The decreasing effect of ammonia enrichment on the combustion emission of hydrogen,methane, and propane fuels

In the present study, non-premixed combustion and NOx emission of H₂, NH₃, C₃H₈, and CH₄ fuels have been studied in a combustion test unit under lean mixture conditions (λ = 4) at 8.6 kW thermal capacity. Furthermore, the combustion and NOx emission of the H₂, C₃H₈, and CH₄ fuels have been investigated for various NH₃ enrichment ratios (5, 10, 20, and 50%) and excess air coefficients (λ = 1.1, 2, 3, and 4) at the same thermal capacity. The obtained results have been compared for each fuel. Numerical simulation results show that H₂ emits intense energy through the reaction zone despite the lowest fuel consumption in mass, among others, due to its high calorific value. Therefore, it has a higher flame temperature than others. At the same time, C₃H₈ has the lowest flame temperature. Besides, NH₃ has the shortest flame length among others, while C₃H₈ has the most extended flame form. The highest level of NOx is released from the NH₃ flame in the combustion chamber, while the lowest NOx is released from the CH₄. However, the lowest NOx emission at the combustion chamber exit is obtained in NH₃ combustion, while the highest NOx emission is obtained with H₂ combustion. It results from the shortest flame length of NH₃, short residence time, and backward NOx reduction to N₂ for NH₃. As for H₂, high flame temperature and relatively long flame, and high residence time of the products trigger NOx formation and keep the NOx level high. On the other hand, excess air coefficient from 1.1 to 2 increases NOx for H₂, CH₄, and NH₃ due to their large flame diameters, unlike propane. Then, NOx emission levels decrease sharply as the excess air coefficient increases to 4 for each fuel. NH₃ fuel also emits minimum NOx in other excess air coefficients at the exit, while H₂ emits too much emission. With NH₃ enrichment, the NOx emissions of H₂, CH₄, and C₃H₈ fuels at the combustion chamber exit decrease gradually almost every excess air coefficient apart from λ = 1.1. As a general conclusion, like renewable fuels, H₂ appears to be a source of pollution in terms of NOx emissions in combustion applications. In contrast, NH₃ appears to be a relatively modest fuel with a low NOx level. In addition, the high amount of NOx emission released from H₂ and other fuels during the combustion can be remarkably reduced by NH₃ enrichment with an excess air combustion.     

Design of Ti4+-doped Li3V2(PO4)3/C fibers for lithium energy storage

In this work, we propose a facile approach to fabricate Ti⁴⁺-doped Li₃V₂(PO₄)₃/C (abbreviated as C-LVTP) nanofibers using an electrospinning route followed by a high temperature treatment. In this designed nanocomposite, the ultrafine LVTP dots are homogeneously dispersed into one-dimensional carbon nanofibers and the Ti⁴⁺ doping does not destroy the crystal structure of monoclinic Li₃V₂(PO₄)₃. Compared to the undoped Li₃V₂(PO₄)₃/C (abbreviated as C-LVP), the as-fabricated C-LVTP fibers present higher reversible capacity, superior high-rate capability as well as better cyclic property. Especially, the C-LVT_7%P cathode delivers not only high capacities of 187.2 and 160.3 mAh g^?1 at 0.5 and 10 C respectively, but also stable cyclic property with the reversible capacity of 135.8 mAh g^?1 at 20 C following 500-cycle spans. The good battery characteristics of C-LVT_7%P can be mainly ascribed to Ti⁴⁺ doping, which can increase the electrical conductivity and Li⁺ diffusion coefficient.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

On the design of secure primitives for real world applications

This editorial paper provides an overview of new advances on hardware security challenges and promising solutions for real world applications. It first presents the increasing hardware vulnerabilities with the emergence of diverse computing platforms. Then, it details the technical challenges, research opportunities, and potential solutions to cyber-attacks on -physical- devices.     

Ultrasonic tomographic velocimeter for visualization of axial flow fields in pipes

An ultrasonic tomographic velocimeter to provide quantitative images of axial flow fields in pipes is developed and presented in this work. To detect the flow in various directions and positions, a novel transducer configuration strategy is proposed. All-in-one transducers are mounted in two sectional planes of the pipe. In each plane, N transducers are equally spaced along the circumference. Overlapped propagation paths are introduced by the configuration strategy, and the influence of the vortex flow can be eliminated theoretically by averaging the line velocities of the overlapped paths. To achieve a fast detection speed, the projection data is collected via an electrical scan in a fan-beam mode. After rearrangement and interpolation of the projection data, the parallel beam filtered back projection (FBP) algorithm is implemented to reconstruct the axial flow field. Numerical simulations with the theoretical velocity profiles were performed. The compensation method for the vortex flow is proved to be effective and necessary, and the number of transducers required for reconstruction of common flow profiles was estimated. Accordingly, an ultrasonic tomographic velocimeter consisting of 2×12 transducers was fabricated. Experiments were conducted in the straight pipe and downstream of a single bend pipe and compared with the computational fluid dynamics (CFD) simulation results. As demonstrated, the ultrasonic tomographic velocimeter was capable of visualizing both symmetric and asymmetric axial flow fields with high reliability.     

Significant spatial co-distribution pattern discovery

Given instances (spatial points) of different spatial features (categories), significant spatial co-distribution pattern discovery aims to find subsets of spatial features whose spatial distributions are statistically significantly similar to each other. Discovering significant spatial co-distribution patterns is important for many application domains such as identifying spatial associations between diseases and risk factors in spatial epidemiology. Previous methods mostly associated spatial features whose instances are frequently located together; however, this does not necessarily indicate a similarity in the spatial distributions between different features. Thus, this paper defines the significant spatial co-distribution pattern discovery problem and subsequently develops a novel method to solve it effectively. First, we propose a new measure, dissimilarity index, to quantify the difference between spatial distributions of different features under the spatial neighbor relation and then employ it in a distribution clustering method to detect candidate spatial co-distribution patterns. To further remove spurious patterns that occur accidentally, the validity of each candidate spatial co-distribution pattern is verified through a significance test under the null hypothesis that spatial distributions of different features are independent of each other. To model the null hypothesis, a distribution shift-correction method is presented by randomizing the relationships between different features and maintaining spatial structure of each feature (e.g., spatial auto-correlation). Comparisons with baseline methods using synthetic datasets demonstrate the effectiveness of the proposed method. A case study identifying co-morbidities in central Colorado is also presented to illustrate the real-world applicability of the proposed method.     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.     

An industrial case study on variability handling in large enterprise software systems

ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices.     

Characterization of sea water ageing effects on mechanical properties of carbon/epoxy composites for tidal turbine blades

In recent years, many tidal turbine projects have been developed using composites blades. Tidal turbine blades are subject to ocean forces and sea water aggressions, and the reliability of these components is crucial to the profitability of ocean energy recovery systems. The majority of tidal turbine developers have preferred carbon/epoxy blades, so there is a need to understand how prolonged immersion in the ocean affects these composites. In this study the long term behaviour of different carbon/epoxy composites has been studied using accelerated ageing tests. A significant reduction of composite strengths has been observed after saturation of water in the material. For longer immersions only small further changes in these properties occur. No significant changes have been observed for moduli nor for composite toughness. The effect of sea water ageing on damage thresholds and kinetics has been studied and modelled. After saturation, the damage threshold is modified while kinetics of damage development remain the same.