סמינר המחלקה להנדסה ביו רפואית

02 בדצמבר 2018, 14:00 
הבניין הרב תחומי חדר 315  
ללא עלות
סמינר המחלקה להנדסה ביו רפואית

Intracranial fluid dynamics A mathematical Model

By Yuliya Zadka

Traumatic brain injury (TBI) is the most common cause of death and disability, mainly caused from an accident or falling. A neurological damage can occur from minutes to hours or days after the impact, making it the leading cause of in hospital deaths after TBI. Two major pathophysiological conditions that may evolve after the TBI are Hydrocephalus and Edema. Hydrocephalus defined as an excessive accumulation of CSF mainly in the lateral ventricles. Edema is classified into two main categories: cytotoxic and vasogenic. Cytotoxic edema caused by cerebral ischemia after TBI leads to intracellular accumulation of fluid in the brain tissue cells. Vasogenic edema occurs when there is an increase in blood-brain barrier permeability, which leads to extracellular accumulation of fluid. Those pathophysiological conditions lead to elevated intracranial pressure (ICP) and decreased cerebral blood flow.
In order to understand the complex interactions of brain fluids in healthy and pathophysiological conditions, we developed an intracranial fluid dynamics mathematical model. We used an electrical lumped parameters model technique in order to model the brain fluid dynamics system in an equivalent electrical circuit. The model included three components: blood, cerebrospinal fluid and brain tissue. The rigid cranium enclosing the brain creates a distinctive and complex environment, greatly affecting system dynamics and ICP. Using the model, we were able to reproduce the physiological behavior of the system as well as the pathophysiological behavior at elevated ICP and reduced CBF in Hydrocephalus and Edema.

יריד תעסוקה

המחלקה להנדסה ביו-רפואית, הפקולטה להנדסה, אוניברסיטת ת"א

18 בדצמבר 2018, 15:00 - 18:00 
הפקולטה להנדסה אוניברסיטת תל-אביב  
כנס

הנכם מוזמנים להשתתף ביריד תעסוקה שיתקיים ביום שלישי, 18.12.2018, בין השעות 15:00-18:00 ברחבת הלובי של הבניין הרב תחומי,  אוניברסיטת תל-אביב.

 

כזכור, בשנה שעברה התקיים היריד הראשון מסוגו ונחל הצלחה רבה הן בתעשייה והן בקרב הסטודנטים והבוגרים. ביריד ישתתפו גם הפעם חברות בתחום הביו-רפואה וחברות ממגזרי היי-טק אחרים.

 

לרישום ליריד תעסוקה, מענה לשאלות ואישור השתתפות אנא פנו ליערית רחמים אברוצקי – מנהלת קשרי תעשיה של ארגון ה - IAP,

טלפון: 03-6405532;

אי-מייל:  yaaritr@tauex.tau.ac.il

סמינר מחלקתי אלקטרוניקה פיזיקאלית : Ram Tuvi

06 בדצמבר 2018, 15:00 
פקולטה להנדסה, ביניין כיתות, חדר 011  
סמינר מחלקתי אלקטרוניקה פיזיקאלית : Ram Tuvi

סמינר רם טובי

You are invited to attend a lecture

Beam-Based Local Tomographic Inverse Scattering

:By

Ram Tuvi

(Ph.D. student Under the joint supervision of Prof. Ehud Heyman of the Faculty of Engineering, TAU, and Prof. Timor Melamed of the Electrical and Computer Engineering Dept, BGU)

 

Abstract

We present a novel strategy for local-tomographic inverse scattering using of beam-wave processing. We actually formulate two self-consistent inversion schemes: a multi-frequency scheme which is used if the scattering data is given as a function of frequency over a wide frequency band, and a time domain scheme which used if the data is given in the short-pulse time domain. 

The frequency domain scheme utilizes a phase-space set of iso-diffracting Gaussian beams (ID-GB) while the time domain scheme utilizes a phase-space set of iso-diffracting pulsed beams (ID-PB). The term iso-diffracting implies that the propagation parameters of these beams are frequency independent and need to be calculated only once and then used for all frequencies.

The theory is structured upon frame theory: It is shown that both the ID-GB set and the ID-PB set constitute frames everywhere in the propagation domain, and thus can be used for local expansion of fields or sources, as an alternative to the conventional plane-wave transforms. They also generalize the standard window Fourier transform frames and the windowed Radon transforms frames.

In the inversion schemes, these "beam frames" are utilized for local phase-space pre-processing of the scattering data, and then for local "filtered-backpropagation" and medium reconstruction. A cogent physical interpretation of these operations is obtained via asymptotic analysis. The efficacy and accuracy of these beam formulations are explored via numerical examples.

 

 On Thursday, Dec 6th, 2018, 15:00

Room 011, Kitot building

Elbit Hanukkah Fest @ TAU

05 בדצמבר 2018, 11:00 - 14:00 
הפקולטה להנדסה אוניברסיטת תל-אביב  
חינם
חנוכה

פסטיבל חנוכה בשיתוף חברת Elbit Systems Career, שיתקיים ב-5.12 בשדרת הדקלים.

להשתתפות בפסטיבל וכניסה להגרלה יש להירשם מראש בלינק הבא: https://goo.gl/forms/e8m30WxiJWLs39xz1

 

סמינר מחלקתי אלקטרוניקה פיזיקאלית : Parry Yu Chen

29 בנובמבר 2018, 15:00 
פקולטה להנדסה, ביניין כיתות, חדר 011  
סמינר מחלקתי אלקטרוניקה פיזיקאלית : Parry Yu Chen

סמינר פרי

You are invited to attend a lecture

 

Lightning-fast solution of scattering problems in nanophotonics: an effortless modal approach

:By

Parry Yu Chen

Unit of electro-optics Engineering, Ben-Gurion University

Abstract

Nanophotonic structures are capable of generating field hotspots, which can enhance quantum light-matter interactions by many orders of magnitude. However, numerical simulations for applications such as radiative heat transfer, electron energy loss spectroscopy, van der Waals forces, Purcell factor throughout a volume, and many others are challenging and often computationally prohibitive. Common to these simulations is that the Green’s function or local photonic density of states must be known at each point across a volume of space, necessitating the solution of Maxwell’s equations perhaps many thousands of times.

We propose a modal solution, which requires just a single simulation to find the modes of the nanophotonic system, from which we immediately obtain the Green’s function everywhere in space. This not only reduces simulation time by approximately 2 orders of magnitude, but also offers ready physical insight into the spatial variation of Green’s function. Modal methods have long been used for closed systems, where the formulation is exceedingly simple. We have generalized modal methods to open systems while maintaining this simplicity, catering to the explosion of research interest in nanophotonics. We furthermore present a highly-efficient exponentially-convergent method of generating the modes themselves

 

 

On Thursday, November 29, 2018, 15:00

Room 011, Kitot building

לכבוד חודש המודעות הבינלאומי לפצעי לחץ, פרופ' עמית גפן מסביר על חשיבות התנועה

  • תגיות:

אנו מציינים כעת את חודש המודעות הבינלאומי לפצעי לחץ, אותו יזם וקידם פרופ' עמית גפן מהמחלקה להנדסה ביו-רפואית בפקולטה להנדסה, בעת שהיה נשיא האיגוד האירופי לפצעי לחץ.

 

השפעתם של פצעי לחץ על תוחלת ואיכות החיים של מטופלים בכל הגילאים ובמגוון מצבים רפואיים כמו גם על עלויות בריאות היא עצומה, ולכן מוקדש מירב זמנו של פרופ' גפן בשני העשורים האחרונים לפעילות מחקרית בינלאומית ולקידום הידע המדעי בנושא ושילובו בהנחיות בינלאומיות למניעה וטיפול.

 

"כידוע, פצעי לחץ גובים מחירים קשים מילדים ופגים, צעירים וקשישים, מנותחים, יולדות ועוד, אולם בידינו היכולת לצמצם את השפעתם המזיקה באמצעות שיתוף פעולה ליצירת ידע מדעי חדש ושימוש בו לפיתוח  הנחיות, התוויות וטכנולוגיות פורצות-דרך. החלפת מידע מדעי וקליני חדש מבוסס-ראיות בנושא חשוב זה בין כל הגורמים הרפואיים, גופי הממשל ותעשיית המכשור והציוד הרפואי היא המפתח לקידום המניעה והטיפול בפצעים הקשים הללו" כך מסביר פרופ' גפן.

 

לאחרונה קיבל השיח הרב-מקצועי שיזם פרופ' גפן כאמור ביטוי באמצעי תקשורת שונים בישראל, ולהלן מספר קישורים לכתבות שפורסמו בימים ובשבועות האחרונים בהם מסביר על תופעת פצעי הלחץ, הסיבות ודרכי טיפול:

פצעי לחץ: עלייה דרמטית בשכיחות בישראל

כתבה ב - doctors

 

מיולדות ופגים ועד סופרמן: 11 עובדות על פצעי לחץ

כתבה ב - ynet 

School of Mechanical Engineering Aviad Sasson

05 בדצמבר 2018, 14:00 - 15:00 
בניין וולפסון חדר 206  
0
School of Mechanical Engineering Aviad Sasson

 

 

School of Mechanical Engineering Seminar
Wednesday, December 05, 2018 at 14.00
Wolfson Building of Mechanical Engineering, Room 206

 

The Parametric HFGMC Micromechanics for Nonlinear and Damage Modeling of Multiphase Materials

Aviad Levi Sasson

 Ph.D. student of Prof. Rami Haj-Ali and Prof. Jacob Aboudi

This study expands the parametric HFGMC capabilities to model and solve engineering problems. New condensed formulation is proposed and proved to yield good results for the effective thermo-mechanical properties and the spatial elastic fields in terms of computing time. For the first time, the parametric HFGMC is extended to predict the effective thermal properties of composite material: coefficients of thermal expansion, effective thermal conductivity and heat capacity at constant pressure and constant volume.

A continuum damage model has been integrated with the parametric HFGMC. This damage model was originated from the principal of energy dissipation proposed by Marigo (1981) model and was coupled with Ledeveze-Lemaitre (1984) model. The Marigo damage model was revised in the current work to eliminate nonphysical behavior under shear loading conditions. The corrected damage model is implemented at the subcell level so each subcell can detect failure due to its local stress state. Material softening behavior due to damage is implemented as well. The isotropic damage law and its evolution generates both an effective anisotropic damage behavior in the global (composite) level and global nonlinear stress-strain response. Several material systems were used to demonstrate the new damage and failure prediction capabilities of the parametric HFGMC. The obtained failure envelops from the parametric HFGMC were compared with experimental results and showed very good agreement. For the first time, micromechanical based failure envelops are matched with new analytical-mathematical expressions for future design and analysis and to reduced computational effort during analyses.

Multiscale analysis of laminated composite structures is proposed by integrating the parametric HFGMC with the classical FE. The multiscale analysis is compared with the experimental results for the cases of notched laminated composite coupons that are subjected to tension and compression loading. In additions, the parametric HFGMC is used to model the mechanical behavior of a Dyneema based soft composite. The new capacities of the parametric HFGMC are shown again to succeed with the prediction of stress-strain curves of soft composite. New experimental tests for the soft composite are designed and proposed in the framework of this study in order to compare the periodic HFGMC prediction with some measurements. The parametric HFGMC shows good agreement with the measured elastic properties.  This talk will conclude by discussing potential future extensions of the proposed micromechanical framework.

School of Mechanical Engineering Denis Voskov

31 בדצמבר 2018, 15:00 
בניין וולפסון חדר 206  
0
School of Mechanical Engineering Denis Voskov

 

 

 

 

School of Mechanical Engineering Seminar
Monday, December 31, 2018 at 14:00
Wolfson Building of Mechanical Engineering, Room 206

 

Efficient and robust forward simulation of complex geothermal processes

 

Denis Voskov

Department of Geoscience and Engineering, TU Delft

Department of Energy Resources Engineering, Stanford University

 

In the recent years, geothermal technology has received substantial attention as an alternative source of energy. However, the lack of detailed information about subsurface formations of interest often introduces significant uncertainties to the technological and economic planning of geothermal projects. That makes the robustness and efficiency of forward simulation extremely important. Geothermal modeling implies the solution of governing laws describing mass and energy transfer in the subsurface, which in turn requires the linearization of strongly nonlinear systems of equations. In my talk, I will describe a novel linearization strategy – Operator-Based Linearization (OBL) - capable to deal with complex nonlinear problems. The key idea of the approach is a transformation of discretised mass- and energy-conservation equations to an operator form with separate space-dependent and state-dependent operators. This transformation provides an opportunity for an approximate representation of the exact physics which is conceptually similar to an approximate representation of space and time discretization performed in conventional simulation. The current version of our simulation framework for geothermal applications includes OBL approximation for thermal-compositional physics of convection, conduction and buoyancy forces with multi-segmented wells and advanced nonlinear solvers.

The OBL approach enhances the computational performance of simulation and provides an opportunity for a simplified porting of simulation engine to heterogeneous computing architectures (such as GPU) which improves the performance even farther. I will show a few examples when the OBL framework is complemented with unique advanced simulation technologies such as compositional multiscale transport or species-based formulation for reactive transport. The advanced nonlinear solvers in OBL formulation is implemented based on the direct analysis of conventional operators in parameter space of nonlinear problem. In addition, the OBL approach can be used in creating physics-based data-driven models for complex subsurface processes. I will discuss several practical applications, ongoing developments and possible extensions of the proposed methodology.

 

Bio: Dr. Voskov is an Associate Professor at TU Delft. He received his PhD degree in Applied Mathematics from Gubkin’s Russian University of Oil and Gas in 2002. Dr. Voskov former positions include: senior researcher at Stanford University, founder and chief technology officer of Rock Flow Dynamics company, chief engineer at YUKOS EP company, and leading engineer-mathematician at the Institute for Problems in Mechanics within the Russian Academy of Sciences.

 

EE Seminar: TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set

28 בנובמבר 2018, 15:30 
חדר 011, בניין כיתות-חשמל  

Speaker: Moran Rubin

M.Sc. student under the supervision of Prof. Natan T. Shaked

 

Wednesday, November 28th 2018 at 15:30

Room 011, Kitot Bldg., Faculty of Engineering

 

TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set

 

 

Abstract

 

We propose a deep learning approach for medical imaging that copes with the problem of a small labeled training set, the main bottleneck of deep learning, and apply it for classification of healthy and cancer cells acquired by quantitative phase imaging. The proposed method is hybridization between transfer learning and generative adversarial networks (GANs). Healthy cells and cancer cells of different metastatic potential have been imaged by low-coherence off-axis holography. After the acquisition, the optical path delay maps of the cells have been extracted and directly used as an input to the deep networks. In order to cope with the small number of classified images, we have used the GAN setup to train a large number of unclassified images from another cell type (sperm cells). After this preliminary training, and after transforming the last layers of the network with new ones, we have designed an automatic classifier that copes with a small training set and classified the correct cell type (healthy/primary cancer/metastatic cancer) with 90-99% accuracy. We believe that our approach makes the combination of holographic microscopy and deep learning networks more accessible to the medical field by enabling a rapid, automatic and accurate classification in stain-free imaging flow cytometry.

עמודים

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