3,439 research outputs found
Coarse-grained Localization of In-body Energy-harvesting Nanonodes
Dispositivos a escala nanométrica con capacidades de comunicación inalámbrica en Ter- ahertz (THz) aspiran a implementarse para aplicaciones de detección dentro del torrente sanguíneo humano. Estos dispositivos detectan biomarcadores, permiten la administración dirigida de medicamentos y mejoran el diagnóstico precoz. La introducción de la localización nanométrica guiada por flujo utiliza la comunicación basada en THz para establecer la comunicación entre nanonodos y anclas. Se espera que este enfoque localice con precisión las regiones donde ocurren los eventos mediante el tiempo de circulación del nanodispositivo en el torrente sanguíneo. Esto facilita la identificación precisa de biomarcadores de enfermedades, virus y bacterias, lo que permite una intervención dirigida y la detección temprana de diversas condiciones de salud. Para evitar los desafíos encontrados en la evaluación y estandarización de la localización tradicional, este trabajo presenta un flujo de trabajo para la evaluación del rendimiento estandarizado de la localización nanométrica guiada por flujo. El flujo de trabajo se implementa en forma de un simulador de código abierto, teniendo en cuenta la movilidad del nanodispositivo, la comunicación THz en el cuerpo con anclas externas y las restricciones relacionadas con la energía. El simulador puede generar datos que se pueden utilizar para optimizar diferentes soluciones de localización y establecer puntos de referencia de rendimiento estandarizados. La evaluación se realiza mediante una exploración del espacio de diseño. Los resultados indican que el flujo de trabajo propuesto y el simulador se pueden utilizar para capturar el rendimiento de los enfoques de localización guiados por flujo de manera que permita una comparación objetiva con otros enfoques, sentando así las bases para la evaluación estandarizada de soluciones futuras.Els dispositius a nanoescala amb capacitats de comunicació sense fils en Terahertz (THz) aspiren a implementar-se en aplicacions basades en detecció i actuació dins del torrent sanguini humà. Aquests dispositius detecten biomarcadors, permeten el lliurament precís de fàrmacs i proporcionen un diagnòstic precoç. La introducció de la localització a nanoescala guiada per flux utilitza la comunicació basada en THz per establir la comunicació entre nanonodes i ancoratges. Aquest enfocament aspira a localitzar amb precisió les regions on es produeixen els esdeveniments utilitzant el temps de circulació del nanodispositiu a cada una de les regions. Això permet la identificació precisa de biomarcadors de malalties, virus i bacteris, donant lloc a una intervenció dirigida i a la detecció precoç de diverses condicions de salut. Per evitar els inconvenients que sorgeixen en les primeres etapes d’investigació, aquest treball presenta un flux de treball per a l’avaluació estandarditzada del rendiment de la localització a nanoescala guiada per flux. El flux de treball s’implementa en forma d’un simulador de codi obert, tenint en compte la mobilitat del nanodispositiu, la comunicació THz dins del cos amb els ancoratges situats a la superfície del cos i les limitacions relacionades amb l’energia. El simulador és capaç de generar dades que després de ser processades, ens permeten obtenir una avaluació estandaritzada del sistema . L’avaluació es va realitzar en forma d’exploració espacial de disseny. Els resultats indiquen que el flux de treball proposat i el simulador es poden utilitzar per capturar el rendiment de la solució implementada d’una manera que permet la comparació objectiva amb altres enfocaments, servint d’aquesta manera com a base per a l’avaluació estandarditzada de futures solucions.Nanoscale devices with Terahertz (THz) wireless communication capabilities are envisioned for sensing and actuation-based applications within human bloodstreams. These devices detect biomarkers, enable targeted drug delivery, and improve precision diagnos- tics. The introduction of flow-guided nanoscale localization utilizes THz-based communication to establish communication between nanonodes and anchors. This approach is envisaged to accurately locate regions where events occur by using the nanodevice’s circulation duration in the bloodstream. This enables precise identification of disease biomarkers, viruses, and bacteria, facilitating targeted intervention and early detection of health conditions. To avoid the pitfalls encountered in benchmarking and standardizing traditional indoor localization, this work presents a workflow for standardized performance evaluation of flow-guided nanoscale localization. The workflow is implemented in the form of an open source simulator, considering nanodevice mobility, in-body THz communication with on- body anchors, and energy-related constraints. The simulator is able to generate raw data that can be used to streamline different flow-guided localization solutions and establish standardized performance benchmarks. The evaluation is performed in the form of a design space exploration. The results indicate that the proposed workflow and the simulator can be utilized for capturing the performance of flow-guided localization approaches in a way that allows objective comparison with other approaches serving as the foundation for standardized evaluation of future solutions
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Adaptive vehicular networking with Deep Learning
Vehicular networks have been identified as a key enabler for future smart traffic applications aiming to improve on-road safety, increase road traffic efficiency, or provide advanced infotainment services to improve on-board comfort. However, the requirements of smart traffic applications also place demands on vehicular networks’ quality in terms of high data rates, low latency, and reliability, while simultaneously meeting the challenges of sustainability, green network development goals and energy efficiency. The advances in vehicular communication technologies combined with the peculiar characteristics of vehicular networks have brought challenges to traditional networking solutions designed around fixed parameters using complex mathematical optimisation. These challenges necessitate greater intelligence to be embedded in vehicular networks to realise adaptive network optimisation. As such, one promising solution is the use of Machine Learning (ML) algorithms to extract hidden patterns from collected data thus formulating adaptive network optimisation solutions with strong generalisation capabilities.
In this thesis, an overview of the underlying technologies, applications, and characteristics of vehicular networks is presented, followed by the motivation of using ML and a general introduction of ML background. Additionally, a literature review of ML applications in vehicular networks is also presented drawing on the state-of-the-art of ML technology adoption. Three key challenging research topics have been identified centred around network optimisation and ML deployment aspects.
The first research question and contribution focus on mobile Handover (HO) optimisation as vehicles pass between base stations; a Deep Reinforcement Learning (DRL) handover algorithm is proposed and evaluated against the currently deployed method. Simulation results suggest that the proposed algorithm can guarantee optimal HO decision in a realistic simulation setup.
The second contribution explores distributed radio resource management optimisation. Two versions of a Federated Learning (FL) enhanced DRL algorithm are proposed and evaluated against other state-of-the-art ML solutions. Simulation results suggest that the proposed solution outperformed other benchmarks in overall resource utilisation efficiency, especially in generalisation scenarios.
The third contribution looks at energy efficiency optimisation on the network side considering a backdrop of sustainability and green networking. A cell switching algorithm was developed based on a Graph Neural Network (GNN) model and the proposed energy efficiency scheme is able to achieve almost 95% of the metric normalised energy efficiency compared against the “ideal” optimal energy efficiency benchmark and is capable of being applied in many more general network configurations compared with the state-of-the-art ML benchmark
A review of solar hybrid photovoltaic-thermal (PV-T) collectors and systems
In this paper, we provide a comprehensive overview of the state-of-the-art in hybrid PV-T collectors and the wider systems within which they can be implemented, and assess the worldwide energy and carbon mitigation potential of these systems. We cover both experimental and computational studies, identify opportunities for performance enhancement, pathways for collector innovation, and implications of their wider deployment at the solar-generation system level. First, we classify and review the main types of PV-T collectors, including air-based, liquid-based, dual air–water, heat-pipe, building integrated and concentrated PV-T collectors. This is followed by a presentation of performance enhancement opportunities and pathways for collector innovation. Here, we address state-of-the-art design modifications, next-generation PV cell technologies, selective coatings, spectral splitting and nanofluids. Beyond this, we address wider PV-T systems and their applications, comprising a thorough review of solar combined heat and power (S–CHP), solar cooling, solar combined cooling, heat and power (S–CCHP), solar desalination, solar drying and solar for hydrogen production systems. This includes a specific review of potential performance and cost improvements and opportunities at the solar-generation system level in thermal energy storage, control and demand-side management. Subsequently, a set of the most promising PV-T systems is assessed to analyse their carbon mitigation potential and how this technology might fit within pathways for global decarbonization. It is estimated that the REmap baseline emission curve can be reduced by more than 16% in 2030 if the uptake of solar PV-T technologies can be promoted. Finally, the review turns to a critical examination of key challenges for the adoption of PV-T technology and recommendations
Tehokkaat ohjauskeinot jatkuvapeitteisen metsänkäsittelyn edistämiseksi runsasravinteisilla turvemailla
Raportissa tarkastellaan, onko luonnontieteellisiä perusteita ohjata metsänkäsittelyä runsasravinteisilla paksuturpeisilla turvemailla nykyistä enemmän kohti jatkuvapeitteistä kasvatusta – ja jos tällaisia perusteita on, miten sitä koskeva ohjaus olisi mahdollista ja tarkoituksenmukaista toteuttaa ja mitkä sen yhteiskunnalliset vaikutukset voisivat olla.
Olemassa olevan luonnontieteellisen tutkimustiedon perusteella näyttäisi olevan perusteita ohjata ja kannustaa metsänomistajia siirtymään runsasravinteisilla turvemailla jatkuvapeitteiseen metsänkäsittelyyn. Avohakkuita välttämällä ja metsänkäsittelyn intensiteettiä muutenkin vähentämällä pystytään pienentämään ravinne- ja kiintoainekuormitusta vesiin. Vesistökuormitusta koskevia tutkimustuloksia jatkuvapeitteisestä metsänkasvatuksesta on erityisesti rämeiltä, mutta samat riippuvuudet pätevät myös runsasravinteisemmilla turvemailla. Kasvihuonekaasupäästöistä tutkimustietoa on runsaasti puustoisilta soilta, ja päästöjen riippuvuus vedenpinnan tasosta sekä puuston vaikutus vedenpinnan tasoon tunnetaan. Avohakkuun jälkeen päästöt kasvavat voimakkaasti.
Siirtymällä runsasravinteisten turvemaiden päätehakkuuikäisissä kuusikoissa jatkuvapeitteiseen metsänkasvatukseen voidaan välttää avohakkuiden jälkeiset suuret kasvihuonekaasupäästöt. Tällaisen siirtymän avulla voitaisiin vähentää päästöjä ja kasvattaa Suomen vuosittaista hiilinielua jopa miljoonalla hiilidioksiditonnilla. Lukessa tehtyjen laskelmien (Lehtonen ym. 2023a) perusteella siirtymä jatkuvapeitteiseen kasvatukseen runsasravinteisilla turvemailla ei juuri vaikuttaisi puuston kasvuun koko maan tasolla.
Raportissa tuodaan esiin 14 keinoa, joilla jatkuvapeitteistä metsänkasvatusta voitaisiin edistää runsasravinteisilla turvemailla. Niistä kolmea tarkastellaan raportissa lähemmin. Muutamaa poikkeusta lukuun ottamatta keinot eivät ole toisiaan poissulkevia vaan pikemminkin toisiaan täydentäviä. Osa niistä olisi verraten helppoja toteuttaa, mutta uudentyyppiset taloudelliset tuet avohakkuiden aiheuttamien ympäristöhaittojen välttämiseen runsasravinteisilla turvemailla vaatisivat tukiehtojen tarkempaa määrittelyä, yhteiskehittelyä ja kokeiluhankkeita erilaisissa olosuhteissa.
Metsätalouden tukijärjestelmä (kestävän metsätalouden rahoituslaki, kemera) oli voimassa jokseenkin muuttumattomana yli 25 vuotta (1997‒2023). Puuntuotannon tukemisen järjestelmä on ollut voimassa vielä paljon pitempään, lähes sata vuotta. Aivan uudentyyppisten, markkinattomien ympäristöhyötyjen tuottamiseen tai ympäristöhaittojen vähentämiseen tähtäävien metsätalouden tukien suunnittelu ja toteutus vaatii paitsi avarakatseisuutta ja ennakkoluulottomuutta, myös lisää tutkimusnäyttöä eri metsänkasvatustapojen vaikutuksista runsasravinteisilla turvemailla. Euroopan unionin valtiontukisääntöjen näkökulmasta uudentyyppisten tukien soveltamiselle ei näyttäisi olevan estettä. Päinvastoin, Euroopan unionin uudet 1.1.2023 voimaan tulleet uudet valtiontukisäännöt avaavat kokonaan uusia mahdollisuuksia ottaa käyttöön ympäristöhyötyjen tuottamiseen kannustavia tukia metsätaloudessa. Näitä mahdollisuuksia olisi tarpeen ottaa käyttöön huomattavasti laajemmin kuin 1.1.2024 voimaan tulevassa metsätalouden uudessa tukijärjestelmässä (Metka) tehdään.
Uudentyyppiset taloudelliset tuet markkinattomien ympäristöhyötyjen tuottamiseen tai ympäristöhaittojen vähentämiseen myös lisäisivät metsänomistajien valinnanmahdollisuuksia suometsiensä käsittelyssä ja käytössä. Kyselyiden perusteella metsänomistajat suhtautuvat tällaisiin tukiin myönteisesti, ja haastatteluiden perusteella myös valtaosa sidosryhmistä näkee tarvetta uudentyyppisille ohjauskeinoille turvemaametsissä
Exoteric effects at nanoscopic interfaces - Uncommon negative compressibility of nanoporous materials and unexpected cavitation at liquid/liquid interfaces
This PhD thesis is devoted to the investigation of some peculiar effects happening at nanoscopic interfaces between immiscible liquids or liquids and solids via molecular dynamics simulations. The study of the properties of interfaces at a nanoscopic scale is driven by the promise of many interesting technological applications, including: a novel technology for developing both eco-friendly energy storage devices in the form of mechanical batteries, as well as energy dissipation systems and, in particular, shock absorbers for the automotive market; biomedical applications related to cavitation, such as High-Intensity Focused Ultrasound (HIFU) ablation of cancer tissues and localised drug delivery, and many more. The kinetics of phenomena taking places at these scales is typically determined by large free-energy barriers separating the initial and final states, and even intermediate metastable states, when they are present. Because of such barriers, the phenomena we are interested in are "rare events", i.e. the system attempts the crossing of the barrier(s) many times before finally succeeding when an energy fluctuation makes it possible. At the same time, the magnitude of the barrier is determined by the energetics and dynamics of atoms, which forces us to model the system by taking into account both the femtosecond atomistic timescale and the timescale of the relevant phenomena, typically exceeding the former by several orders of magnitude. These longer timescales are inaccessible to standard molecular dynamics, so, in order to tackle this issue, advanced MD techniques need to be employed.
The thesis is divided into two parts, corresponding to the main lines of research investigated, which are (I) the interfaces between water and complex nanoporous solids, and (II) planar solid-liquid and liquid-liquid interfaces. Anticipating some results, atomistic simulations helped uncovering the microscopic mechanism behind the (incredibly rare!) giant negative compressibility exhibited by the ZIF-8 metal organic framework (MOF) upon water intrusion. Molecular dynamics simulations also supported experimental results showing how it is possible to change the intermediate intrusion-extrusion performance of ZIF-8 by changing its grain morphology and arrangement, from a fine powder to compact monolith. Free-energy MD calculations allowed to explain the exceptional stability of surface nanobubbles in water, at undersaturated conditions, on a surprisingly wide variety of substrates, characterized by disparate hydrophobicities and gas affinities; and yet, how they catastrophically destabilize in organic solvents. Finally, through simulations, some light was shed upon the working mechanism behind the novelly discovered phenomenon of how the interface between two immiscible liquids can act as a nucleation site for cavitation
Responsive Building Envelope for Grid-Interactive Efficient Buildings – Thermal Performance and Control
The building sector accounts for 30% of total energy consumption worldwide. Responsive building envelopes (or RBEs) are one of the approaches to achieving net-zero energy and grid-interactive efficient buildings. However, research and development of RBEs are still in the early stages of technologies, simulation, control, and design. The control strategies in prior studies did not fully explore the potential of RBEs or they obtained good performance with high design and deployment costs. A low-cost strategy that does not require knowledge of complex systems is needed, while no studies have investigated online implementations of model-free control approaches for RBEs. To address these challenges, this dissertation describes a multidisciplinary study of the modeling, control, and design of RBEs, to understand mechanisms governing their dynamic properties and synthesis rules of multiple technologies through simulation analyses. Widely applicable mathematical models are developed that can be easily extended for multiple RBE types with validation. Computational frameworks (or co-simulation testbeds) that flexibly integrate multiple control methods and building simulation models are established with higher computation efficiency than that using commercial software during offline training. To overcome the limitations of the control strategies (e.g., rule-based control and MPC) in prior research, a novel easy-to-implement yet flexible ‘demand-based’ control strategy, and model-free online control strategies using deep reinforced learning are proposed for RBEs composed of active insulation systems (AISs). Both the physics-derived and model-free control strategies fully leverage the advantages of AISs and provide higher energy savings and thermal comfort improvement over traditional temperature-based control methods in prior research and demand-based control. The case studies of RBEs that integrate AISs and high thermal mass or self-adaptive/active modules (e.g., evaporative cooling techniques and dynamic glazing/shading) demonstrate the superior performance of AISs in regulating thermal energy transfer to offset AC demands during the synergy. Moreover, the controller design and training implications are elaborated. The applicability assessment of promising RBE configurations is presented along with design implications based on building energy analyses in multiple scenarios. The design and control implications represent an interactive and holistic way to operate RBEs allowing energy and thermal comfort performances to be tuned for maximum efficiency
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