132571 research outputs found
Sort by
A nonlinear repair technique for the MPFA-D scheme in single-phase flow problems and heterogeneous and anisotropic media
No full textA novel Flux Limited Splitting (FLS) non-linear Finite Volume (FV) method for families of linear Control Volume Distributed Multi Point Flux Approximation (CVD-MPFA) schemes is presented. The new formulation imposes a local discrete maximum principal (LDMP) which ensures that the discrete solution is free of spurious oscillations. The FLS scheme can be seen as a natural extension of the M-Matrix Flux Splitting method that splits the MPFA flux components in terms of the Two-Point Flux Approximation (TPFA) flux and Cross Diffusion Terms (CDT), with the addition of a dynamically computed relaxation parameter to the CDT that identifies and locally corrects the regions where the LDMP is violated. Moreover, the whole non-linear procedure was devised as a series of simple straightforward matrix operations. The methodology is presented considering the Multi-Point Flux Approximation with a Diamond (MPFA-D) in what we call the FLS + MPFA-D formulation which is tested using a series of challenging benchmark problems. For all test cases, the FLS repair technique imposes the LDMP and eliminates the spurious oscillations induced by the original MPFA-D method.Numerical Analysi
Tuning Nanopores in Tubular Ceramic Nanofiltration Membranes with Atmospheric-Pressure Atomic Layer Deposition: Prospects for Pressure-Based In-Line Monitoring of Pore Narrowing
No full textAtomic layer deposition (ALD) is known for its unparalleled control over layer thickness and 3D conformality and could be the future technique of choice to tailor the pore size of ceramic nanofiltration membranes. However, a major challenge in tuning and functionalizing a multichannel ceramic membrane is posed by its large internal pore volume, which needs to be evacuated during ALD cycling. This may require significant energy and processing time. This study presents a new reactor design, operating at atmospheric pressure, that is able to deposit thin layers in the pores of ceramic membranes. In this design, the reactor wall is formed by the industrial tubular ceramic membrane itself, and carrier gas flows are employed to transport the precursor and co-reactant vapors to the reactive surface groups present on the membrane surface. The layer growth for atmospheric-pressure ALD in this case proceeds similarly to that for state-of-the-art vacuum-based ALD. Moreover, for membrane preparation, this new reactor design has three advantages: (i) monolayers are deposited only at the outer pore mouths rather than in the entire bulk of the porous membrane substrate, resulting in reduced flow resistances for liquid permeation; (ii) an in-line gas permeation method was developed to follow the layer growth in the pores during the deposition process, allowing more precise control over the finished membrane; and (iii) expensive vacuum components and cleanroom environment are eliminated. This opens up a new avenue for ceramic membrane development with nano-scale precision using ALD at atmospheric pressure.Sanitary EngineeringChemE/Product and Process Engineerin
From statistical relational to neurosymbolic artificial intelligence: A survey
No full textThis survey explores the integration of learning and reasoning in two different fields of artificial intelligence: neurosymbolic and statistical relational artificial intelligence. Neurosymbolic artificial intelligence (NeSy) studies the integration of symbolic reasoning and neural networks, while statistical relational artificial intelligence (StarAI) focuses on integrating logic with probabilistic graphical models. This survey identifies seven shared dimensions between these two subfields of AI. These dimensions can be used to characterize different NeSy and StarAI systems. They are concerned with (1) the approach to logical inference, whether model or proof-based; (2) the syntax of the used logical theories; (3) the logical semantics of the systems and their extensions to facilitate learning; (4) the scope of learning, encompassing either parameter or structure learning; (5) the presence of symbolic and subsymbolic representations; (6) the degree to which systems capture the original logic, probabilistic, and neural paradigms; and (7) the classes of learning tasks the systems are applied to. By positioning various NeSy and StarAI systems along these dimensions and pointing out similarities and differences between them, this survey contributes fundamental concepts for understanding the integration of learning and reasoning.Algorithmic
Economic assessment of nature-based solutions to reduce flood risk and enhance co-benefits
No full textFlooding is expected to increase due to climate change, urbanisation, and land use change. To address this issue, Nature-Based Solutions (NBSs) are often adopted as innovative and sustainable flood risk management methods. Besides the flood risk reduction benefits, NBSs offer co-benefits for the environment and society. However, these co-benefits are rarely considered in flood risk management due to the inherent complexities of incorporating them into economic assessments. This research addresses this gap by developing a comprehensive methodology that integrates the monetary analysis of co-benefits with flood risk reduction in economic assessments. In doing so, it aspires to provide a more holistic view of the impact of NBS in flood risk management. The assessment employs a framework based on life-cycle cost-benefit analysis, offering a systematic and transparent assessment of both costs and benefits over time supported by key indicators like net present value and benefit cost ratio. The methodology has been applied to the Tamnava basin in Serbia, where significant flooding occurred in 2014 and 2020. The methodology offers valuable insights for practitioners, researchers, and planners seeking to assess the co-benefits of NBS and integrate them into economic assessments. The results show that when considering flood risk reduction alone, all considered measures have higher costs than the benefits derived from avoiding flood damage. However, when incorporating co-benefits, several NBS have a net positive economic impact, including afforestation/reforestation and retention ponds with cost-benefit ratios of 3.5 and 5.6 respectively. This suggests that incorporating co-benefits into economic assessments can significantly increase the overall economic efficiency and viability of NBS.BT/Environmental Biotechnolog
Surface modification of multilayer graphene electrodes by local printing of platinum nanoparticles using spark ablation for neural interfacing
No full textIn this paper, we present the surface modification of multilayer graphene electrodes with platinum (Pt) nanoparticles (NPs) using spark ablation. This method yields an individually selective local printing of NPs on an electrode surface at room temperature in a dry process. NP printing is performed as a post-process step to enhance the electrochemical characteristics of graphene electrodes. The NP-printed electrode shows significant improvements in impedance, charge storage capacity (CSC), and charge injection capacity (CIC), versus the equivalent electrodes without NPs. Specifically, electrodes with 40% NP surface density demonstrate 4.5 times lower impedance, 15 times higher CSC, and 4 times better CIC. Electrochemical stability, assessed via continuous cyclic voltammetry (CV) and voltage transient (VT) tests, indicated minimal deviations from the initial performance, while mechanical stability, assessed via ultrasonic vibration, is also improved after the NP printing. Importantly, NP surface densities up to 40% maintain the electrode optical transparency required for compatibility with optical imaging and optogenetics. These results demonstrate selective NP deposition and local modification of electrochemical properties in graphene electrodes for the first time, enabling the cohabitation of graphene electrodes with different electrochemical and optical characteristics on the same substrate for neural interfacing.Bio-ElectronicsEKL ProcessingElectronic Components, Technology and Material
Experimentally informed modeling of the early-age stress evolution in cementitious materials using exponential conversion from creep to relaxation
No full textThis study presents comprehensive numerical modeling methods for simulating early-age stress (EAS) relaxation in cementitious materials, based on the autogenous deformation (AD), elastic modulus, creep, and stress continuously tested by a mini temperature stress testing machine (Mini-TSTM) and a mini AD testing machine from a very early age (i.e., from a few hours to a week). Four methods for converting creep compliance to relaxation modulus were discussed in detail and used for the one-dimensional (1D) and three-dimensional (3D) simulation of stress evolution in the Mini-TSTM test. Furthermore, virtual creep and relaxation tests were conducted using an exponential algorithm with either the Kelvin or Maxwell chains to show their applicability in simulating the viscoelastic behavior of early-age cementitious materials. The results showed that the exponential algorithm with the Maxwell chain using an exponential conversion function from creep to relaxation obtains good prediction accuracy of EAS in 3D analysis. The numerical solutions of the Volterra integral of creep compliance can lead to a negative relaxation modulus, thus introducing stress calculation errors in both 1D and 3D analysis.Materials and Environmen
An adaptive route choice model for integrated fixed and flexible transit systems
No full textOver the past decade, there has been a surge of interest in the application of agent-based simulation models to evaluate flexible transit solutions characterized by different degrees of short-term flexibility in routing and scheduling. A central modelling decision in the development is how one chooses to represent the mode- and route-choices of travellers. The real-time adaptive behaviour of travellers is important to model in the presence of a flexible transit service, where the routing and scheduling of vehicles is highly dependent on supply-demand dynamics at a near real-time temporal resolution. We propose a utility-based transit route-choice model with representation of within-day adaptive travel behaviour and between-day learning where station-based fixed-transit, flexible-transit, and active-mode alternatives may be dynamically combined in a single path. To enable experimentation, this route-choice model is implemented within an agent-based dynamic public transit simulation framework. We first explore model properties in a choice between fixed- and flexible-transit modes for a toy network. The adaptive route choice framework is then applied to a case study based on a real-life branched transit service in Stockholm, Sweden. This case study illustrates level-of-service trade-offs, in terms of waiting times and in-vehicle times, between passenger groups and analyzes traveller mode choices within a mixed fixed- and flexible transit system. Results show that the proposed framework is capable of capturing dynamic route choices in mixed flexible and fixed transit systems and that the day-to-day learning model leads to stable fixed-flexible mode choices.Transport and Plannin
Investigation of non-ideal effects in compressible boundary layers of dense vapors through direct numerical simulations
No full textIn this work, we present an investigation about the sources of dissipation in adiabatic boundary layers of non-ideal compressible fluid flows. Direct numerical simulations (DNS) of transitional, zero-pressure gradient boundary layer flows are performed for two fluids characterized by different complexity of the fluid molecules, namely, “air” and siloxane MM. Different sets of thermodynamic free-stream boundary conditions are selected to evaluate the influence of the fluid state on both the frictional loss and the dissipation mechanisms. The thermophysical properties of siloxane MM are calculated with a state-of-the-art equation of state. Results show that the dissipation due to both time-mean strain field, irreversible heat transfer, and turbulent dissipation differs significantly depending on both the molecular complexity of the fluid and its thermodynamic state. The dissipation coefficient calculated from the DNS results is then compared against the one obtained using a reduced-order model (ROM), which solves the two-dimensional boundary layer flow equations for an arbitrary fluid [M. Pini and C. De Servi, “Entropy generation in laminar boundary layers of non-ideal fluid flows,” in 2nd International Seminar on Non-Ideal Compressible Fluid Dynamics for Propulsion and Power (Springer, 2020), pp. 104-117]. Results from both the DNS and the ROM show that low values of the overall dissipation are observed in the case of fluids made of simple molecules, e.g., air, and if the fluid is at a thermodynamic state in the proximity of that of the vapor-liquid critical point.Flight Performance and Propulsio
A System of Systems Aircraft Design Framework: Demonstration Using a Seaplane Transport Network in the Greek Islands
No full textThis paper presents a System of Systems Engineering approach to aircraft design. For this purpose, conventional design disciplines are coupled with Agent-Based Modeling and Simulation (ABMS) defining a unique optimization problem. The proposed methodology is applied to design seaplanes for an on-demand transportation system connecting the Greek islands. Within this network, diverse scenarios are analyzed by varying parameters of the model such as fleet size and travel demands at each seaport. The objective is to show the impact of including ABMS in the design workflow on the optimized seaplane design parameters. The optimum designs are evaluated on the basis of a number of classic performance metrics, to assess to what extent they can represent a competitive alternative to existent maritime means of transportation. The results reveal optimal fleet performance for seaplanes characterized by lower cruise speeds and passenger capacities, as compared to those derived from conventional methodologies and to existing designs.Aerospace Engineerin
Compilation of an open-source traffic and CO2 emissions dataset for commercial aviation
No full textThe study of the environmental transition of the aviation sector calls for prospective traffic scenarios. Detailed traffic and emissions inventories are often needed to refine the available analyses and to enable the simulation of regionalised scenarios. In the past studies, these are generally based on commercial, proprietary traffic data, making their dissemination problematic and reducing the reproducibility of the science produced. Open-source alternatives do exist, but with limited geographical coverage. This paper presents a method to aggregate different sources of flight information, in order to obtain an open-source air traffic dataset for 2019. Then, missing flight information is identified and completed using an airline route database built from Wikipedia parsing and related socio-economic data. After that, several reference datasets are used to evaluate the accuracy of the extended open-source dataset. Despite varying accuracy for different routes, major traffic flows are reasonably well estimated at the country and continental levels. Finally, the CO2 emissions are obtained using an existing aircraft performance surrogate model, and the accuracies are examined compared to the results from previous studies.Control & Simulatio