5916 research outputs found
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Metaporous acoustic metamaterials with Helmholtz resonators for enhanced NVH performance in battery electric vehicles
No full textMetamaterials have gained an increasing attention as a way of absorbing noise to achieve improved acoustic performance on vehicles, and thanks to their novel functionalities compared to traditional designs, these structures are employed by many automotive companies as noise-reduction solutions for engineering applications. One of the key challenges for automotive original equipment manufacturers (OEMs) in the noise, vibration, and harshness (NVH) development process is absorption performance in the frequency range of 400 Hz-800 Hz. Although sound engineers use porous polyurethane in these frequency ranges, the absorption performance of these designs is limited to meet increasing customer expectations. Managing airborne noise in vehicles is particularly challenging in the low frequency spectrum, where Helmholtz resonators are widely used. The main purpose of this study is to develop a metaporous sound barrier incorporating a Helmholtz resonator, effective in the low to mid-frequency range of the spectrum. For this purpose, a frequency domain simulation was carried out to obtain the absorption coefficient, analyze frequency-dependent effects, and identify critical frequencies in vehicle acoustics. Furthermore, local resonance effects to prevent acoustic waves were investigated and design parameters of metastructure were analyzed using a multi-physics based simulation model. These results were validated experimentally using an acoustic impedance tube. The methodology is demonstrated in a battery electric vehicle (BEV) to improve airborne compressor noise during engine idling. The optimum design parameters were determined using the Taguchi design method. Finally, the performance of developed metaporous material was validated through vehicle-level tests, with results showing an improvement of 3 dB(A)
Comparative analysis on the phenomenological and artificial neural network modeling for flow curves of a beta titanium alloy
No full textThis study investigates the elevated temperature mechanical behavior of Ti-5V-5Mo-5Cr-4Al alloy through uniaxial tensile experiments conducted at temperatures ranging from room temperature to 550 degrees C and strain rates of 0.001, 0.01, and 0.1 s(-1). The results reveal that the dominant softening mechanism is dynamic recovery, whereas dynamic precipitation took place at the lowest rate of deformation and at temperatures ranging from 400 degrees C to 500 degrees C. To predict the mechanical behavior of this recent beta titanium alloy, artificial neural network (ANN) approach and modified Hensel-Spittel (m-HS) model were employed. In the prediction of flow curves using the m-HS model, a correlation coefficient (R) of 0.901 and an average absolute relative error (AARE) of 8.891 % were obtained. In contrast, the ANN approach yielded significantly better results, with an R value of 0.997 and an AARE of 2.3 %. The findings from this study provide routes for determining the hot workability of next-generation metastable beta titanium alloys.Ozyegin Universit
Integrated femtosecond laser system for precision surface patterning and high-speed cutting of intraocular lenses
No full textWe demonstrate the implementation of a zonal diffractive intraocular lens design based on VSY Biotechnology's recent patent [1], using a custom-developed femtosecond fiber laser system optimized for transparent material processing. Our system operates at 1030 nm with sub-500 fs pulses, employing two distinct scanning strategies: a high-precision 4-axis translation stage synchronized with spiral scanning for precise Fresnel zone patterning (1.1 μm depth modulation), and a galvo scanner with f-theta lens configuration for rapid haptic cutting achieving industrial-compatible processing speeds (<40 s/lens)
Track switching made easy in media-over-quic transport
No full textAs the Media-over-QUIC Transport (MOQT) continues to evolve, interest in its potential as a versatile media delivery protocol capable of scaling efficiently and operating at sub-second latencies is growing. In this paper, we propose an atomic operation for track switching between alternative tracks in media streaming, enhancing the current SUBSCRIBE/UNSUBSCRIBE mechanism of MOQT. Further, we present results from our implementation of the method that show significant reductions in excess traffic that would normally lead to unnecessary stalls during track switching
Toward self-sustainable airborne communication networks: Comprehensive modeling and analysis of energy consumption and harvesting
No full textAirborne networks build upon the use of unmanned aerial vehicles (UAVs) and high-altitude platform stations (HAPSs) for wireless access and backhauling and are expected to be instrumental in providing global coverage and ubiquitous connectivity. They can offer a range of benefits, including lower latency and higher data rate capacity per unit area, making them an attractive alternative or complementary solution to low-earth orbit satellites in future non-terrestrial networks. The practical deployment of airborne nodes is restricted by onboard energy limitations, motivating the use of energy harvesting techniques. In this paper, we present an in-depth examination of the power consumption of HAPSs and rotary-wing UAVs. We delve into consumption patterns across various flight phases, shedding light on the multifaceted impact of diverse system and operational parameters on overall energy utilization. We then present a thorough analysis of energy harvesting methods. First, we examine solar energy harvesting and demonstrate its dependence on factors such as operational altitude, geographical location, climate conditions, and daylight duration. Subsequently, we introduce laser power beaming as a more predictable and controllable energy source. Thereafter, we discuss the feasibility of self-sustainable airborne networks based on these energy harvesting techniques and typical energy consumption patterns. © 2005-2012 IEEE.Tamkeen under the Research Institute NYUA
A multitier approach for dynamic and partially observable multiagent path-finding
No full textThis paper introduces a novel Dynamic and Partially Observable Multiagent Path-Finding (DPO-MAPF) problem and presents a multitier solution approach accordingly. Unlike traditional MAPF problems with static obstacles, DPO-MAPF involves dynamically moving obstacles that are partially observable and exhibit unpredictable behavior. Our multitier solution approach combines centralized planning with decentralized execution. In the first tier, we apply state-of-the-art centralized and offline path planning techniques to navigate around static, known obstacles (e.g., walls, buildings, mountains). In the second tier, we propose a decentralized and online conflict resolution mechanism to handle the uncertainties introduced by partially observable and dynamically moving obstacles (e.g., humans, vehicles, animals, and so on). This resolution employs a metaheuristic-based revision process guided by a consensus protocol to ensure fair and efficient path allocation among agents. Extensive simulations validate the proposed framework, demonstrating its effectiveness in finding valid solutions while ensuring fairness and adaptability in dynamic and uncertain environments.Publisher versio
Evaluation of industry 5.0 technologies in automotive industry using integrated IVIF MCDM methodology
No full textAdvances in technological developments have been the triggers of industrial revolutions. Emerging digital technologies have initiated the industry 5.0 revolution, which holistically transforms the industries in the business world. Industry 5.0 has emerged differently from its previous versions, with its structure encompassing the dimensions of human centricity, sustainability, and resilience. The transformation process considers these dimensions and has affected all sectors, including the automotive industry. This situation has caused companies to face a strategic decision-making process regarding incorporating digital technologies into their operational processes. For this reason, this study focuses on evaluating and selecting I5.0 technologies in the automotive industry. The study consists of two main stages. First, it proposes a new model based on the opinions of experts and a literature review. Second, it presents an application based on an integrated multi-criteria decision-making (MCDM) methodology for the automotive industry in Turkey to verify the proposed model’s applicability, validity, and suitability. In this regard, the study utilizes the analytic hierarchy process (AHP) to compute the weights of the criteria of the proposed model. Following this, VIšeKriterijumska Optimizacija i Kompromisno Rešenje (VIKOR) is employed to select the most appropriate I5.0 technology among the alternatives based on the proposed model. However, real-life decision-making problems involve complexity, uncertainty, and subjective human perception. Therefore, in this study, classical AHP and VIKOR methods are extended to interval-valued intuitionistic fuzzy (IVIF) sets to eliminate these problems. The study presents valuable insights regarding the priority of the criteria to select I5.0 technologies in the automotive industry and identifies the most appropriate technology for the industry.Özyeğin Üniversites
Maximum causal entropy IRL in mean-field games and GNEP framework for forward RL
No full textThis paper explores the use of Maximum Causal Entropy Inverse Reinforcement Learning (IRL) within the context of discrete-time stationary Mean-Field Games (MFGs) characterized by finite state spaces and an infinite-horizon, discounted-reward setting. Although the resulting optimization problem is non-convex with respect to policies, we reformulate it as a convex optimization problem in terms of state-action occupation measures by leveraging the linear programming framework of Markov Decision Processes. Based on this convex reformulation, we introduce a gradient descent algorithm with a guaranteed convergence rate to efficiently compute the optimal solution. Moreover, we develop a new method that conceptualizes the MFG problem as a Generalized Nash Equilibrium Problem (GNEP), enabling effective computation of the mean-field equilibrium for forward reinforcement learning (RL) problems and marking an advancement in MFG solution techniques. We further illustrate the practical applicability of our GNEP approach by employing this algorithm to generate data for numerical MFG examples.TÜBİTAKPublisher versio
Effect of phase noise on the performance of coherent visible light communication systems
No full textVisible light communication (VLC) builds upon the dual use of illumination infrastructure for wireless access. The recent commercialization of laser diode (LD)–empowered white light luminaires gives the opportunity to build coherent VLC systems. Coherent VLC systems can leverage the high bandwidth of lasers and advanced digital signal processing techniques to significantly improve the data rates. For coherent reception, a local oscillator in the form of a monochromatic laser is used. In practice, lasers suffer from random fluctuations in phase due to spontaneous emission and carrier density fluctuations. In this paper, we analyze the effects of phase noise on the performance of a coherent VLC system in the presence of atmospheric turbulence as encountered in outdoor and vehicular applications. We assume that a phase locked loop (PLL) is used for phase recovery. Turbulence-induced fading phase is estimated through pilot symbols and provided as input to the PLL. The PLL uses this estimated channel phase to initialize its phase estimate at the beginning of each frame. Based on the statistical distribution of the residual phase, we derive an approximate closed-form expression for the pairwise error probability (PEP) which is then used to obtain a union bound on the error rate. Through comprehensive simulations, we validate the accuracy of the derived expression and quantify the impact of phase noise on the error rate performance
Designing a preschool outdoor classroom in early childhood education: A case from istanbul
No full textThis study aims to define the spatial requirements and establish a design strategy for preschool outdoor classrooms (POCs), emphasizing their educational significance and promoting broader implementation. Additionally, through POC arrangements, the article aims to enhance children's interaction with nature, diversify and support their experiences, and foster environmental awareness by increasing their engagement with the natural environment at an early age. Integrating design-based research with qualitative methods, the study was conducted in four phases: research, design, implementation, and evaluation. The research phase involved an extensive review of literature, international design guidelines, and outdoor education organizations to identify pedagogical foundations and essential design components. In the design phase, the required spatial elements and tools were defined, and a strategic framework was developed. A participatory approach was applied during the implementation phase to create a POC in Nisantepe, Istanbul, Türkiye, referred to as N-POC. The final phase evaluated the N-POC design based on established POC criteria. The study identified core spaces and tools essential for POC development and validated the proposed, context and content-based design strategy through the N-POC case, demonstrating its applicability and effectiveness