing Zn anode, ZIBs with high capacity, rate performance, and mechanical flexibility are achieved. The volumetric energy density of the ZIBs reaches 8.22 mW h cm-3 with a battery thickness of 0.4 mm. This work demonstrates that free-standing Zn anodes are promising anodes for flexible ZIBs
Crowdsourcing design guidance for contextual adaptation of text content in augmented reality
No full textAugmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer's inability to assess how uncontrolled deployment contexts may infuence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user's own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efciently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by reexamining the design challenge of adapting AR text content to the user's environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset
A Full Bayesian Approach to Sparse Network Inference Using Heterogeneous Datasets
No full textNetwork inference has been attracting increasing attention in several fields, notably systems biology and biomedicine. Indeed, one of our biggest challenges is to uncover and understand complex molecular networks behind cells and organisms. A network is mainly characterized by its topology and internal dynamics. In particular, sparse topologies with stable dynamics are properties present in most real-world networks. Moreover, experiments typically measure a partial set of nodes. Linear systems have been used as approximations of complex nonlinear systems in a wide range of applications. Although they exhibit simpler dynamics, they can easily model unmeasured nodes, e.g., via transfer functions, which is not possible for nonlinear systems. This article explores these properties and considers general linear network models. It develops a method, based on reversible jump Markov chain Monte Carlo, to estimate the confidence of all links and produce the most likely topology. Monte Carlo simulations indicate that our approach consistently produces more accurate networks compared with other state-of-the-art methods, including kernel-based methods, nonlinear ordinary-differential-equation-based methods (iCheMA), and machine-learning-based methods (dynGINIE3). We show that this is also true on a well-known biological nonlinear model. The proposed method can be used in a wide range of applications, such as systems biology and biomedicine, and fault detection and diagnosis
NFV orchestration over disaggregated metro optical networks with end-to-end multi-layer slicing enabling crowdsourced live video streaming
No full textNetwork infrastructure must support emerging applications, fulfill 5G requirements, and respond to the sudden increase of societal need for remote communications. Remarkably, crowdsourced live video streaming (CLVS) challenges operators' infrastructure with tides of users attending major sport or public events that demand high bandwidth and low latency jointly with computing capabilities at the networks' edge. The Metro-Haul project entered the scene proposing a cost-effective, agile, and disaggregated infrastructure for the metro segment encompassing optical and packet resources jointly with computing capabilities. Recently, a major Metro-Haul outcome took the form of a field trial of network function virtualization (NFV) orchestration over the multi-layer packet and disaggregated optical network testbed that demonstrated a CLVS use case. We showcased the average service creation time below 5 min, which met the key performance indicator as defined by the 5G infrastructure public private partnership. In this paper, we expand our field trial demonstration with a detailed view of the Metro-Haul testbed for the CLVS use case, the employed components, and their performance. The throughput of the service is increased from approximately 9.6 Gbps up to 35 Gbps per virtual local area network with high-performance VNFs based on single-root input/output virtualization technology
Quench Protection Modeling of an HTS Magnet for MRI System
No full textThe High-Temperature Superconducting (HTS) magnet is one of the most promising technologies to accommodate various high field applications. With the high magnetic field, the quench problem of HTS material should be considered with extra care, and the specific quench protection scheme should be projected. In this article, the modeling of the quench protection of an HTS magnet for the MRI system is presented. The modeling strategy was composed of two stages: Stage 1 the HTS magnet was in the normal operation circuit, and Stage 2 the HTS magnet was switched to the heat dissipation circuit. The 1st stage was based on the finite element method (FEM) using the H-formulation together with the thermal-coupled model, which simulated the current distribution of typical HTS tapes and showed the process of temperature increase when the hot source occurred. The 2nd stage was based on the analytical model to investigate the reasonable damping resistance and the hot spot temperature of the HTS magnet
Corrigendum to “Centrifuge modelling of the behaviour of pile groups under vertical eccentric load”. [Soils Found. 61 (2021) 465–479] (Soils and Foundations (2021) 61(2) (465–479), (S0038080621000202), (10.1016/j.sandf.2021.01.006))
No full textThe authors regret for the absence of Fig. 1, and associated caption, in the article. This figure, referenced in the text, is reported below. The authors would like to apologise for any inconvenience caused
