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HagesLab
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เข้าร่วมเมื่อ 2 ก.ย. 2020
วีดีโอ
Fin Energy Balance - Lecture 1 [Heat / Energy Transfer]
มุมมอง 554ปีที่แล้ว
Fin Energy Balance - Lecture 1 [Heat / Energy Transfer]
Fin Equation General Solution - Lecture 2 [Heat / Energy Transfer]
มุมมอง 249ปีที่แล้ว
Fin Equation General Solution - Lecture 2 [Heat / Energy Transfer]
Fin Boundary Conditions - Lecture 3 [Heat / Energy Transfer]
มุมมอง 384ปีที่แล้ว
Fin Boundary Conditions - Lecture 3 [Heat / Energy Transfer]
Infinite Fin Solution - Lecture 4 [Heat / Energy Transfer]
มุมมอง 211ปีที่แล้ว
Infinite Fin Solution - Lecture 4 [Heat / Energy Transfer]
Fin Effectiveness - Lecture 7 [Heat / Energy Transfer]
มุมมอง 217ปีที่แล้ว
Fin Effectiveness - Lecture 7 [Heat / Energy Transfer]
Convection Fin Tip Solution - Lecture 6 [Heat / Energy Transfer]
มุมมอง 720ปีที่แล้ว
Convection Fin Tip Solution - Lecture 6 [Heat / Energy Transfer]
Adiabatic Fin Tip Solution - Lecture 5 [Heat / Energy Transfer]
มุมมอง 978ปีที่แล้ว
Adiabatic Fin Tip Solution - Lecture 5 [Heat / Energy Transfer]
How to: Solve an ODE in Python (Boundary Value Problem)
มุมมอง 8Kปีที่แล้ว
Learn out to numerically solve an ordinary differential equation (ODE) in Python using a built in solver for boundary value problems: "scipy.integrate.solve_bvp()". Here I discuss a 2nd order ODE with 2 boundary conditions (i.e. boundary value problem - BVP). A 1D steady-state heat transfer problem is used as an example, with various boundary conditions (fixed temperature, radiation) and with t...
Fermi-Dirac Integral (Semiconductors): Derivation and Python Plotting
มุมมอง 1.8Kปีที่แล้ว
Fermi-Dirac Integral (Semiconductors): Derivation and Python Plotting
Chalcogenide Perovskite Nanoparticles "Flash Talk" | Faraday Discussion 2022 | Chuck Hages (UF)
มุมมอง 420ปีที่แล้ว
Low-temperature, Solution-based Synthesis of Chalcogenide Perovskites -Flash poster presentation for the "Emerging Inorganic Materials in Thin-film Photovoltaics" Faraday Discussion, July 2022, Bath, England Related Papers: pubs.acs.org/doi/abs/10.1021/jacs.2c06168 pubs.acs.org/doi/abs/10.1021/acs.chemmater.2c01289 Authors: Ruiquan Yang, Alex Jess, Calvin Fai, Chuck Hages University of Florida,...
Machine Learning for Analysis of TRPL Data | EMRS 2022 | Chuck Hages (UF)
มุมมอง 2902 ปีที่แล้ว
Machine Learning for Accelerated Analyses of Time-resolved Photoluminescence Data via Bayesian Inference - Invited talk for Symposium K: "Thin film chalcogenide photovoltaic materials" Authors: Calvin Fai, Tony Ladd, Chuck Hages University of Florida, Chemical Engineering, Gainesville, FL
How to Give an Effective Scientific Presentation | Chuck Hages (UF)
มุมมอง 8763 ปีที่แล้ว
How to Give an Effective Scientific Presentation | Chuck Hages (UF)
How to: Import, Plot, Fit, and Integrate Data in Python
มุมมอง 75K3 ปีที่แล้ว
How to: Import, Plot, Fit, and Integrate Data in Python
this function is really usefull!
Very good video!
first thanks a lot for the excellent video and good description then I have a question how can you find the roots of this equation: R = ∑_(k=1)^(k=100)▒∑_(j=-100)^(j=100)▒(e^12 〖 (12)〗^k )/k! k/(2π(w^2+1/4)) √(1-〖(w/(LkR^2 ))〗^2 ) ∆w ∆k , ∆k=1,∆w=LkR^2/100
more important
Hello, how ca I do this with more columns and rows, that means with a dataset?
With this method, that is np.diff(y) / np.diff(x) will compute the gradient of the data points but the derivative will have one less data point, what can be done about that?
perfect video, thanks!
This is really helpful, but the link to the python code in the description no longer works.\
Great man, but i want something. Im trying to make a code with a table of the function f and its derivative valuated but i dont know how to print without any error
Thank you for explaining in such details
Hi Chuck, I am a student at Cambridge University looking to employ MCMC or HMC on TRPL and TA datasets. I have read your paper on this subject and would be interested to know if you have released your code to run this on a CPU?
Incredible video, nice and clear explanation. 10/10
Can you please use light mode?
Hi! I have a question: the plot of the bands are the same in both cases of epsilon > 1 and epsilon <1?
thanks a lot ! <3 lil cutie
it is not necessary to define the bounds most of the time, more often, p0, the initial guess is something you need to provide
where is download your code *.py and csv file sir ?
how do you solve a 3 order ODE, is it the same as this since we have 3 dimensions for y? and the boundary conditions also double.
I LOVE YOU SO MUCH THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU
Thank you so much!!!!! You saved me!!!❤ subscribed 🥹
thank you for video. it was so easy to understand how to use this function. really perfect you know, I had a problem with code, and I didn't know what I need to do to solve. the problem was in boundary conditions. It really easy to solve my problem)
Very nice animation! What RNG are you using? How well do different RNG converge? How well would the actual digits of Pi used as a distribution source perform? I don't know why suddenly a lot more questions come to my mind. In any case: thank you very much for the inspiration!
Simple but outstanding. Deep gratitude! Thank you.
thanks a lot
Awesome! Thanks for the clear guide of how to use this matplotlib tool!
MERCI BEAUCOUP TRES INTERESSANT
Great lecture! Thank you very much!
This is a nice video. As usual, I am confused. I have never understood contourf and meshgrid. It seems to me that contourf should work with 1D arrays rlist and thetalist, and a function Z(r, theta). The function would be a 1D array of appropriate length = len(rlist)*len(thetalist). This seems completely defined, so I don't know what is accomplished with meshgrid. All I need to do is a nested loop that fills Z(r, theta) with each element of r and theta. I checked the documentation for contourf. It can accept 1D arrays, so why use meshgrid? Conceptually, I have trouble verifying that meshgrid is doing the right thing. A nested loop seems much easier to verify, because I explicitly pass in the r and theta values that I want to evaluate for Z. It's not always possible to generate a 2D array for Z, as done in the video. Sometimes, the function Z is complicated and cannot just take in 2D arrays directly. When that is the case, getting the correct Z function using meshgrid takes effort to understand exactly how meshgrid creates the grid. I basically have to reverse engineer meshgrid to fill Z. Very complicated. So, I try to work with 1D arrays and a nested loop. That always works and is simple conceptually, whereas the meshgrid technique might or might not work, depending on the function. What's really mind-bending for me is that meshgrid returns two 2D arrays, whereas conceptually a contour plot maps two numbers to a third number, not two 2D arrays to a third number. So, the meshgrid technique is much more confusing for me to validate and conceptualize.
Having programmed in Python for some time, I found the video confusing because python does not normally perform math operations on an entire list of floats which is what is done in function f here. And, this program would not work if you manually defined xlist with something like xlist = [-10.0, -9.9, ...., 9.9, 10.0]. However, using numpy to create the list does not create a list of floats but instead a class 'numpy.ndarray' object. Python then understands math operations like xlist **2.
I am using VSCODE as my IDE. I could not get the plot window to show up, unless I added plt.show() to thee end of your code. I enjoyed your video, but I wanted to know more about which function outputs the graph, and whether or not this issue is IDE specific (spyder vs vscode)
Thanks. Very important and useful How to find conduction quasi-fermi level for a known injected carrier concentration, effective mass, and conduction band minimum?
Your videos are amazing and really helpfull. Keep going bro
Thanks for excellent video. Flux is in W/m2.
is there a way to solve these type of problems when you also have boundary conditions for the first derivative? e.g. a function that starts at (T, T') = (T0, 0) and ends at (T, T') = (0, 0) . That would mean 4 boundary conditions for a 1D problem, is it possible?
That's an awesome tutorial. It was so easy to understand the codes. Great work!!
gracias maestro
top 10 heat fin series ever
Top 5 energy transfer operation youtuber ngl
fr
14:57
This is my favorite Minecraft lets play series, keep up the good content
Cool video. This I like a lot. Thanks for the helpful instructions.
How we can find Spectroscopic Limited Maximum Efficiency (SLME) of Perovskite materials by Using CASTEP code or Python?
Please include in your title "Spyder". It will help in the search! :)
thank you, this is an awesome primer.
You are just osm where can I connect to you
thanks, very clear explination and was also interesting to see spyder used for investigation rather than jupyter lab
i dont found de CSV ?
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Thank you