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This paper aims to propose a method of the safety boundary protection for unmanned aerial vehicles (UAVs) in the icing conditions.

Forty icing conditions were sampled in the continuous maximum icing conditions in the Appendix C of the Federal Aviation Regulation Part 25. Icing numerical simulations were carried out for the 40 samples and the anti-icing thermal load distribution in full evaporation mode were obtained. Based on the obtained anti-icing thermal load distribution, the surrogated model of the anti-icing thermal load distribution was established with proper orthogonal decomposition and Kriging interpolation. The weather research and forecasting (WRF) model was used for meteorological simulations to obtain the icing meteorological conditions in the target area. With the obtained icing conditions and surrogated model, the anti-icing thermal load distribution in the target area and the variation with time can be determined. According to the energy supply of the UAVs, the graded safety boundaries can be obtained.

The surrogated model can predict the effects of five factors, such as temperature, velocity, pressure, median volume diameter (MVD) and liquid water content (LWC), on the anti-icing thermal load quickly and accurately. The simulated results of the WRF mode agree well with the observed results. The method can obtain the graded safety boundaries.

The method has a reference significant for the safety of the UAVs with the limited energy supply in the icing conditions.

Realistic composite vehicles with 2, 3, 5 and 9 axles, consisting of a truck with one or two trailers, are addressed in this paper by computational models for vehicle–bridge interaction analysis.

The vehicle–bridge interaction (VBI) models are formed by sets of 2-D rigid blocks interconnected by mass, damping and stiffness elements to simulate their suspension system. The passage of the vehicles is performed at different speeds. Several rolling surface profiles are admitted, considering the maintenance grade of the pavement. The spectral density functions are generated from an experimental database to form the longitudinal surface irregularity profiles. A computational code written in Phyton based on the finite element method was developed considering the Euler–Bernoulli beam model.

Several models of composite heavy vehicles are presented as manufactured and currently travel on major roads. Dynamic amplification factors are presented for each type of composite vehicle.

The VBI models for compound heavy vehicles are 2-D.

This work contributes to improving the safety and lifetime of the bridges, as well as the stability and comfort of the vehicles when passing over a bridge.

The structural response of the bridge is affected by the type and size of the compound vehicles, their speed and the conservative grade of the pavement. Moreover, one axle produces vibrations that can be superposed by the vibrations of the other axles. This effect can generate not usual dynamic responses.

This paper introduced the simple synthesis process of self-cleaning coating with fog-resistance property using hydrophobic polydimethylsiloxane (PDMS) polymer and nano-calcium carbonate (nano-CaCO₃) and titanium dioxide (TiO₂).

The synthesis method of PDMS/nano-CaCO₃-TiO₂ is based on sol-gel process. The crosslinking between PDMS and nanoparticles is driven by the covalent bond at temperature of 50°C. The 3-Aminopropyltriethoxysilane is used as binder for nanoparticles attachment in polymer matrix. Two fabrication methods are used, which are dip- and spray-coating methods.

The prepared coated glass fulfilled the requirement of standard self-cleaning and fog-resistance performance. For the self-cleaning test BS EN 1096-5:2016, the coated glasses exhibited the dust haze value around 20%–25% at tilt angle of 10°. For the antifog test, the coated glasses showed the fog haze value were below 2% and the gloss value were above 85%. The obtained results completely achieved the standard antifog value ASTM F659-06 protocol.

Findings will provide an infrastructure support for the building glass to enhance building’s energy efficiency, cleaning performance and friendly environment.

This study proposed the simple synthesis method using hydrophobic polymer and nano-CaCO₃ and nano-TiO₂, which can achieve optimum self-cleaning property at low tilt angle and fog-resistance performance for building glass.

The research findings have high potential for building company, cleaning building company and government sector. The proposed project capable to reduces the energy consumption about 20% per annum due to labor cost, time-consuming and safety during manual cleaning.

The novel method to develop self-cleaning coating with fog-resistance using simple synthesis process and fabrication method for building glass application.

Entrepreneurial ventures aspiring to disrupt existing market incumbents often use business-model innovation to increase the attractiveness of their offerings. A value proposition is the central element of a business model, and is critical for this purpose. However, how entrepreneurial ventures modify their value propositions to increase the attractiveness of their comparatively inferior offerings is not well understood. The purpose of this paper is to analyze the value proposition innovation (VPI) of aspiring disruptors.

The authors used a flexible pattern matching approach to ground the inductive findings in extant theory. The authors conducted 21 semi-structured interviews with managers from startups in the global electric vehicle industry.

The authors developed a framework, showing two factors, determinants and tactics, that play a key role in VPI connected by a continuous feedback loop. Directed by the determinants of cognitive antecedents, development drivers and realization capabilities, aspiring disruptors determine the scope, focus and priorities of various configuration and support tactics to enable and secure the success of their value proposition.

The authors contribute to theory by showing how cognitive antecedents, development drivers and capabilities determine VPI tactics to disrupt existing market incumbents, furthering the understanding of configuration tactics. The results have important implications for disruptive innovation theory, and entrepreneurship research and practice, as they offer an explanatory framework to analyze strategies of aspiring disruptors who increase the attractiveness of sustainable technologies, thereby accelerating their diffusion.

The UAE has set an ambitious target to become one of the most sustainable countries in the world. In addition, the country's infrastructure is playing a pivotal role in terms of electric vehicle (EV) usability with regard to its roads, power generation capacity, availability of charging stations and the drive towards customer adoption. The readiness for EVs in the UAE is assessed in this study as part of its development towards its sustainable target. This research aims to study EV readiness among the UAE car users from a sustainability perspective.

The proposed methodology follows with a comprehensive literature review to identify the various drivers of EV readiness and their contribution to sustainability. A list of hypotheses was developed based on the identified drivers to EV readiness. A questionnaire survey was designed to validate the hypothesis, and data were collected from consumers in the UAE. In total, 140 complete responses were received across different consumers and the results were studied using partial least square based structural equation modeling (PLS-SEM) method.

An initial framework for EV readiness was developed, and analyses of the variables that are driving the relationships was done. The analysis confirmed that quality of service, power quality and infrastructure are positively linked to EV readiness in the UAE. However, the role of blockchain as a moderator to enhance the relationship between power quality, infrastructure and sustainability is not significant, indicating blockchain adoption in the UAE is still nascent in nature. However, its adoption has some potential to save energy.

The research is limited to the UAE region in terms of sample collection and respondents' profile. Further, research on EV readiness seemed to be early at present and therefore this research on EV readiness and its associated variables could set future research directions.

Logistics industry and automotive industries will benefit from the outcomes of the study especially while operating in the UAE. Also, the research recommends EV makers to understand the relationship between quality of service, power quality, infrastructure, EV readiness and sustainability in order to move towards a more sustainable transportation future.

The learning outcomes of this case study are to understand the business model canvas and value propositions and apply advanced business innovation tools in electric vehicle business models; evaluate the current cargo vehicle scenarios at national and global levels and draw out the possibilities and costs for a new player; extrapolate the future scenario of the cargo economy, its electrification and positioning in a business-to-business (B2B) and business-to-customer (B2C) segment, especially for a developing economy; and improve the student’s ability to get organisational buy-in and execute new business models.

LoadExx is a fully electrified electric cargo service focusing on logistics in Kolkata, a metropolitan city in the eastern part of the country. The service of LoadExx commenced in January 2021 in the B2B segment after overcoming its then issues of driver hesitancy and customer anxiety and financial issues to adopt electrified cargo systems. The conundrum faced by LoadExx in its commencement thus had been solved under the able guidance of its owner Amit Arora. The case study was positioned four months after the commencement of LoadExx. To gain market power and traction, Arora and his team came up with the idea of market expansion. However, the current conundrum was whether LoadExx would enter the B2C segment in its current location or expand with the same business model to other parts of the country. The expansion was to be implemented in the immediate future to retain its rarity and reduce the imitability of the business model of LoadExx. This case study details the logistics and market operations of the cargo sector, especially electric cargo, in a developing economy, especially India. A teaching note supplementing the “Cracking the conundrum of e-cargo logistics: curious case of LoadExx” case study has been provided.

This case study is designed for undergraduate and postgraduate students and senior management professionals in executive education programmes undertaking courses in logistics management and supply chain operations and related cargo logistics courses. This case study denotes integrating key processes from end-users and gaining the trust of drivers, thereby showing the perspective of the plight and conundrums of a cargo aggregator working in the B2C segment. This case study could be used to discuss concepts related to not-for-profit firms, aggregators, policymakers and think tanks.

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

The global automobile industry is striving towards a sustainable future. Emerging countries including India are gearing up for the revolution. Considering the key role of customer acceptance in the success of any technological shift, the study endeavors to ascertain the catalysts accelerating the adoption of Electric Two-Wheelers (E2W) in India by leveraging an extended Unified Theory of Acceptance and Use of Technology-2 model. The same would assist Electric Vehicle (EV) stakeholders in directing their efforts toward pivotal aspects having the potential to significantly bolster E2W penetration.

Data was collected using convenience sampling technique from 1,254 electric two-wheeler owners across four Indian states and analyzed using Structural Equation Modelling.

Performance Expectancy, Price Value and Hedonic Motivation have a significant influence on purchase intention leading to actual buying behavior. Effort Expectancy, Social Influence, habit value and facilitating conditions were insignificant. Pro-Environmental Approach and Government Support significantly impact adoption intention and behavior respectively in addition to model predictors thus supporting the study’s novelty. Purchase intention proved to influence Actual Buying Behavior. Synergized efforts of EV stakeholders towards performance innovation, cost-effectiveness, improved infrastructure and information diffusion on sustainability and user-friendliness could aid in achieving transition to green mobility.

The study predominantly intends to address the intention–behavior gap related to electric two-wheelers in India. Also, two additional constructs, government support and pro-environmental approach, were incorporated resulting in a novel research framework that aims to test their nuanced ability to impact the model predictors.

This paper aims to assess the impact of electrifying the environmental control system (ECS) and ice protection system (IPS), the primary pneumatic system consumers in a conventional commercial transport aircraft, on aircraft weight, range, and fuel consumption.

The case study was carried out on Airbus A321-200 aircraft. Design, modelling and analysis processes were carried out on Pacelab SysArc software. Conventional and electrical ECS and IPS architectures were modelled and analysed considering different temperature profiles.

The simulation results have shown that the aircraft model with ±270 VDC ECS and IPS architecture is lighter, has a more extended range and has less relative fuel consumption. In addition, the simulation results showed that the maximum range and relative fuel economy of all three aircraft models increased slightly as the temperature increased.

Considering the findings in this paper, it is seen that the electrification of the conventional pneumatic system in aircraft has positive contributions in terms of weight, power consumption and fuel consumption.

The positive contributions in terms of weight, power consumption and fuel consumption in aircraft will be direct environmental and economic contributions.

Apart from the conventional ECS and IPS of the aircraft, two electrical architectures, 230 VAC and ±270 VDC, were modelled and analysed. To see the effects of the three models created in different temperature profiles, analyses were done for cold day, ISA standard day and hot day temperature profiles.

The basis of safe flight is the management of risks. This paper aims to present a new process-based risk assessment model, with an approach to calculate the risk score.

Since thousands of minor changes occur within ground operations, it is difficult to calculate how much risk these variations will pose. This paper proposes a risk assessment model fed from analysis of ground operation processes using functional resonance analysis method (FRAM) and fuzzy logic.

FRAM is used to detect variations in ground operation. Using the FRAM analysis, it has been revealed how much risk the process steps described in the procedures involve. The risk score was calculated by combining the probability value obtained from the airline’s database and the severity assessment of the expert group in fuzzy logic. The risk level can be monitored dynamically with the transfer of events in the airline’s database to the process-based risk assessment model.

FRAM analysis, which is used to detect function variations before undesirable risk occurs, has brought a proactive approach to risk assessment. The process-based risk assessment model allows the creation of new safety parameter indicators to be followed to reduce the risk level of the function with a high-risk level. The proposed approach can be used for other operational areas in aviation as well.

This study aims to fabricate a multifunctional electromagnetic interference (EMI) shielding composite fabric with simultaneous high-efficiency photothermal conversion and Joule heating performances.

A multifunctional polypyrrole (PPy) hydrogel/multiwalled carbon nanotube (MWCNT)/cotton EMI shielding composite fabric (hereafter denoted as PHMC) was prepared by loading MWCNT onto tannin-treated cotton fabric, followed by in situ crosslinking-polymerization to synthesize three-dimensional (3D) conductive networked PPy hydrogel on the surface of MWCNT-coated cotton fabric.

Benefiting from the unique interconnected 3D networked conductive structure of PPy hydrogel, the obtained PHMC exhibited a high EMI-shielding effectiveness vale of 48 dB (the absorbing electromagnetic wave accounted for 84%) within a large frequency range (8.2–12.4 GHz). Moreover, the temperature of the laminated fabric reached 54°C within 900 s under 15 V, and it required more than 100 s to return to room temperature (28.7°C). When the light intensity was adjusted to 150 mW/cm², the PHMC temperature was about 38.2°C after lighting for 900 s, indicating high-efficiency electro-photothermal effect function.

This paper provides a novel strategy for designing a type of multifunctional EMI shielding composite fabric with great promise for wearable smart garments, EMI shielding and personal heating applications.