This research work presents an implantable antenna that operates at 5.8 GHz. By using a radiator with a loop-based design, the antenna can be made smaller. Radiator is made up of three connected rectangular loops. On the substrate’s back side, an I-shaped ground plane is used. As substrate and superstrate, polydimethylsiloxane (PDMS) with dimensions of 7 mm × 5 mm × 0.3 mm is used. The conducting sections are made using copper foil that is 30 µm thick. The suggested antenna is examined by the implantable medical device using realistic human scalp phantom models and a homogenous skin box. Simulated study revealed that it operates around 5.8 GHz with a bandwidth from 5.69 to 5.92 GHz. The specific absorption rate was 0.28 and 0.26 W/kg for skin box and human scalp phantoms, respectively, at 1 mW input power across 1 g volume tissue.

An ultra-wideband (UWB) and compact-size four-port multiple input multiple output (MIMO) antenna with a footprint of 34 mm × 34 mm fed by an asymmetric coplanar strip (ACS) is investigated. The proposed antenna is composed of four orthogonally placed identical modified elliptical-shaped radiators and achieves an impedance bandwidth of 3.4–12.2 GHz. By etching two inverted L-shaped slots in the radiator element, WLAN band and X-band are rejected in the operating communication range. Because of the usage of a meander line decoupler, the isolation enhancement at the 8–12 GHz band is achieved and the isolation is more than 18 dB for most of the UWB range. The performance of the proposed antenna is studied in terms of isolation between each port, radiation pattern, current distribution, gain, envelope correlation coefficient, diversity gain, and total active reflection coefficient. The compact size and reduced complexity make the proposed design highly suitable for portable devices.

The increase in global population and urbanization is presenting significant challenges to society: space is becoming increasingly scarce, demand is exceeding capacity for deteriorating infrastructure, transportation is fraught with congestion, and environmental impacts are accelerating. Underground space, and particularly tunnels, has a key role to play in tackling these challenges. However, the cost, risk, uncertainty, and complexity of the tunneling process have impeded its growth. In this paper, we envision several technological advancements that can potentially innovate and transform the mechanized tunneling industry, including artificial intelligence (AI), autonomous, and bio-inspired systems. The proliferation of AI may assist human engineers and operators in making informed decisions systematically and quantitatively based on massive real-time data during tunneling. Autonomous tunneling systems may enable precise and predictable tunneling operations with minimal human intervention and facilitate the construction of massive and large-scale underground infrastructure projects that were previously challenging or unfeasible using conventional methods. Bio-inspired systems may provide valuable references and strategies for more efficient tunneling design and construction concepts. While these technological advancements can offer great promise, they also face considerable challenges, such as improving accessibility to and shareability of tunneling data, developing robust, reliable, and explainable machine learning systems, as well as scaling the mechanics and ensuring the applicability of bio-inspired systems from the prototype level to real-world applications. Addressing these challenges is imperative to ensure the successful implementation of these innovations for future tunneling.

A fleet of aircraft can be seen as a set of degrading systems that undergo variable loads as they fly missions and require maintenance throughout their lifetime. Optimal fleet management aims to maximise fleet availability while minimising overall maintenance costs. To achieve this goal, individual aircraft, with variable age and degradation paths, need to operate cooperatively to maintain high fleet availability while avoiding mechanical failure by scheduling preventive maintenance actions. In recent years, reinforcement learning (RL) has emerged as an effective method to optimise complex sequential decision-making problems. In this paper, an RL framework to optimise the operation and maintenance of a fleet of aircraft is developed. Three cases studies, with varying number of aircraft in the fleet, are used to demonstrate the ability of the RL policies to outperform traditional operation/maintenance strategies. As more aircraft are added to the fleet, the combinatorial explosion of the number of possible actions is identified as a main computational limitation. We conclude that the RL policy has potential to support fleet management operators and call for greater research on the application of multi-agent RL for fleet availability optimisation.

The current paper is focused on the conceptual design of a thermal management system with a liquid working medium for a commuter hybrid-electric aircraft, featuring a series propulsion configuration. Regarding the system’s architecture, parametric analyses are conducted, by altering the number of heat exchangers. To clarify, a centralised and a decentralised thermal management system architecture are examined. Furthermore, a computational model calculates the temperatures during the system’s operation and the required coolant mass flows to sufficiently cool all the compartments. Subsequently, the required heat exchanger surface is determined and the weight of each compartment that comprises the thermal management system can be calculated. It is worth noting, that the compartments’ cold plate weight is integrated. The results indicate that the decentralised configuration results in lower temperature fields for all components compared to the centralised configuration. However, the latter weighs 32.2% lower at 158.22kg while the decentralised configuration weighs 233.48kg.

This research paper presents an application of the integrated process and product design (IPPD) approach for selecting the best joint configuration for dissimilar material joining in the early product design phase. The proposed methodology integrates the multi-criteria decision making (MCDM) approach with quality function deployment (QFD) to identify the key criteria for joint selection, including load-carrying capacity, size, cost per joint, ease of manufacturing, time consumption and deformation. Three types of joints (rivet, weld and adhesive) and two hybrid joints (adhesive-weld and adhesive-rivet) are considered for three dissimilar material configurations: carbon fiber-reinforced plastic (CFRP) aluminum, CFRP steel, and aluminum-steel. QFD is utilised to transform job requirements into design criteria, and in the second phase, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to choose the optimal joint configuration based on the weighted criteria acquired in the previous phase. The selected joint configuration is then validated through experimental study. The findings demonstrate that the proposed IPPD approach with QFD-TOPSIS techniques is highly effective for selecting mechanical joints for dissimilar material joining in the early design phase. The study concludes that the adhesive-rivet hybrid joint is the optimal solution among all alternatives. The proposed methodology can ultimately lead to improved product reliability and performance, as well as reduced development time and cost.

High-intensity vortex beams with tunable topological charges and low coherence are highly demanded in applications such as inertial confinement fusion (ICF) and optical communication. However, traditional optical vortices featuring nonuniform intensity distributions are dramatically restricted in application scenarios that require a high-intensity vortex beam owing to their ineffective amplification resulting from the intensity-dependent nonlinear effect. Here, a low-coherence perfect vortex beam (PVB) with a topological charge as high as 140 is realized based on the super-pixel wavefront-shaping technique. More importantly, a globally adaptive feedback algorithm (GAFA) is proposed to efficiently suppress the original intensity fluctuation and achieve a flat-top PVB with dramatically reduced beam speckle contrast. The GAFA-based flat-top PVB generation method can pave the way for high-intensity vortex beam generation, which is crucial for potential applications in ICF, laser processing, optical communication and optical trapping.

Mid-spatial frequency wavefront deformation can be deleterious for the operation of high-energy laser systems. When fluid cooled high-repetition-rate amplifiers are used, the coolant flow is likely to induce such detrimental mid-spatial frequency wavefront deformations. Here, we describe the design and performance of a 90 mm × 90 mm aperture, liquid-cooled Nd:phosphate split-slab laser amplifier pumped by flash-lamps. The performance of the system is evaluated in terms of wavefront aberration and gain at repetition rates down to 1 shot per minute. The results show that this single cooled split-slab system exhibits low wavefront distortions in the medium to large period range, compatible with a focus on target, and despite the use of liquid coolant traversed by both pump and amplified wavelengths. This makes it a potential candidate for applications in large high-energy laser facilities.

This paper presents the development and experimental utilization of a synchronized off-harmonic laser system designed as a probe for ultra-intense laser–plasma interaction experiments. The system exhibits a novel seed-generation design, allowing for a variable pulse duration spanning over more than three orders of magnitude, from 3.45 picoseconds to 10 nanoseconds. This makes it suitable for various plasma diagnostics and visualization techniques. In a side-view configuration, the laser was employed for interferometry and streaked shadowgraphy of a laser-induced plasma while successfully suppressing the self-emission background of the laser–plasma interaction, resulting in a signal-to-self-emission ratio of 110 for this setup. These properties enable the probe to yield valuable insights into the plasma dynamics and interactions at the PHELIX facility and to be deployed at various laser facilities due to its easy-to-implement design.