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1 |
The physical and mechanical properties for flexible biomass particles using computer vision
خواص فیزیکی و مکانیکی ذرات زیست توده انعطاف پذیر با استفاده از بینایی کامپیوتری-2022 The combustion and fluidization behavior of biomass depend on the physical properties (size, morphology, and
density) and mechanical performances (elastic modulus, Poisson’s ratio, tensile strength and failure strain), but
their quantitative models have rarely been focused in previous researchers. Hence, a static image measurement
for particle physical properties is studied. Combining the uniaxial tension and digital image correlation tech-
nology, the dynamic image measurement method for the mechanical properties is proposed. The results indicate
that the average roundness, rectangularity, and sphericity of present biomass particles are 0.2, 0.4, and 0.16,
respectively. The equivalent diameter and density obey the skewed normal distribution. The tensile strength and
failure stress are sensitive to stretching rate, fiber size and orientation. The distribution intervals of elastic
modulus and Poisson’s ratio are 30–600 MPa and 0.25–0.307, respectively. The stress–strain curves obtained
from imaging experiments agree well with the result of finite element method. This study provides the operating
parameters for the numerical simulation of particles in the fluidized bed and combustor. Furthermore, the
computer vision measurement method can be extended to the investigations of fossil fuels. keywords: ذرات زیست توده | مشخصات فیزیکی | اجرای مکانیکی | تست کشش | آزمایش تصویربرداری | بینایی کامپیوتر | Biomass particle | Physical properties | Mechanical performances | Tensile testing | Imaging experiment | Computer vision |
مقاله انگلیسی |
2 |
General Mixed-State Quantum Data Compression With and Without Entanglement Assistance
فشرده سازی داده های کوانتومی حالت مخلوط عمومی با و بدون کمک درهم تنیدگی-2022 We consider the most general finite-dimensional
quantum mechanical information source, which is given by a
quantum system A that is correlated with a reference system R.
The task is to compress A in such a way as to reproduce the
joint source state ρAR at the decoder with asymptotically high
fidelity. This includes Schumacher’s original quantum source
coding problem of a pure state ensemble and that of a single
pure entangled state, as well as general mixed state ensembles.
Here, we determine the optimal compression rate (in qubits per
source system) in terms of the Koashi-Imoto decomposition of
the source into a classical, a quantum, and a redundant part.
The same decomposition yields the optimal rate in the presence
of unlimited entanglement between compressor and decoder, and
indeed the full region of feasible qubit-ebit rate pairs.
keywords: Quantum information | source coding | entanglement. |
مقاله انگلیسی |
3 |
High-Stability Cryogenic System for Quantum Computing With Compact Packaged Ion Traps
سیستم برودتی با پایداری بالا برای محاسبات کوانتومی با تله های یونی بسته بندی شده فشرده-2022 Cryogenic environments benefit ion trapping experiments by offering lower motional heating
rates, collision energies, and an ultrahigh vacuum (UHV) environment for maintaining long ion chains
for extended periods of time. Mechanical vibrations caused by compressors in closed-cycle cryostats can
introduce relative motion between the ion and the wavefronts of lasers used to manipulate the ions. Here,
we present a novel ion trapping system where a commercial low-vibration closed-cycle cryostat is used
in a custom monolithic enclosure. We measure mechanical vibrations of the sample stage using an optical
interferometer, and observe a root-mean-square relative displacement of 2.4 nm and a peak-to-peak displacement of 17 nm between free-space beams and the trapping location. We packaged a surface ion trap
in a cryopackage assembly that enables easy handling while creating a UHV environment for the ions. The
trap cryopackage contains activated carbon getter material for enhanced sorption pumping near the trapping
location, and source material for ablation loading. Using 171Yb+ as our ion, we estimate the operating
pressure of the trap as a function of package temperature using phase transitions of zig-zag ion chains as a
probe. We measured the radial mode heating rate of a single ion to be 13 quanta/s on average. The Ramsey
coherence measurements yield 330-ms coherence time for counter-propagating Raman carrier transitions
using a 355-nm mode-locked pulse laser, demonstrating the high optical stability.
INDEX TERMS: Optomechanical design | quantum computing | trapped ions. |
مقاله انگلیسی |
4 |
Incompressibility of Classical Distributions
تراکم ناپذیری توزیع های کلاسیک-2022 In blind compression of quantum states, a sender
Alice is given a specimen of a quantum state ρ drawn from
a known ensemble (but without knowing what ρ is), and she
transmits sufficient quantum data to a receiver Bob so that
he can decode a near perfect specimen of ρ. For many such
states drawn iid from the ensemble, the asymptotically achievable
rate is the number of qubits required to be transmitted per
state. The Holevo information is a lower bound for the achievable rate, and is attained for pure state ensembles, or in the
related scenario of entanglement-assisted visible compression of
mixed states wherein Alice knows what state is drawn. In this
paper, we prove a general and robust lower bound on the
achievable rate for ensembles of classical states, which holds
even in the least demanding setting when Alice and Bob share
free entanglement and a constant per-copy error is allowed.
We apply the bound to a specific ensemble of only two states
and prove a near-maximal separation (saturating the dimension
bound in leading order) between the best achievable rate and
the Holevo information for constant error. This also implies
that the ensemble is incompressible – compression does not
reduce the communication cost by much. Since the states are
classical, the observed incompressibility is not fundamentally
quantum mechanical. We lower bound the difference between
the achievable rate and the Holevo information in terms of
quantitative limitations to clone the specimen or to distinguish
the two classical states.
Index Terms— Blind compression | classical distributions | quantum states | free entanglement | Holevo information | constant error | incompressibility |
مقاله انگلیسی |
5 |
In-situ optimization of thermoset composite additive manufacturing via deep learning and computer vision
بهینه سازی درجای تولید افزودنی کامپوزیت ترموست از طریق یادگیری عمیق و بینایی کامپیوتری-2022 With the advent of extrusion additive manufacturing (AM), fabrication of high-performance thermoset com-
posites without the need of tooling has become a reality. However, finding an optimal set of printing parameters
for these thermoset composites during extrusion requires tedious experimentation as composite ink properties
can vary significantly with respect to environmental parameters such as temperature and relative humidity.
Addressing this challenge, this study presents a novel optimization framework that utilizes computer vision and
deep learning (DL) to optimize the calibration and printing processes of thermoset composite AM. Unlike
traditional DL models where printing parameters are determined prior to printing, our proposed framework
dynamically and autonomously adjusts the printing parameters during extrusion. A novel DL integrated extrusion
AM system is developed to determine the optimal printing parameters including print speed, road width, and
layer height for a given composite ink. This closed loop system is consisted of a computer communicating with an
extrusion AM system, a camera to perform in-situ imaging and several high accuracy convolution neural net-
works (CNNs) selecting the ideal process parameters for composite AM. The results show that our proposed
process optimization framework was able to autonomously determine these parameters for a carbon fiber-
composite ink. Consequently, specimens with complex geometries could be fabricated without visible defects
and with maximum fiber alignment and thus enhancing the mechanical performance of the specimen’s com-
posite material. Moreover, our proposed framework minimizes a labor-intensive procedure required to additively
manufacture thermoset composites by optimizing the extrusion process without any user intervention. keywords: یادگیری عمیق | بینایی کامپیوتر | اکستروژن | پرینت سه بعدی کامپوزیت | Deep learning | Computer vision | Extrusion | Composite 3D printing |
مقاله انگلیسی |
6 |
Next generation material interfaces for neural engineering
واسط های مواد نسل بعدی برای مهندسی عصبی-2021 Neural implant technology is rapidly progressing, and gaining
broad interest in research fields such as electrical engineering,
materials science, neurobiology, and data science. As the
potential applications of neural devices have increased, new
technologies to make neural intervention longer-lasting and
less invasive have brought attention to neural interface
engineering. This review will focus on recent developments in
materials for neural implants, highlighting new technologies in
the fields of soft electrodes, mechanical and chemical
engineering of interface coatings, and remotely powered
devices. In this context, novel implantation strategies,
manufacturing methods, and combinatorial device functions
will also be discussed. |
مقاله انگلیسی |
7 |
Nanoinfiltration behavior of carbon nanotube based nanocomposites with enhanced mechanical and electrical properties
رفتار نانوفیلتراسیون نانوکامپوزیت های مبتنی بر نانولوله کربنی با خواص مکانیکی و الکتریکی بهبود یافته-2021 In this work, carbon nanotube (CNT) based nanocomposites with high mass fraction are proposed by
in-situ bridging carbon matrix into CNT paper through optimized chemical vapor infiltration (CVI).
Nanoinfiltration behavior of CNTs is basically investigated under the CVI process. The contact between
each CNT can be strengthened and the conductive pathways can be established, resulting in the better
mechanical and electrical properties. Compared with the pristine CNT paper, the CNT/C composite after
pyrolysis process confirms a remarkable advance in tensile strength (up to 310 ± 13 MPa) and Young’s
modulus (up to 2.4 ± 0.1 GPa). Besides, a notable feature of electrical conductivity also shows an improvement up to 8.5 S/cm, which can be attributed to the mass fraction of CNT (41 wt%) breaking the limits of
percolation thresholds and the efficient densification of this sample to establish the conductive pathways.
This study has a broad application in the development of the multi-functional electrical and engineering
materials.
Keywords: Carbon nanotube | Chemical vapor infiltration (CVI) | Nanocomposites |
مقاله انگلیسی |
8 |
A review and perspectives on predicting the performance and durability of electrical contacts in automotive applications
بررسی و دیدگاههایی در مورد پیشبینی عملکرد و دوام کنتاکتهای الکتریکی در کاربردهای خودرو-2021 This review reports the recent progress in predicting the performance and long-term durability of
electrical connectors in the automotive industry. The review features a short introduction to
electrical contacts as well as the validation process before product launch, followed by a study of
fretting wear and the latest mathematical models describing this phenomenon. We discuss approaches to numerical modeling in the micro- and macro-scale, including the identification of the
most promising research approaches to allow durability prediction of an electrical connector.
Finally, we address some gaps in the research which require further investigation. This would
allow further development of numerical models enabling the prediction of automotive connector
durability with regard to its electrical and mechanical performance, and hence, the performance
of the entire wire harness.
Keywords: Fretting | Modeling and simulation | Numerical modeling | Mechanics of materials | Electrical and electronic engineering | Modeling of degradation | LSR aging |
مقاله انگلیسی |
9 |
Chemical adsorption on 2D dielectric nanosheets for matrix free nanocomposites with ultrahigh electrical energy storage
جذب شیمیایی روی نانوصفحات دی الکتریک دوبعدی برای نانوکامپوزیت های بدون ماتریس با ذخیره انرژی الکتریکی فوق العاده بالا-2021 Relaxor ferroelectric polymers display great potential in capacitor dielectric applications because of their
excellent flexibility, light weight, and high dielectric constant. However, their electrical energy storage
capacity is limited by their high conduction losses and low dielectric strength, which primarily originates
from the impact-ionization-induced electron multiplication, low mechanical modulus, and low thermal
conductivity of the dielectric polymers. Here a matrix free strategy is developed to effectively suppress
electron multiplication effects and to enhance mechanical modulus and thermal conductivity of a dielectric polymer, which involves the chemical adsorption of an electron barrier layer on boron nitride
nanosheet surfaces by chemically adsorbing an amino-containing polymer. A dramatic decrease of leakage current (from 2.4 106 to 1.1 107 A cm2 at 100 MV m1) and a substantial increase of breakdown strength (from 340 to 742 MV m1) were achieved in the nanocompostes, which result in a
remarkable increase of discharge energy density (from 5.2 to 31.8 J cm3). Moreover, the dielectric
strength of the nanocomposites suffering an electrical breakdown could be restored to 88% of the original
value. This study demonstrates a rational design for fabricating dielectric polymer nanocomposites with
greatly enhanced electric energy storage capacity.
Keywords: Boron nitride nanosheets | Electron barrier layer | Relaxor ferroelectric polymers | Nanocomposites | Electrical energy storage |
مقاله انگلیسی |
10 |
Assisted development process for model-based systems engineering
فرآیند توسعه کمکی برای مهندسی سیستم های مبتنی بر مدل-2021 The system development process is becoming increasingly complex as the systems themselves become more and more complex. At the same time, the various disciplines such as mechanical engineering, electrical engineering and software engineering are becoming increasingly intermixed, so that companies in one discipline are experiencing leaps and bounds in the complexity of their systems and their development. For this reason, this publication presents a concept of a virtual assistant that leads through a development phase. It shows that the software supporting the development needs an information model to store the data of the developed system and to connect it with the existing knowledge. This knowledge can either be available internally or on the web. The development process should therefore support cooperation so that the assistance software and engineers interact with each other.
Keywords: Model-based Systems Engineering | chatbots | virtual assistants | development process | conversation logic |
مقاله انگلیسی |