11,952 research outputs found

    Key technologies for safe and autonomous drones

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    Drones/UAVs are able to perform air operations that are very difficult to be performed by manned aircrafts. In addition, drones' usage brings significant economic savings and environmental benefits, while reducing risks to human life. In this paper, we present key technologies that enable development of drone systems. The technologies are identified based on the usages of drones (driven by COMP4DRONES project use cases). These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. Also, we present the contributions of the COMP4DRONES project to improve existing technologies. These contributions aim to ease drones’ customization, and enable their safe operation.This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 826610. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Austria, Belgium, Czech Republic, France, Italy, Latvia, Netherlands. The total project budget is 28,590,748.75 EUR (excluding ESIF partners), while the requested grant is 7,983,731.61 EUR to ECSEL JU, and 8,874,523.84 EUR of National and ESIF Funding. The project has been started on 1st October 2019

    Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions

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    In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request

    neuroAIx-Framework: design of future neuroscience simulation systems exhibiting execution of the cortical microcircuit model 20× faster than biological real-time

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    IntroductionResearch in the field of computational neuroscience relies on highly capable simulation platforms. With real-time capabilities surpassed for established models like the cortical microcircuit, it is time to conceive next-generation systems: neuroscience simulators providing significant acceleration, even for larger networks with natural density, biologically plausible multi-compartment models and the modeling of long-term and structural plasticity.MethodsStressing the need for agility to adapt to new concepts or findings in the domain of neuroscience, we have developed the neuroAIx-Framework consisting of an empirical modeling tool, a virtual prototype, and a cluster of FPGA boards. This framework is designed to support and accelerate the continuous development of such platforms driven by new insights in neuroscience.ResultsBased on design space explorations using this framework, we devised and realized an FPGA cluster consisting of 35 NetFPGA SUME boards.DiscussionThis system functions as an evaluation platform for our framework. At the same time, it resulted in a fully deterministic neuroscience simulation system surpassing the state of the art in both performance and energy efficiency. It is capable of simulating the microcircuit with 20× acceleration compared to biological real-time and achieves an energy efficiency of 48nJ per synaptic event

    Interview with Wolfgang Knauss

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    An oral history in four sessions (September 2019–January 2020) with Wolfgang Knauss, von Kármán Professor of Aeronautics and Applied Mechanics, Emeritus. Born in Germany in 1933, he speaks about his early life and experiences under the Nazi regime, his teenage years in Siegen and Heidelberg during the Allied occupation, and his move to Pasadena, California, in 1954 under the sponsorship of a local minister and his family. He enrolled in Caltech as an undergraduate in 1957, commencing a more than half-century affiliation with the Institute and GALCIT (today the Graduate Aerospace Laboratories of Caltech). He recalls the roots of his interest in aeronautics, his PhD solid mechanics studies with his advisor, M. Williams, and the GALCIT environment in the late 1950s and 1960s at the dawn of the Space Age, including the impact of Sputnik and classes with NASA astronauts. He discusses his experimental and theoretical work on materials deformation, dynamic fracture, and crack propagation, including his solid-propellant fuels research for NASA and the US Army, wide-ranging programs with the US Navy, and his pioneering micromechanics investigations and work on the time-dependent fracture of polymers in the 1990s. He offers his perspective on GALCIT’s academic culture, its solid mechanics and fluid mechanics programs, and its evolving administrative directions over the course of five decades, as well as its impact and reputation both within and beyond Caltech. He describes his work with Caltech’s undergraduate admissions committee and his scientific collaborations with numerous graduate students and postdocs and shares his recollections of GALCIT and other Caltech colleagues, including C. Babcock, D. Coles, R.P. Feynman, Y.C. Fung, G. Neugebauer, G. Housner, D. Hudson, H. Liepmann, A. Klein, G. Ravichandran, A. Rosakis, A. Roshko, and E. Sechler. Six appendices contributed by Dr. Knauss, offering further insight into his life and career, also form part of this oral history and are cross-referenced in the main text

    Review of Methodologies to Assess Bridge Safety During and After Floods

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    This report summarizes a review of technologies used to monitor bridge scour with an emphasis on techniques appropriate for testing during and immediately after design flood conditions. The goal of this study is to identify potential technologies and strategies for Illinois Department of Transportation that may be used to enhance the reliability of bridge safety monitoring during floods from local to state levels. The research team conducted a literature review of technologies that have been explored by state departments of transportation (DOTs) and national agencies as well as state-of-the-art technologies that have not been extensively employed by DOTs. This review included informational interviews with representatives from DOTs and relevant industry organizations. Recommendations include considering (1) acquisition of tethered kneeboard or surf ski-mounted single-beam sonars for rapid deployment by local agencies, (2) acquisition of remote-controlled vessels mounted with single-beam and side-scan sonars for statewide deployment, (3) development of large-scale particle image velocimetry systems using remote-controlled drones for stream velocity and direction measurement during floods, (4) physical modeling to develop Illinois-specific hydrodynamic loading coefficients for Illinois bridges during flood conditions, and (5) development of holistic risk-based bridge assessment tools that incorporate structural, geotechnical, hydraulic, and scour measurements to provide rapid feedback for bridge closure decisions.IDOT-R27-SP50Ope

    Innovative Hybrid Approaches for Vehicle Routing Problems

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    This thesis deals with the efficient resolution of Vehicle Routing Problems (VRPs). The first chapter faces the archetype of all VRPs: the Capacitated Vehicle Routing Problem (CVRP). Despite having being introduced more than 60 years ago, it still remains an extremely challenging problem. In this chapter I design a Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP, shortened to FILO. The simplicity of the CVRP definition allowed me to experiment with advanced local search acceleration and pruning techniques that have eventually became the core optimization engine of FILO. FILO experimentally shown to be extremely scalable and able to solve very large scale instances of the CVRP in a fraction of the computing time compared to existing state-of-the-art methods, still obtaining competitive solutions in terms of their quality. The second chapter deals with an extension of the CVRP called the Extended Single Truck and Trailer Vehicle Routing Problem, or simply XSTTRP. The XSTTRP models a broad class of VRPs in which a single vehicle, composed of a truck and a detachable trailer, has to serve a set of customers with accessibility constraints making some of them not reachable by using the entire vehicle. This problem moves towards VRPs including more realistic constraints and it models scenarios such as parcel deliveries in crowded city centers or rural areas, where maneuvering a large vehicle is forbidden or dangerous. The XSTTRP generalizes several well known VRPs such as the Multiple Depot VRP and the Location Routing Problem. For its solution I developed an hybrid metaheuristic which combines a fast heuristic optimization with a polishing phase based on the resolution of a limited set partitioning problem. Finally, the thesis includes a final chapter aimed at guiding the computational evaluation of new approaches to VRPs proposed by the machine learning community

    AIUCD 2022 - Proceedings

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    L’undicesima edizione del Convegno Nazionale dell’AIUCD-Associazione di Informatica Umanistica ha per titolo Culture digitali. Intersezioni: filosofia, arti, media. Nel titolo ù presente, in maniera esplicita, la richiesta di una riflessione, metodologica e teorica, sull’interrelazione tra tecnologie digitali, scienze dell’informazione, discipline filosofiche, mondo delle arti e cultural studies

    Elasto-plastic deformations within a material point framework on modern GPU architectures

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    Plastic strain localization is an important process on Earth. It strongly influ- ences the mechanical behaviour of natural processes, such as fault mechanics, earthquakes or orogeny. At a smaller scale, a landslide is a fantastic example of elasto-plastic deformations. Such behaviour spans from pre-failure mech- anisms to post-failure propagation of the unstable material. To fully resolve the landslide mechanics, the selected numerical methods should be able to efficiently address a wide range of deformation magnitudes. Accurate and performant numerical modelling requires important compu- tational resources. Mesh-free numerical methods such as the material point method (MPM) or the smoothed-particle hydrodynamics (SPH) are particu- larly computationally expensive, when compared with mesh-based methods, such as the finite element method (FEM) or the finite difference method (FDM). Still, mesh-free methods are particularly well-suited to numerical problems involving large elasto-plastic deformations. But, the computational efficiency of these methods should be first improved in order to tackle complex three-dimensional problems, i.e., landslides. As such, this research work attempts to alleviate the computational cost of the material point method by using the most recent graphics processing unit (GPU) architectures available. GPUs are many-core processors originally designed to refresh screen pixels (e.g., for computer games) independently. This allows GPUs to delivers a massive parallelism when compared to central processing units (CPUs). To do so, this research work first investigates code prototyping in a high- level language, e.g., MATLAB. This allows to implement vectorized algorithms and benchmark numerical results of two-dimensional analysis with analytical solutions and/or experimental results in an affordable amount of time. After- wards, low-level language such as CUDA C is used to efficiently implement a GPU-based solver, i.e., ep2-3De v1.0, can resolve three-dimensional prob- lems in a decent amount of time. This part takes advantages of the massive parallelism of modern GPU architectures. In addition, a first attempt of GPU parallel computing, i.e., multi-GPU codes, is performed to increase even more the performance and to address the on-chip memory limitation. Finally, this GPU-based solver is used to investigate three-dimensional granular collapses and is compared with experimental evidences obtained in the laboratory. This research work demonstrates that the material point method is well suited to resolve small to large elasto-plastic deformations. Moreover, the computational efficiency of the method can be dramatically increased using modern GPU architectures. These allow fast, performant and accurate three- dimensional modelling of landslides, provided that the on-chip memory limi- tation is alleviated with an appropriate parallel strategy
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