מחקר חדש בסיוע שעונים חכמים: הישראלים ישנים הרבה פחות

Testing Engineer

Job Description

The validation Group, responsible for the testing of one of the flagship products of the company. Required a Testing Engineer.

מהנדס.ת אנליזות ומבנה

לאתר החברה ברחובות דרוש.ה מהנדס.ת אנליזות ומבנה
 

במסגרת התפקיד:
ביצוע אנליזות חוזק, סטטיות, דינמיות, חישובי מאמצים, תזוזות, רעידות והלמים וביצוע ניסויים במרעד

 

דרישות

סמינר מחלקה של איתמר ברטל - אידוי של נוזל הזורם כלפי מטה בשלושה צינורות מקבילים

04 במרץ 2024, 14:00 - 15:00 
פקולטה להנדסה  
0
סמינר מחלקה של איתמר ברטל - אידוי של נוזל הזורם כלפי מטה בשלושה צינורות מקבילים

 

 

SCHOOL OF MECHANICAL ENGINEERING SEMINAR

Monday 4.03.2024 at 14:00

 

Wolfson Building of Mechanical Engineering, Room 206

 

Evaporation of liquid flowing downward in three parallel pipes

Itamar Bartal

M.Sc. Student, under the supervision of Prof. Dvora Barnea and Prof. Yehuda Taitel

School of Mechanical Engineering, Tel Aviv University, Tel Aviv, Israel

 

Evaporating flow in parallel heated pipes may occur in power plants such as steam, solar, geothermic or nuclear power plants or in cooling systems such as electronic devices cooling and air conditioning systems.

Parallel heated pipes are used to enhance heat transfer due to their large surface area. However, systems of parallel heated pipes may be subjected to instability problems, flow rate maldistribution and oscillations that may impair their performance.

In the present work evaporation of liquid flowing downward in three parallel pipes with common inlet and outlet headers is studied theoretically and experimentally. Subcooled liquid enters an upper manifold, and the pipes exit is placed somewhat below a water surface open to the atmosphere. Evaporation of liquid in parallel pipes was mainly investigated in co-current horizontal and upward flows. Recently Hayat et al. (2022) studied the behavior of a system of two parallel heated pipes with an upper inlet header. They found that the static instability (Ledinegg) is not sufficient to predict some of the phenomena occurring in such systems since upward flow and oscillations of pressure and flow rates may take place in certain regions of inlet flow rates. As can be expected the degree of complexity of the behavior of three parallel heated pipes increases significantly compared to that of two parallel pipes. This is reflected both in the steady state solutions, where several steady state flow rate distributions may be obtained for the same inlet flow rate and in the various transient trajectories towards the steady state solutions. Cases of upward flow in one pipe and downward flow in the two other pipes may take place as well as upward flow in two pipes and downward flow in one pipe may occur for the same inlet flow rate, resulting in different oscillatory behavior.

 

Acknowledgments

Support for this project was provided by the ISF (Grant No. 1098/18) and Ministry of Energy (Grant No. 053-11-220).

Underground Cavity Detection Using Cross-Borehole Ground-Penetrating Radar | Caleb Leibowitz

סמינר זה יחשב כסמינר שמיעה לתלמידי תואר שני

27 בדצמבר 2023, 13:00 
zoom  
 Underground Cavity Detection Using Cross-Borehole Ground-Penetrating Radar | Caleb Leibowitz

https://tau-ac-il.zoom.us/j/86067718025?pwd=RlJBaGpQR004cWx6dWxKaHVzdkE0dz09

Meeting ID:   860 6771 8025
Passcode:       219983

 

Electrical Engineering Systems ZOOM Seminar

 

Speaker: Caleb Leibowitz

Ph.D. student under the supervision of Prof. Anthony Weiss

 

Wednesday, 27th December 2023, at 13:00

 

Underground Cavity Detection Using Cross-Borehole Ground-Penetrating Radar

 

Abstract

We study the use of cross-borehole ground-penetrating radar (GPR) to detect underground cavities. Cross-borehole GPR has been shown to perform very well on the cavity-detection problem, but in many circumstances existing techniques are incapable of achieving satisfactory results. In particular, these circumstances often include measurements in stratified soils, where the effect on the wave of propagation through an anomalous stratum can be confused with the effect on the wave of propagation through a cavity.

We develop a model of the propagation of the GPR signal through soil which contains a cavity. Using this model, we predict the effect of propagation through a cavity on both the magnitude spectrum of the measured signal and on the group dispersion observed. We validate this model, at least as it concerns the prediction of the magnitude spectrum and of group dispersion. We then provide methods to use these features of the received signal to detect underground cavities with high probability. We further show that these methods are robust to factors, such as borehole drift or certain anomalous strata, which render conventional cavity-detection methods unworkable.

 

השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום בצ'ט של שם מלא + מספר ת.ז.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

EE Systems Seminar: Quantifying and Predicting Feature Learning in Deep Finite Neural Networks | Dr. Inbar Seroussi (TAU)

סמינר זה יחשב כסמינר שמיעה לתלמידי תואר שני

27 בדצמבר 2023, 15:00 
בניין כיתות חשמל, חדר 011  
EE Systems Seminar:  Quantifying and Predicting Feature Learning in Deep Finite Neural Networks | Dr. Inbar Seroussi (TAU)

(The talk will be given in English)

 

Speaker:       Dr. Inbar Seroussi,

Applied Mathematics Department, Tel Aviv University

011 hall, Electrical Engineering-Kitot Building

 

Wednesday, December 27th, 2023

 

15:00 - 16:00

 

Quantifying and Predicting Feature Learning in Deep Finite Neural Networks
Abstract

Deep neural networks (DNNs) are powerful tools for compressing and distilling information. Their scale and complexity, often involve billions of inter-dependent internal degrees of freedom, rendering direct microscopic analysis difficult. Several works have shown that the statistics and dynamics of DNNs drastically simplify in the infinite width limit and become analytically tractable. However, the infinite width limit misses out on several qualitative aspects, such as feature learning and the fact that real-world DNNs are not nearly as over-parameterized. This gap is particularly apparent in deep convolutional neural networks (CNNs). In this talk, I will present a novel mean-field theory for finite fully trained deep non-linear DNNs. Specifically, we show that DNN layers couple only through the second moment (kernels) of their post-activations and pre-activations. Moreover, in various settings, the latter fluctuates in a nearly Gaussian manner. For CNNs with infinitely many channels, these kernels are inert, while for finite CNNs they adapt to the data. In several deep non-linear CNN models trained on real data, the resulting thermodynamic theory of deep learning yields accurate predictions. In addition, it provides a new tool to analyze and understand CNNs, and DNNs in general. This is joint work with Gadi Naveh and Zohar Ringel, for more information see https://www.nature.com/articles/s41467-023-36361-y.

Short Bio

Inbar Seroussi is a postdoctoral fellow in the Applied Mathematics department at Tel Aviv University. Before that, she was a postdoctoral fellow in the Mathematics department at the Weizmann Institute of Science, hosted by Prof. Ofer Zeitouni. She completed her Ph.D. in the Applied Mathematics department at Tel-Aviv University under the supervision of Prof. Nir Sochen. During her Ph.D., she was a long-term intern at Microsoft Research (MSR). Her research interest is at the interface between machine learning, statistical physics, and high dimensional probability.

 

השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום שם מלא + מספר ת.ז. בטופס הנוכחות שיועבר באולם במהלך הסמינר

 

 

EE Systems Seminar: Constrained system identification of reaction-diffusion equations: a bridge between control and inverse problems | Dr. Rami Katz (University of Trento)

סמינר זה יחשב כסמינר שמיעה לתלמידי תואר שני

25 בדצמבר 2023, 15:00 
בניין כיתות חשמל, חדר 011  
EE Systems Seminar: Constrained system identification of reaction-diffusion equations: a bridge between control and inverse problems | Dr. Rami Katz (University of Trento)

(The talk will be given in English)

 

Speaker:     Dr. Rami Katz  University of Trento

 

011 hall, Electrical Engineering-Kitot Building

 

Monday, June 25th, 2023

 

15:00 - 16:00

 

Constrained system identification of reaction-diffusion equations: a bridge between control and inverse problems

 

 

Abstract

System identification uses mathematical methods to reconstruct models of systems from partial and noisy data. The identification of reaction-diffusion (RD) systems is a mathematically intricate and significant research domain within systems and control, and finds application across diverse fields, spanning from multi-agent systems to chemical reactors. Many identification algorithms necessitate an infinite number of measurements and often fail to yield explicit bounds on recovery errors, in the presence of noise. In this talk, I will consider the problem of recovering the first dominant modes and initial condition of an unknown one-dimensional RD system from a finite set of filtered (noisy) state measurements. We demonstrate that Prony’s method for spike deconvolution, commonly applied in super-resolution problems, is suitable for solving this identification task. Moreover, building on recent results on the error sensitivity of Prony’s method, we derive new explicit identification guarantees, by analyzing the first-order condition numbers with respect to the measurement filtering error and showing their (super) exponential decay to zero in several identification regimes. The developed tools establish a hitherto unexplored connection between systems and control theory and inverse problems.

Joint with D. Batenkov from the School of Mathematics at Tel Aviv University.

Short Bio

Rami Katz is a post-doctoral researcher at the University of Trento, Italy. Rami recieved his B.Sc. and M.Sc in applied mathematics and his Ph.D. in electrical engineering from Tel Aviv University. He is the recipient of the KLA and Weinstein fellowships, as well as several excellence awards for both studies and teaching. He is an ECC21 best student paper award finalist and the recipient of the June 2020 editor's choice in Automatica. His research interests include control of nonlinear and distributed parameter system, systems biology and inverse problems in signal processing and control. 

השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום שם מלא + מספר ת.ז. בטופס הנוכחות שיועבר באולם במהלך הסמינר

 

 

 

 

 

 

 

 

 

EE Systems Seminar: Water Pouring solutions for log loss rate distortion| Nitzan Katz

סמינר זה יחשב כסמינר שמיעה לתלמידי תואר שני

20 בדצמבר 2023, 15:00 
בניין כיתות-חשמל, חדר 011  
EE Systems Seminar: Water Pouring solutions for log loss rate distortion| Nitzan Katz

Electrical Engineering Systems Seminar

 

Speaker: Nitzan Katz

M.Sc. student under the supervision of Prof. Meir Feder

 

Wednesday, 20th December 2023, at 15:00

Room 011, Kitot Building, Faculty of Engineering

 

Water Pouring solutions for log loss rate distortion

 

Abstract

We analyze solutions to the rate distortion problem under the log-loss distortion measure. We generalize the water pouring solution procedure, used in the Gaussian rate distortion problem under the MSE measure. These water pouring solutions utilize a diagonalizing transformation, similar to the PCA transformation in the Gaussian-MSE case. We discuss the continuous case under log-loss, where we find optimization criteria for water pouring solutions, based on entropy power. We also show an approximate water pouring solution for the discrete case, and apply it for a common real life distribution: Zipf law.

 

השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום שם מלא + מספר ת.ז. בדף הנוכחות שיועבר באולם במהלך הסמינר

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A Brief History of Adaptation and learning | Prof. Alexander Fradkov (Institute for Problems of Mechanical Engineering of RAS and Saint Petersburg University)

סמינר זה יחשב כסמינר שמיעה לתלמידי תואר שני

20 בדצמבר 2023, 11:00 
חדר 011, בניין כיתות-חשמל  
A Brief History of Adaptation and learning | Prof. Alexander Fradkov (Institute for Problems of Mechanical Engineering of RAS and Saint Petersburg University)

(The talk will be given in English)

 

Speaker:     Prof. Alexander Fradkov 

Institute for Problems of Mechanical Engineering of RAS and Saint Petersburg University

 

011 hall, Electrical Engineering-Kitot Building

 

Wednesday, December 20th, 2023

 

11:00 - 12:00

 

A Brief History of Adaptation and learning

 

Abstract

Machine learning and artificial intelligence have attracted a lot of attention during recent years. They are applied to various  new problems and it looks like they are based upon completely new ideas in the applied science. However, there exist strong links between  machine learning and lassical adaptation methods which are much lesser known and almost not exploited nowadays.

In this talk a brief overview of the historical evolution of the machine learning field will be presented and its relations to adaptation, optimization and adaptive control will be discussed.

A number of little-known facts published in hard-to-reach sources are presented.

Short Bio

Alexander L. Fradkov received the Diploma degree in mathematics from Leningrad (currently St.Petersburg) State University in 1971, the Candidate of Sciences (Ph.D.) degree in technical cybernetics in 1975 from Leningrad Mechanical Institute, and the Doctor of Sciences (Habilitation) degree in control engineering in 1986 from Leningrad Electrotechnical University. He is currently the Head of the “Control of Complex Systems” Lab of the Institute for Problems in Mechanical Engineering of Russian Academy of Sciences and Professor of the Department of Theoretical Cybernetics at Saint Petersburg University.

Prof. Fradkov is the coauthor of more than 800 journal and conference papers, 18 books and textbooks, and a holder of ten patents. In his book "Cybernetical Physics" (Nauka, 2003; Springer-Verlag, 2007) an emerging boundary field between Physics and Control areas is pioneered. His research interests include nonlinear and adaptive and learning control, control of oscillatory and chaotic systems, dynamics and control of complex physical systems and networks. Prof. Fradkov was recipient of the best paper award from the Elsevier journal Annual Reviews of Control for 2020-2022. He is IEEE and IFAC.

השתתפות בסמינר תיתן קרדיט שמיעה = עפ"י רישום שם מלא + מספר ת.ז. בטופס הנוכחות שיועבר באולם במהלך הסמינר

 

 

 

 

 

 

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