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The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

A structural load estimating methodology was developed for the RLV-TD HEX-01 mission, the maiden winged body technology demonstrator vehicle of ISRO. The technique characterizes atmospheric regime of flight from vehicle loads perspective and ensures adequate structural margin considering atmospheric variations and system level perturbations. Primarily the method evaluates time history of station loads considering effects of vehicle dynamics and structural flexibility. Station loads in the primary structure are determined by superposition of quasi-static aerodynamic loads, dynamic inertia loads, control surface loads and propulsion system loads based on actual physics of the system. Spatial aerodynamic distributions at various Mach numbers along the trajectory have been used in the study. Argumentation in aerodynamic loads due to vehicle flexibility is assessed through the use of spatial aerodynamic distributions.

In order to study the tire friction characteristics under wet skid surface, the “pseudo” hydrodynamic pressure bearing effect is used to be equivalent to the hydrodynamics of water film, and an advanced Lugre tire hydroplaning dynamic model is developed by combining the arbitrary pressure distribution function. The water hydroplaning dynamic tests were carried out for 285/70R19.5 tire under wet of different water film thickness and dry conditions, and the parameters of the advanced Lugre tire dynamic model were identified. The results show that the tire water-skiing model proposed in this paper can effectively simulate the friction characteristics of tires under different water film thicknesses. Under dry conditions, 0.5mm water film and 1mm water film road conditions, the relative errors of the maximum tire friction coefficient between the tested and advanced Lugre tire model are 1.11%, 0.12% and 0.16%, respectively.

Global automobile manufacturers are increasingly adopting vehicle architecture development systems in the early stages of product development. This strategic move is aimed at rationalizing their product portfolios based on similar specifications and functions, with the overarching goal of simplifying design complexities and enabling the creation of scalable vehicles. Nevertheless, ensuring consistent performance in this dynamic context poses formidable challenges due to the wide range of design possibilities and potential variations at each development stage. This paper introduces an efficient reliability analysis process designed to identify and mitigate the distribution of Ride and Handling (R&H) performance. We employ a range of reliability analysis techniques, including Latin Hypercube Sampling and the enhanced Dimension Reduction (eDR) method, utilizing various types of models such as surrogate models and multi-body dynamics models.

An escalating demand for improved heat dissipation from electronic components is driven by the imperative need to eliminate the accumulated heat that gradually builds up over time. In this study, a 3-D simulation was carried out to analyze the heat distribution performance of a heat sink based on PCM/NePCM. The heat sink was subjected to varying heat fluxes ranging from 3-7 kW/m2, and its performance was evaluated over time. The findings of the computational research indicate that using PCM assists in maintaining the heat sink base's temperature within lower bounds, and leads to uniform melting within the heat sink. Further, inclusion of Alumina nano particles integration in PCM enhanced the performance of heat sink. The percentage reduction in charging time of NePCM without fins (φ = 1%, 2.5% and 5%) in comparison to the Pure-PCM (φ = 0%) is 6%, 11% and 51% respectively at 6 kW/m2 input.

The safety of commercial aviation industry has come under extensive scrutiny and how the system safety process is applied. One specific system safety regulation concerns how unsafe system operating conditions are meeting regulatory requirements. Minimal regulatory guidance was available on this topic and an industry committee (American Society for Testing of Materials) decided to provide a consensus standard with input from a cross-section of airplane manufacturers, suppliers, and regulatory authorities on what is meant by an unsafe system operating condition and how compliance can be shown to the regulation(s). The committee determined that an unsafe system operating condition is when a failure condition severity increases (to hazardous or catastrophic) due to crewmember(s) inaction. For example, if a hazard has occurred it is possible the severity can increase to an unacceptable level as the crewmember(s) are not aware of the hazard.

The aircraft lifecycle involves thousands of transactions and an enormous amount of data being exchanged across the stakeholders in the aircraft ecosystem. This data pertains to various aircraft life cycle stages such as design, manufacturing, certification, operations, maintenance, and disposal of the aircraft. All participants in the aerospace ecosystem want to leverage the data to deliver insight and add value to their customers through existing and new services while protecting their own intellectual property. The exchange of data between stakeholders in the ecosystem is involved and growing exponentially. This necessitates the need for standards on data interoperability to support efficient maintenance, logistics, operations, and design improvements for both commercial and military aircraft ecosystems. A digital thread defines an approach and a system which connects the data flows and represents a holistic view of an asset data across its lifecycle.

Since the early days of aviation, when an AC-type generator became a primary source of electrical power for all aircraft systems, the demand for electrical power has steadily grown. Following rapid technology and scientific advancements in the aerospace industry, the complexity and criticality of all aircraft systems have increased to the point where multiple independent and isolated electrical power sources are required. In such an environment, with two or more variable-frequency AC-type generators that can be simultaneously activated to provide electrical power to the aircraft power distribution system, a safe power transfer process becomes a major priority. This means that any two independent aircraft AC power sources with different frequencies or phase angles cannot be connected simultaneously to a common power bus.

At present, the problem of global warming is becoming more and more serious, and the transformation of energy structure is very important. The rotary engine has the advantages of small size, high power-to-weight ratio, and high fuel adaptability, which makes it promising for application in the fields of new energy vehicle range extender and unmanned aerial vehicle.

The driving risk field model offers a feasible approach for assessing driving risks and planning safe trajectory in complex traffic scenarios. However, the conventional risk field fails to account for the vehicle size and acceleration, results in the same trajectories are generated when facing different vehicle types and unable to make safe decisions in emergency situations. Therefore, this paper firstly introduces the acceleration and vehicle size of surrounding vehicles for improving the driving risk model. Then, an integrated decision-making and planning model is proposed based on the combination of the novelty risk field and model predictive control (MPC), in which driving risk and vehicle dynamics constraints are taken into consideration. Finally, the multiple driving scenarios are designed and analyzed for validate the proposed model.

Unmanned Aircraft Systems (UAS) have been growing over the past few years and will continue to grow at a faster pace in future. UAS faces many challenges in certification, airspace management, operations, supply chain, and maintenance. Blockchain, defined as a distributed ledger technology for the enterprise that features immutability, traceability, automation, data privacy, and security, can help address some of these challenges. However, blockchain also has certain challenges and is still evolving. Hence it is essential to study on how blockchain can help UAS. G-31 technical committee of SAE International responsible for electronic transactions for aerospace has published AIR 7356 [1] entitled Opportunities, Challenges and Requirements for use of Blockchain in Unmanned Aircraft Systems Operating below 400ft above ground level for Commercial Use. This paper is a teaser for AIR 7356 [1] document.

This study presents the results of the ICE GENESIS 2021 Swiss Jura Flight Campaign in a way that is readily usable for ice accretion modelling and aims at improving the description of snow particles for model inputs. 2D images from two OAP probes, namely 2D-S and PIP, have been used to extract 3D shape parameters in the oblate spheroid assumption, as there are the diameter of the sphere of equivalent volume as ellipsoid, sphericity, orthogonal sphericity, and an estimation of bulk density of individual ice crystals through a mass-geometry parametrization. Innovative shape recognition algorithm, based on Convolutional Neural Network, has been used to identify ice crystal shapes based on these images and produce shape-specific mass particle size distributions to describe cloud ice content quantitatively in details. 3D shape descriptors and bulk density have been extracted for all the data collected in cloud environments described in the regulation as icing conditions.

Aircraft icing remains a significant threat to aviation safety. Software that predicts the impingement and ice accretion on full aircraft geometries and aircraft components are in demand and NASA Glenn is committed to produce software that meets this need. One of the key parameters affecting an accurate prediction of iced geometry is the effect of ice roughness on the heat transfer coefficient. While many efforts have been made to implement the roughness in the flow solver, this report takes a correlation for roughness height distribution that is based on experimental measurements and demonstrates how to relate those measurements to an augmentation to the heat transfer coefficient provided by the flow solution. The outcome of this effort was the callibration of defaults for user supplied parameters to this correlation through comparison with 95 large glaze conditions from experiment by adjusting user-supplied parameters in the roughness augmentation equation.

In the framework of the European ICE GENESIS project (https://www.ice-genesis.eu/), a field experiment was conducted in the Swiss Jura in January 2021 in order to characterize snow microphysical properties and document snow conditions for aviation industry purposes. Complementary to companion papers reporting on snow properties, this study presents an investigation on mixed-phase conditions sampled during the ICE GENESIS field campaign. Using in situ measurement of the liquid and total water content, the ice mass fraction is calculated and serves as a criteria to identify mixed-phase conditions. In the end, mixed phase conditions were identified in almost 30 % of the 3800 km long cloud samples included in the ICE GENESIS dataset. The data suggests that the occurrence of mixed-phase does not clearly depend on temperature in the 0 to -10 °C range, but varies significantly from one cloud system to another.

Threats to aviation safety as a result of super-cooled large drops (SLD) has been addressed by the FAA rules change (14 CFR Part 25) with the additional icing certification requirement. SLD clouds often consist of bi-modal drop size spectra leading to significant problems in simulating and characterizing these conditions in situ and in icing wind tunnels. Legacy instrumentation for measuring drop size distributions and liquid water content are challenged under these conditions. The large size range measurement problem is addressed with the development of the Phase Doppler Interferometer, Flight Probe Dual-Range (PDI FPDR). The method is described in this report along with the measurement capabilities including the dynamic measurement range and overall working size range. The PDI instrument bases drop size measurements on the light wavelength as the measurement length scale. The light wavelength is a much more robust scale, especially as compared to the light scattering intensity.

Aerospace manufacturing is improving its productivity and growth by expanding its capacity for production by investing in new tools and more equipment to provide additional capacity and flexibility in the face of widespread supply disruptions and unpredictable demand. However, the cost of such measures can result in increased unit costs. Alternatively, productivity and quality can be improved by utilizing available resources better to reach optimal performance and react to emerging disruptions and changes. Elastic Manufacturing is a new paradigm that aims to change the response behavior of firms to meet sudden market demands based on automated analysis of the utilization of the available resources, and autonomous allocation of capacity to use resources in the most efficient manner. Through digitalization of the shopfloor, streaming data from equipment enables companies to identify areas for improvement and boost the efficiency without large capital expenditure.

Certification standards for high-assurance systems include objectives for demonstrating compliance of process artifacts such as requirements and code with style guidelines and other standards. With the emergence of model-based development, similar objectives have been specified that apply to models. Demonstration of compliance is often achieved by employing a static analysis linter tool. This paper describes Resolint, an open-source, lightweight linter tool for checking compliance of Architecture Analysis and Design Language (AADL) models with modeling guidelines. AADL enables engineers to describe the key elements of distributed, real-time, embedded system architectures with a sufficiently rigorous semantics. In addition, AADL provides an annex mechanism for extending the base language, enabling new kinds of analyses and tool support. Resolint uses the AADL annex capability to provide a language for specifying style guide rule sets.

Recent advancements in eVTOL aircraft have generated significant interest within and beyond the traditional aviation industry. One promising application is for last-mile (and middle-mile) military transport and logistics, which can complement current mission capabilities and enhance operational readiness. With the dynamic and varying global challenges facing military operations, eVTOL aircraft can offer timely, on-demand, and potentially cost-effective aerial mobility components to the overall solution.

Currently, the Aviation industry uses traditional methods of communication, coordination, & human interaction to give disposition to resolve any kind of nonconformance occurrences which occur during manufacturing or operation of commercial or defense products. This involves increased in-person interaction and additional travel, especially to address the nonconformance issues arising at supplier plants or airports around the globe. During Covid and post-Covid environments, human interactions for the transfer of detailed information at different & distant manufacturing plant locations has been difficult, since support engineering teams (Example: Liaison, Product Review, Quality, Supplier Quality, and Manufacturing Engineering, and/or Service Engineering) have been working remotely.

Bolted joint is a popular method for assembly of mechanical systems which are typically designed by considering members to be in full contact without initial gap. However, manufacturing imperfections or part tolerances can introduce gaps between members. This initial gap is proven to have an adverse effect on the performance of bolted connection. The gap introduces additional bending moments (B.M.) during tightening operation and affects the loads shared by the threads thereby aggravating thread strip and fatigue performance. The aim of this paper is to provide a robust approach for predicting this premature failure of bolted joint due to initial gaps in assembly. VDI 2230 industry guideline for fastener assessment does not account for bending effect due to initial gap. To address this limitation, a “Coupled Analytical and FEA based” approach is developed to accurately capture initial bending moment and its effect on distribution of loads between the engaged threads.