2,197 research outputs found

    Site selection and capacity determination of charging stations considering the uncertainty of users’ dynamic charging demands

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    Aiming at the problems of high investment and low efficiency in the planning and construction of electric vehicle (EV) charging stations in cities, an optimization model for site selection and capacity determination of charging stations considering the uncertainty of users’ dynamic charging demands is proposed. Firstly, based on the travel chain theory and the Origin-Destination (OD) matrix, the travel characteristics of EVs are studied, and the spatial and temporal distribution prediction model of EV charging load is established through the dynamic Dijkstra algorithm combined with the Monte Carlo method. Secondly, a site selection model for the charging station is established which takes the minimum annualized cost of the charging station operator and the annualized economic loss of the EV users as the goal. At the same time, the weighted Voronoi diagram and Adaptive Simulated Annealing Particle Swarm Optimization algorithm (ASPSO) are adopted to determine the optimal number/site selection and service scope of charging stations. Finally, an uncertain scenario set is introduced into the capacity determination model to describe the uncertainty of the users’ dynamic charging demands, and the robust optimization theory is utilized to solve the capacity of the charging station. A case study is carried out for the EV charging station planning problem in some urban areas of a northern city, and the validity of the model is verified

    Dynamic data structures for k-nearest neighbor queries

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    Our aim is to develop dynamic data structures that support k-nearest neighbors (k-NN) queries for a set of n point sites in the plane in O(f(n)+k) time, where f(n) is some polylogarithmic function of n. The key component is a general query algorithm that allows us to find the k-NN spread over t substructures simultaneously, thus reducing an O(tk) term in the query time to O(k). Combining this technique with the logarithmic method allows us to turn any static k-NN data structure into a data structure supporting both efficient insertions and queries. For the fully dynamic case, this technique allows us to recover the deterministic, worst-case, O(log2⁡n/log⁡log⁡n+k) query time for the Euclidean distance claimed before, while preserving the polylogarithmic update times. We adapt this data structure to also support fully dynamic geodesic k-NN queries among a set of sites in a simple polygon. For this purpose, we design a shallow cutting based, deletion-only k-NN data structure. More generally, we obtain a dynamic planar k-NN data structure for any type of distance functions for which we can build vertical shallow cuttings. We apply all of our methods in the plane for the Euclidean distance, the geodesic distance, and general, constant-complexity, algebraic distance functions

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Biomimicry green façade : integrating nature into building façades for enhanced building envelope efficiency

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    Incorporating natural elements into the design of building façades, such as green façades, has emerged as a promising strategy for achieving sustainable and energy-efficient buildings. Biomimicry has become a key inspiration for the development of innovative green façade systems. However, there is still progress to be made in maximising their aesthetic and structural performance, and the application of advanced and generative design methods is imperative for optimising green façade architecture. This research aims to present a generative design-based prototype of a biomimicry green façade substrate with photosynthetic microorganisms to enhance building façade efficiency. The concept of green façades offers numerous advantages, as it can be adapted to a wide range of building structures and implemented in various climates. To achieve this, Rhino and Grasshopper were utilized to design the generative and parametric substrate, optimizing the architectural form using a genetic algorithm. Consequently, a bio-façade prototype was developed, determining the optimal number and shape of coral envelopes to maintain cyanobacteria within a generative and parametric façade. Furthermore, the photosynthetic microorganism façade acted as an adaptive façade, effectively improving visual and thermal comfort, daylighting, and Indoor Environmental Quality performance

    Fluid dynamics and mass transfer in porous media: Modelling fluid flow and filtration inside open-cell foams

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Towards addressing training data scarcity challenge in emerging radio access networks: a survey and framework

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    The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch automation, a myriad of AI-based solutions are being proposed in literature to leverage AI for modeling and optimizing network behavior to achieve the zero-touch automation goal. However, to work reliably, AI based automation, requires a deluge of training data. Consequently, the success of the proposed AI solutions is limited by a fundamental challenge faced by cellular network research community: scarcity of the training data. In this paper, we present an extensive review of classic and emerging techniques to address this challenge. We first identify the common data types in RAN and their known use-cases. We then present a taxonomized survey of techniques used in literature to address training data scarcity for various data types. This is followed by a framework to address the training data scarcity. The proposed framework builds on available information and combination of techniques including interpolation, domain-knowledge based, generative adversarial neural networks, transfer learning, autoencoders, fewshot learning, simulators and testbeds. Potential new techniques to enrich scarce data in cellular networks are also proposed, such as by matrix completion theory, and domain knowledge-based techniques leveraging different types of network geometries and network parameters. In addition, an overview of state-of-the art simulators and testbeds is also presented to make readers aware of current and emerging platforms to access real data in order to overcome the data scarcity challenge. The extensive survey of training data scarcity addressing techniques combined with proposed framework to select a suitable technique for given type of data, can assist researchers and network operators in choosing the appropriate methods to overcome the data scarcity challenge in leveraging AI to radio access network automation

    Proceedings of the 2nd 4TU/14UAS Research Day on Digitalization of the Built Environment

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    On the role of energy infrastructure in the energy transition. Case study of an energy independent and CO2 neutral energy system for Switzerland

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    The transition towards renewable energy is leading to an important strain on the energy grids. The question of designing and deploying renewable energy technologies in symbiosis with existing grids and infrastructure is arising. While current energy system models mainly focus on the energy transformation system or only investigate the effect on one energy vector grid, we present a methodology to characterize different energy vector grids and storage, integrated into the multi-energy and multi-sector modeling framework EnergyScope. The characterization of energy grids is achieved through a traditional energy technology and grid modeling approach, integrating economic and technical parameters. The methodology has been applied to the case study of a country with a high existing transmission infrastructure density, e.g., Switzerland, switching from a fossil fuel-based system to a high share of renewable energy deployment. The results show that the economic optimum with high shares of renewable energy requires the electric distribution grid reinforcement with 2.439 GW (+61%) Low Voltage (LV) and 4.626 GW (+82%) Medium Voltage (MV), with no reinforcement required at transmission level [High Voltage (HV) and Extra High Voltage (EHV)]. The reinforcement is due to high shares of LV-Photovoltaic (PV) (15.4 GW) and MV-wind (20 GW) deployment. Without reinforcement, additional biomass is required for methane production, which is stored in 4.8–5.95 TWh methane storage tanks to compensate for seasonal intermittency using the existing gas infrastructure. In contrast, hydro storage capacity is used at a maximum of 8.9 TWh. Furthermore, the choice of less efficient technologies to avoid reinforcement results in a 8.5%–9.3% cost penalty compared to the cost of the reinforced system. This study considers a geographically averaged and aggregated model, assuming all production and consumption are made in one single spot, not considering the role of future decentralization of the energy system, leading to a possible overestimation of grid reinforcement needs

    Functional space-time properties of team synergies in high-performance football

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    This thesis aimed to investigate the performance of high-level teams in football, through the analysis of the interactions of their players in the context of the game, as these interactions result in functional effects that could not otherwise be achieved (synergies). From a spatial point of view, we argue that the understanding of collective “payoffs” emerging from players’ interactions and their behavioural patterns, can be accomplished through ”Delaunay triangulations” and consequent ”Voronoi diagrams”. Analysing the positional data (22 players and the ball) in 20 games of the French premier league, in this thesis we essentially sought to focus on territorial dominance as a variable that potentially captures the spatial affordances perceived by players. Whether from a collective global point of view or from a perspective of the local interactions that arise in the game landscape. Supported by the ecological dynamics and the synergism hypothesis, in this thesis we begin by demonstrating the existing connection between the territorial dominance of a team and the offensive effectiveness, as well as the absence of temporal overlap between the ball possession status and territorial dominance. Similarly, we also demonstrated that the space dominance of each player, which contributes to the territorial dominance of the team as a whole, is constrained by the team’s formation and the role assumed by each player in this collective framework. In order to understand the dynamics of interactions between players and the functional effects that come from it, we then focus on two tasks that are related to collective performance: the pass and the shot. Reflecting on the need to find methods that capture how the distribution of players on the pitch influences the functional degrees of freedom of a team as a whole and the passing opportunities that emerge from it. And, at the level of finishing situations, how the dominance of space can be included in the quantification of the value that each player assigns to occupy a certain place in the game landscape, and which is at the basis of their decision-making (shoot or pass the ball to another teammate possibly better ”positioned”). In sum, through the initial conceptual framework and the applied studies, we argue that the analysis of team performance should focus on the functional synergies that result from interactions between players. In this way, we demonstrate, through some examples, how the methods and conclusions taken from this thesis can be applied in practice by football coaches.Esta tese teve como objetivo investigar a performance de equipas de alto nível no futebol, através da análise das interações dos seus jogadores no contexto do jogo pois daí resultam efeitos funcionais que apenas são atingidos através dessas mesmas interações (sinergias). De um ponto de vista espacial, defendemos que o estudo glocal das interações entre os jogadores para a compreensão do rendimento coletivo, pode ser realizado através de “triangulações de Delaunay” e consequentes “diagramas de Voronoi”. Analisando os dados posicionais dos 22 jogadores e da bola, em 20 jogos da primeira liga francesa, nesta tese procurámos essencialmente nos focar sobre o domínio territorial enquanto variável que capta potencialmente as affordances espaciais percebidas pelos jogadores. Seja de um ponto de vista global coletivo, seja numa perspetiva das interações locais que surgem na paisagem de jogo. Suportados pela dinâmica ecológica e pela hipótese do sinergismo, nesta tese começamos por demonstrar a ligação existente entre o domínio territorial das equipas e a sua efetividade ofensiva, bem como a inexistência de uma sobreposição temporal entre a posse de bola e esse domínio. De igual forma, também demonstrámos que o domínio do espaço de cada jogador, que contribui para o domínio territorial da equipa no seu todo, é constrangido pelo sistema de jogo das equipas e pelo papel assumido por cada jogador neste referencial coletivo. No sentido de compreender a dinâmica das interações entre os jogadores e os efeitos funcionais que daí advêm, focamo-nos seguidamente em duas tarefas que estão relacionadas com a performance coletiva: o passe e o remate. Refletindo sobre a necessidade de encontrar métodos que captem de que forma a distribuição dos jogadores em campo influencia os graus de liberdade funcionais de uma equipa no seu todo e as oportunidades de passe que daí emergem. E, ao nível das situações de finalização, de que forma o domínio do espaço poderá ser incluído na quantificação do valor que cada jogador atribui a ocupar um determinador espaço na paisagem de jogo e que está na base da sua tomada de decisão (rematar ou passar a bola para outro colega eventualmente melhor “posicionado”). Em suma, através do enquadramento conceptual inicial e dos estudos aplicados, defendemos que o estudo da performance das equipas deverá se centrar nas sinergias funcionais que resultam das interações entre os jogadores. Desta forma, demonstramos, através de alguns exemplos, como é que os métodos e ilações retirados desta tese poderão ser aplicados na prática pelos treinadores de futebol
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