Excitation transport with collective radiative decay

We investigate a one-dimensional quantum emitter chain where transport of excitations and correlations takes place via nearest neighbor, dipole-dipole interactions. In the presence of collective radiative emission, we show that a phase imprinting wavepacket initialization procedure can lead to subradiant transport and can preserve quantum correlations. In the context of cavity mediated transport, where emitters are coupled to a common delocalized optical mode, we analyze the effect of frequency disorder and nonidentical photon-emitter couplings on excitation transport

Robotic Non-Destructive Testing

Non-destructive testing (NDT) and evaluation (NDE) are commonly referred to as the vast group of analysis techniques used in civil, medical, and industrial sectors to evaluate the properties of materials, tissues, components, or structures without causing any damage [...]

Quantitative and qualitative analysis of the mental models deployed by undergraduate students in explaining thermally activated phenomena

In this contribution we describe a research aimed at pointing out the quality of mental models undergraduate engineering students deploy when asked to create explanations for phenomena/processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are initially analyzed using researcher-generated categories of reasoning, based on the Physics Education Research literature on student understanding of the relevant physics content. The inferred students\u2019 mental models about the analyzed phenomena are categorized as practical, descriptive, or explanatory, based on an analysis of student responses to the questionnaire. A qualitative analysis of interviews conducted with students after the questionnaire administration is also used to deepen some aspects which emerged from the quantitative analysis and validate the results obtained

Interleukin-2-based therapy following surgery for renal cell carcinoma metastatic to the chest wall.

Herein, thè authors report two cases of renai celi carcinoma with solitary metastasis to thè chest wall. lnterleukin-2-based therapy following nephrectomy and resection of thè metastatic lesion of thè chest wall resulted in improvement of quality of life and in prolonged diseasefree survival in ali patients. They believe that an aggressive surgical approach, in selected patients with metastatic renai celi carcinoma, may improve patients' response to immunotherap

Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction

Tessellated surfaces generated from point clouds typically show inaccurate and jagged boundaries. This can lead to tolerance errors and problems such as machine judder if the model is used for ongoing manufacturing applications. This paper introduces a novel boundary point detection algorithm and spatial FFT-based filtering approach, which together allow for direct generation of low noise tessellated surfaces from point cloud data, which are not based on pre-defined threshold values. Existing detection techniques are optimized to detect points belonging to sharp edges and creases. The new algorithm is targeted at the detection of boundary points and it is able to do this better than the existing methods. The FFT-based edge reconstruction eliminates the problem of defining a specific polynomial function order for optimum polynomial curve fitting. The algorithms were tested to analyse the results and measure the execution time for point clouds generated from laser scanned measurements on a turbofan engine turbine blade with varying numbers of member points. The reconstructed edges fit the boundary points with an improvement factor of 4.7 over a standard polynomial fitting approach. Furthermore, through adding artificial noise it has been demonstrated that the detection algorithm is very robust for out-of-plane noise lower than 25% of the cloud resolution and it can produce satisfactory results when the noise is lower than 75%

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Many industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences

Introducing a novel mesh following technique for approximation-free robotic tool path trajectories

Modern tools for designing and manufacturing of large components with complex geometries allow more flexible production with reduced cycle times. This is achieved through a combination of traditional subtractive approaches and new additive manufacturing processes. The problem of generating optimum tool-paths to perform specific actions (e.g. part manufacturing or inspection) on curved surface samples, through numerical control machinery or robotic manipulators, will be increasingly encountered. Part variability often precludes using original design CAD data directly for toolpath generation (especially for composite materials), instead surface mapping software is often used to generate tessellated models. However, such models differ from precise analytical models and are often not suitable to be used in current commercially available path-planning software, since they require formats where the geometrical entities are mathematically represented thus introducing approximation errors which propagate into the generated toolpath. This work adopts a fundamentally different approach to such surface mapping and presents a novel Mesh Following Technique (MFT) for the generation of tool-paths directly from tessellated models. The technique does not introduce any approximation and allows smoother and more accurate surface following tool-paths to be generated. The background mathematics to the new MFT algorithm are introduced and the algorithm is validated by testing through an application example. Comparative metrology experiments were undertaken to assess the tracking performance of the MFT algorithms, compared to tool-paths generated through commercial software. It is shown that the MFT tool-paths produced 40% smaller errors and up to 66% lower dispersion around the mean values

Robotization of the IR-Thermographic technique – impact on the visualisation quality and considerations on the data workflow

Quality control automation is becoming increasingly popular in industrial production lines. Active thermography techniques are well-regarded for their adaptability, providing fast, non-contact, and full-field non-destructive evaluation. Automating thermographic evaluation can increase assessment speed and repeatability without sacrificing inspection accuracy. By using a robot arm to manipulate the thermographic setup, it becomes possible to inspect large components and refine scans on suspicious zones, even in parts with complex geometries. In this study, the performance of a new thermographic inspection platform is compared with a conventional setup to showcase the potential improvements. A plastic curved-shaped sample with artificial flat bottom hole defects is used as a benchmark for the comparison. The advantages and disadvantages of robotizing the infrared non-destructive setup are analyzed, and the impact of the data workflow and future research activities are also discussed