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نتیجه جستجو - Tunnel

تعداد مقالات یافته شده: 48
ردیف عنوان نوع
1 Tunneling Current Through a Double Quantum Dots System
جریان تونل زنی از طریق سیستم دو نقطه کوانتومی-2022
Electrostatically confined quantum dots in semiconductors hold the promise to achieve high scalability and reliability levels for practical implementation of solid-state qubits where the electrochemical potentials of each quantum dot can be independently controlled by the gate voltages.In this paper, the current and charge stability diagram of two-well potentials arising from electrostatically defined double quantum dot (DQD) are analytically realized. We propose to apply the Generalized Hubbard model to find the Hamiltonian of the system. The proposed analysis takes the tunnel coupling between the dots, Coulomb interaction, and Zeeman energy arising from an external magnetic field into account. Using quantum master equations to predict the probability of the final states in a DQD system, we study the tunneling current through two quantum dots coupled in series with two conducting leads, and therefore, the charge stability diagram is theoretically investigated. The impact of the tunnel coupling and Zeeman energy on the charge stability diagram is deeply discussed. The validity of the presented analysis is confirmed by experimental data as well as the classical capacitance model.
INDEX TERMS: Double quantum dot | hubbard model | zeeman energy | charge stability diagram | master equation.
مقاله انگلیسی
2 A Multiscale Simulation Approach for Germanium-Hole-Based Quantum Processor
یک رویکرد شبیه سازی چند مقیاسی برای پردازنده کوانتومی مبتنی بر حفره ژرمانیوم-2022
A multiscale simulation method is developed to model a quantum dot (QD) array of germanium (Ge) holes for quantum computing. Guided by three-dimensional numerical quantum device simulations of QD structures, an analytical model of the tunnel coupling between the neighboring hole QDs is obtained. Two-qubit entangling quantum gate operations and quantum circuit characteristics of the QD array processor are then modeled. Device analysis of two-qubit Ge hole quantum gates demonstrates faster gate speed, smaller process variability, and less stringent requirement of feature size, compared to its silicon counterpart. The multiscale simulation method allows assessment of the quantum processor circuit performance from a bottom-up, physics-informed perspective. Application of the simulation method to the Ge QD array processor indicates its promising potential for preparing high-fidelity ansatz states in quantum chemistry simulations.
keywords: Quantum computing | Germanium | Hole | Quantum dot | Quantum gate | Multiscale simulation
مقاله انگلیسی
3 Effect of CNT additives on the electrical properties of derived nanocomposites (experimentally and numerical investigation)
تأثیر افزودنی‌های CNT بر خواص الکتریکی نانوکامپوزیت‌های مشتق‌شده (بررسی تجربی و عددی)-2021
In this work, two simulations models have been developed to study the electrical percolation and the electrical conductivity of epoxy-based nanocomposite containing Multi-walled Carbon Nanotubes. The models are based on resistor-model and finite element analysis. The former was evaluated using MATLAB code and the finite element analysis using DIGIMAT software. The maximum tunneling distance and its influence on the percolation probability and final electrical conductivity were studied. Electrical measurements on the samples were conducted for numerical validation. The experimental data showed a percolation achievement around 2 wt%, which was confirmed in the numerical simulations. This study provides evidence of the effectiveness of the resistor model and finite element method approach to predict the electrical conductivity of nanocomposites.
Keywords: Polymer-matrix composites (PMCs) | Nanocomposites | Carbon nanotube | Electrical properties | Computational modelling
مقاله انگلیسی
4 Refraction seismic complementing electrical method in subsurface characterization for tunneling in soft pyroclastic, (a case study)
روش الکتریکی تکمیلی لرزه‌ای شکست در شناسایی زیرسطحی برای تونل‌زنی در آذرآواری نرم (مطالعه موردی)-2021
The paper highlights the potential drawback of mapping a single geophysical property for subsurface characterization in potential engineering sites. As an exemplary case study, we present the geophysical survey conducted along the surface projection of a tunnel in the quaternary volcanic terrain of the Main Ethiopia Rift. Initially, geoelectrical mapping involving 12 Vertical Electrical Sounding (VES) and a short Electrical Resistivity Imaging (ERI) line, was carried out. The 1D geoelectric model indicates that the formation resistivity at tunnel zone varies from 50 to 500 Ω∙m. The corresponding value on 2D model, (>350 Ω∙m), is also compatible. Based on limited available geological information, the geoelectric horizon was attributed to weathered and variably saturated ignimbrite. Following unexpected encounter during excavation, refraction seismic and core drilling were carried out for additional insights. Tomographic analysis of the seismic arrival times revealed that below a depth of 45 m, (tunnel zone), the velocity substratum is marked by a range, (1200–1800 m/s). Such low velocity range is typical of unconsolidated materials and, thus, cannot rationalize the geoelectrical attribution (ignimbrite). In a joint interpretation, the likely formation that may justify the observed range of the electrical resistivity and low P-wave velocity appears to be unwelded pyroclastic deposit (volcanic ash). Eventually, core samples from the tunnel zone confirmed the presence of thick ash flow. However, the unexpected ground conditions encountered at the early phase, due to insufficient information derived from a single geophysical parameter, caused extra cost and considerable delay.
Keywords: Integrated approach | Refraction seismic | DC resistivity | Subsurface characterization | Main Ethiopian Rift (MER)
مقاله انگلیسی
5 Comprehensive review on electrical noise analysis of TFET structures
بررسی جامع تحلیل نویز الکتریکی سازه های TFET-2021
Tunnel Filed Effect Transistors (TFETs) have appeared as an alternative for conventional CMOS due to their advantages like very low leakage current and steep sub-threshold slope. In semiconductor devices, noise is considered an undesired signal that can deteriorate the desired signal. In TFET structures different noise sources affect the performance at different frequency ranges. This paper presents a comprehensive review of impact of electrical noise on the performance of various TFET structures. The impact of both low-frequency noise sources and high-frequency sources have been discussed thoroughly. The study of different types of electrical noises occur in simple TFET device and different structures of TFET is presented.
Keywords: Tunneling | Flicker noise | Shot noise | Thermal noise | Random telegraph noise
مقاله انگلیسی
6 Derivation and validation of wind tunnel free-flight similarity law for store separation from aircraft
اشتقاق و اعتبار قانون تشابه پرواز آزاد تونل باد برای جداسازی فروشگاه از هواپیما-2020
This paper describes a design method for a similarity law for free-flight tests of aircraft load separation. The effect of the initial separation velocity on the motion similarity is considered. For the first time, the initial separation velocity is introduced into the equation of motion to identify similar trajectories. Finally, the model mass parameter characteristics and separation velocity equation are solved to determine similarity laws for wind tunnel tests, greatly improving the accuracy and applicability of test results from wind tunnels. The proposed derivation overcomes the problems faced by the traditional light model method and the traditional heavy model method, namely that they are limited in terms of ejection separation and cannot be realized in wind tunnel tests. The typical separation state under wind load scenarios is simulated using computational fluid dynamics (CFD). Separation data from real aircraft and previous test methods are compared with the simulation data obtained by the new similarity law design method. The improvement of the new similarity law in terms of trajectory simulation is verified through a comprehensive data comparison. The data show that the new similarity law greatly improves the accuracy of wind tunnel tests.
Keywords: Similarity law derivation | High-speed weapon delivery | Carrier and missile interference | Multi-body separation | Free-flight wind tunnel test
مقاله انگلیسی
7 Wake modeling of wind turbines using machine learning
مدل سازی توربین های بادی با استفاده از یادگیری ماشین-2020
In the paper, a novel framework that employs the machine learning and CFD (computational fluid dynamics) simulation to develop new wake velocity and turbulence models with high accuracy and good efficiency is proposed to improve the turbine wake predictions. An ANN (artificial neural network) model based on the backpropagation (BP) algorithm is designed to build the underlying spatial relationship between the inflow conditions and the three-dimensional wake flows. To save the computational cost, a reduced-order turbine model ADM-R (actuator disk model with rotation), is incorporated into RANS (Reynolds-averaged Navier-Stokes equations) simulations coupled with a modified k − ε turbulence model to provide big datasets of wake flow for training, testing, and validation of the ANN model. The numerical framework of RANS/ADM-R simulations is validated by a standalone Vestas V80 2MW wind turbine and NTNU wind tunnel test of double aligned turbines. In the ANN-based wake model, the inflow wind speed and turbulence intensity at hub height are selected as input variables, while the spatial velocity deficit and added turbulence kinetic energy (TKE) in wake field are taken as output variables. The ANN-based wake model is first deployed to a standalone turbine, and then the spatial wake characteristics and power generation of an aligned 8-turbine row as representation of Horns Rev wind farm are also validated against Large Eddy Simulations (LES) and field measurement. The results of ANNbased wake model show good agreement with the numerical simulations and measurement data, indicating that the ANN is capable of establishing the complex spatial relationship between inflow conditions and the wake flows. The machine learning techniques can remarkably improve the accuracy and efficiency of wake predictions.
Keywords: Wind turbine wake | Wake model | Artificial neural network (ANN) | Machine learning | ADM-R (actuator-disk model with rotation) | model | Computational fluid dynamics (CFD)
مقاله انگلیسی
8 AI Aided Noise Processing of Spintronic Based IoT Sensor for Magnetocardiography Application
پردازش نویز به کمک هوش مصنوعی مبتنی بر حسگر اینترنت اشیا بر Spintronic برای کاربرد مغناطیسی قلب-2020
As we are about to embark upon the highly hyped “Society 5.0”, powered by the Internet of Things (IoT), traditional ways to monitor human heart signals for tracking cardio-vascular conditions are challenging, particularly in remote healthcare settings. On the merits of low power consumption, portability, and non-intrusiveness, there are no suitable IoT solutions that can provide information comparable to the conventional Electrocardiography (ECG). In this paper, we propose an IoT device utilizing a spintronic-technology-based ultra-sensitive Magnetic Tunnel Junction (MTJ) sensor that measures the magnetic fields produced by cardio-vascular electromagnetic activity, i.e. Magentocardiography (MCG). We treat the low-frequency noise generated by the sensor, which is also a challenge for most other sensors dealing with low-frequency bio-magnetic signals. Instead of relying on generic signal processing techniques such as moving average, we employ deep-learning training on biomagnetic signals. Using an existing dataset of ECG records, MCG signals are synthesized. A unique deep learning model, composed of a one-dimensional convolution layer, Gated Recurrent Unit (GRU) layer, and a fully-connected neural layer, is trained using the labeled data moving through a striding window, which is able to smartly capture and eliminate the noise features. Simulation results are reported to evaluate the effectiveness of the proposed method that demonstrates encouraging performance.
Index Terms: Smart health | IoT | ECG | MCG | deep learning | noise | spintronic sensor | convolution | GRU | medical analytics
مقاله انگلیسی
9 Derivation and verification of a similarity law for wind-tunnel free-flight tests of heavy-store separation
استخراج و تأیید قانون تشابه برای آزمایش های پرواز آزاد تونل بادی از تفکیک فروشگاه های سنگین-2020
Test-method research was carried out to consider the separation of a heavy store, and a similarity law for unsteady wind-tunnel free-flight tests of air-launch rockets was derived. The derivation of this similarity law considers the particular characteristics of a heavy store and aerodynamic interference with the carrier and focuses on solving the following problems: the separation of a heavy store causes a real carrier to have an acceleration and a velocity that cannot be ignored; the carrier in a wind-tunnel test is vertically fixed; and a wind-tunnel test cannot meet the Froude number (Fr) similarity condition. According to the special characteristics of heavy-store separation, a similarity law for wind-tunnel free-flight tests of heavy-store separation is derived. Computational fluid dynamics simulations are used to verify the new similarity law. The results show that the new similarity law can simulate the separation trajectory more realistically than existing methods, and the linear and angular displacement errors are decreased by an order of magnitude. The experimental accuracy of the new similarity law is even higher than that of a separation trajectory satisfying Fr matching. It is demonstrated that the new similarity law can be used to carry out unsteady experimental research on the separation of a heavy store such as an air-launch rocket, and this new law provides strong support for establishing the safety boundaries of heavy-store separation.
Keywords: Air-launch rocket | Similarity law derivation | Carrier and store interference | Multi-body separation | Wind-tunnel free-drop testing | Heavy-store airdrop
مقاله انگلیسی
10 Risk assessment and management via multi-source information fusion for undersea tunnel construction
ارزیابی و مدیریت ریسک از طریق تلفیق اطلاعات چند منبع برای ساخت تونل زیر زمینی -2020
The construction of undersea tunnels is an extremely risky endeavor that is vulnerable to water seepage and gushing due to the high water pressure, complex geological conditions, and pore water trapped in unstable rocks. This risk can lead to the collapse of tunnels under construction and disastrous consequences of fatalities and injuries as well as project delays and financial losses. The current risk management practices for tunnel construction projects in China are static and rely on the subjective judgement of experts and practitioners and do not incorporate real-time monitoring data during the construction process at this time. This paper presents a new method and system to assess and manage the risks during the construction process by coupling the risk management system and the quality management system and integrating jobsite monitoring data, design data, and environmental data. In this new method and system, the risk factors are categorized into (hu)man, material, machine, method, and environment, or 4M1E, and are quantitatively measured. The Dempster-Shaffer (D-S) theory was adopted in this method to both fuse the 4M1E data and to compute the aggregate risk index. This new method and system was tested during the Xiamen Metro Line No. 3 project when a shield machine cutter accident occurred. The results show that, before the accident, the individual risk measures in all five dimensions (4M1E) and the aggregate risk index were extremely high, which clearly illustrated the feasibility and capability of the newly developed method and system.
Keywords: Undersea tunnel construction | Multi-source information fusion | Construction risk | D-S evidence theory | Fuzzy matter element
مقاله انگلیسی
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