Global and local multi-trace formulations provide a flexible and efficient method for the modelling of scattering and transmission of time harmonic electromagnetic waves by composite structures. This contribution extends the domain of applicability of global multi-trace formulations to cases where penetrable domains, perfectly conducting domain, and perfectly conducting thin sheets are all part of the design. A novel and easy to implement resonance free equation to model scattering by perfect conductors is introduced. A Calderón preconditioner designed to limit the number of iterations required for the solution of the discrete system is designed and studied. The accuracy, flexibility, and efficiency of the method is demonstrated on a representative range of examples.

Part quality monitoring and control in wire-based directed energy deposition additive manufacturing (w-DEDAM) processes has been garnering continuous interest from both the academic and industrial sectors. However, maintaining a consistent layer height and ensuring that the wall height aligns closely with the design, as depicted in computer-aided design (CAD) models, pose significant challenges. These challenges arise due to the uncertainties associated with the manufacturing process and the working environment, particularly with extended processing times. To achieve these goals in an industrial scenario, the deposition geometry must be measured with precision and efficiency throughout the part-building process. Moreover, it is essential to comprehend the changes in the interlayer deposition height based on various process parameters. This paper first examines the behaviour of interlayer deposition height when process parameters change within different wall regions, with a particular focus on the transition areas. In addition, this paper explores the potential of geometry monitoring information in implementing interlayer wall height compensation during w-DEDAM part-building. The in-process layer height was monitored using a coherent range-resolved interferometry (RRI) sensor, and the accuracy and efficiency of this measurement were carefully studied. Leveraging this information and understanding of deposition geometry, the control points of the process parameters were identified. Subsequently, appropriate and varied process parameters were applied to each wall region to gradually compensate for wall height. The wall height discrepancies were generally compensated for in two to three layers.

Process control and quality assurance of wire + arc additive manufacturing (WAAM) and automated welding rely heavily on in-process monitoring videos to quantify variables such as melt pool geometry, location and size of droplet transfer, arc characteristics, etc. To enable feedback control based upon this information, an automatic and robust segmentation method for monitoring of videos and images is required. However, video segmentation in WAAM and welding is challenging due to constantly fluctuating arc brightness, which varies with deposition and welding configurations. Additionally, conventional computer vision algorithms based on greyscale value and gradient lack flexibility and robustness in this scenario. Deep learning offers a promising approach to WAAM video segmentation; however, the prohibitive time and cost associated with creating a well-labelled, suitably sized dataset have hindered its widespread adoption. The emergence of large computer vision models, however, has provided new solutions. In this study a semi-automatic annotation tool for WAAM videos was developed based upon the computer vision foundation model SAM and the video object tracking model XMem. The tool can enable annotation of the video frames hundreds of times faster than traditional manual annotation methods, thus making it possible to achieve rapid quantitative analysis of WAAM and welding videos with minimal user intervention. To demonstrate the effectiveness of the tool, three cases are demonstrated: online wire position closed-loop control, droplet transfer behaviour analysis, and assembling a dataset for dedicated deep learning segmentation models. This work provides a broader perspective on how to exploit large models in WAAM and weld deposits.

The RWG basis widely used in the discretisation of the EFIE is traditionally defined over interior edges of the structure's mesh when modelling charge-neutral scattering problems. In this paper, a careful extension to the RWG function space that allows for flow of current in and out of a structure via its boundary edges while maintaining current conservation is constructed. This space is appropriate for the computation of capacitance, where (i) a constant voltage difference is maintained between two components making up the device, and (ii) the total current is conserved. Using this basis implicitly enforces a constant potential difference between the metal plates (cf. natural boundary conditions), and explicitly places a restriction on the current (cf. essential boundary conditions). It improves upon the classic delta gap excitation of capacitive structures in that it is asymptotically independent of the triangulation used to describe the device's geometry.

We demonstrate how the coupling of a full-wave time-domain boundary element method (BEM) solver with a circuit solver can be used to model 1) the generation of high frequency oscillations in resonant tunneling diode (RTD) oscillators, and 2) the mutual coupling and synchronization of non-identical RTDs with significant differences in frequencies to achieve coherent power combination. Numerical simulations show a combined output power of up to 3.7 times a single oscillator in synchronized devices. The non-differential conductance of the RTD is modeled as a lumped component with a non-linear current-voltage relationship. The lumped element is coupled to the radiating structure using a finite-gap model in a consistent and discretisation independent manner. The resulting circuit equations are solved simultaneously and consistently with time-domain electric field integral equations that model the transient scattering of electromagnetic (EM) fields from conducting surfaces that make up the device. This paper introduces three novel elements: (i) the application of a mesh independent feed line to the modelling of feed lines of RTD devices, (ii) the coupling of the radiating system to a strongly non-linear component with negative differential resistance, and (iii) the verification of this model with circuit models where applicable and against the experimental observation of synchronisation when two RTDs are placed in close proximity. These three elements provide a methodology that create the capacity to model RTD sources and related technology.

New solid-state sources of Gigahertz-Terahertz electromagnetic radiation continue to have many applications in high-speed electronics, communications, security, and medicine. To develop new devices, it is important to understand the coupling of such high-frequency sources not only with each other but also with their environment e.g. to achieve increased power output, synchronization, and to control interference. Using Graphene-based materials is particularly promising due to its high electron mobility and configurability of the device structures. However, accurately modelling its electromagnetic behavior computationally along with the inherent complexities of the device itself (e.g. non-linearities, and quantum effects) can be quite challenging using current tools. To address this, we use a simplified approximate model to reduce the complexity of the structure and derive new formulations that describe its electromagnetic and intrinsic behaviours. In this poster, we report new formulations, finite element spaces and general progress in modelling a graphene hexagonal-boron-nitride resonant tunneling diode (GRTD) using the time-domain boundary element method. We also explore the possibility of mutual coupling and synchronization between two GRTD devices as well as their radiation patterns and total output power.