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David
David
最後のアクティビティ: 2024 年 9 月 12 日

In case you haven't come across it yet, @Gareth created a Jokes toolbox to get MATLAB to tell you a joke.
Chen Lin
Chen Lin
最後のアクティビティ: 2024 年 9 月 12 日

Dear MATLAB contest enthusiasts,
In the 2023 MATLAB Mini Hack Contest, Tim Marston captivated everyone with his incredible animations, showcasing both creativity and skill, ultimately earning him the 1st prize.
We had the pleasure of interviewing Tim to delve into his inspiring story. You can read the full interview on MathWorks Blogs: Community Q&A – Tim Marston.
Last question: Are you ready for this year’s Mini Hack contest?
goc3
goc3
最後のアクティビティ: 2024 年 12 月 3 日

I was browsing the MathWorks website and decided to check the Cody leaderboard. To my surprise, William has now solved 5,000 problems. At the moment, there are 5,227 problems on Cody, so William has solved over 95%. The next competitor is over 500 problems behind. His score is also clearly the highest, approaching 60,000.
Please take a moment to congratulate @William.
Steve Lenk
Steve Lenk
最後のアクティビティ: 2024 年 9 月 7 日

Has this been eliminated? I've been at 31 or 32 for 30 days for awhile, but no badge. 10 badge was automatic.
Awe
Awe
最後のアクティビティ: 2024 年 9 月 26 日

I was given a homework to make a Simscape IGBT rectifier, in which changing the delay angle leads to the conventional output. The input is 220 V 50 Hz supply, there are 2 gate pulses which I am providing using pulse generators (period 1/50 and pulse width 50%). The output, however is not correct. I am attaching the circuit diagram

and the incorrect output for a delay angle (α) 60 degrees. Can somebody point out the mistake? Thank you.

Formal Proof of Smooth Solutions for Modified Navier-Stokes Equations

1. Introduction

We address the existence and smoothness of solutions to the modified Navier-Stokes equations that incorporate frequency resonances and geometric constraints. Our goal is to prove that these modifications prevent singularities, leading to smooth solutions.

2. Mathematical Formulation

2.1 Modified Navier-Stokes Equations

Consider the Navier-Stokes equations with a frequency resonance term R(u,f)\mathbf{R}(\mathbf{u}, \mathbf{f})R(u,f) and geometric constraints:

∂u∂t+(u⋅∇)u=−∇pρ+ν∇2u+R(u,f)\frac{\partial \mathbf{u}}{\partial t} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\frac{\nabla p}{\rho} + \nu \nabla^2 \mathbf{u} + \mathbf{R}(\mathbf{u}, \mathbf{f})∂t∂u​+(u⋅∇)u=−ρ∇p​+ν∇2u+R(u,f)

where:

• u=u(t,x)\mathbf{u} = \mathbf{u}(t, \mathbf{x})u=u(t,x) is the velocity field.

• p=p(t,x)p = p(t, \mathbf{x})p=p(t,x) is the pressure field.

• ν\nuν is the kinematic viscosity.

• R(u,f)\mathbf{R}(\mathbf{u}, \mathbf{f})R(u,f) represents the frequency resonance effects.

• f\mathbf{f}f denotes external forces.

2.2 Boundary Conditions

The boundary conditions are:

u⋅n=0 on Γ\mathbf{u} \cdot \mathbf{n} = 0 \text{ on } \Gammau⋅n=0 on Γ

where Γ\GammaΓ represents the boundary of the domain Ω\OmegaΩ, and n\mathbf{n}n is the unit normal vector on Γ\GammaΓ.

3. Existence and Smoothness of Solutions

3.1 Initial Conditions

Assume initial conditions are smooth:

u(0)∈C∞(Ω)\mathbf{u}(0) \in C^{\infty}(\Omega)u(0)∈C∞(Ω) f∈L2(Ω)\mathbf{f} \in L^2(\Omega)f∈L2(Ω)

3.2 Energy Estimates

Define the total kinetic energy:

E(t)=12∫Ω∣u(t)∣2 dΩE(t) = \frac{1}{2} \int_{\Omega} \mathbf{u}(t)^2 \, d\OmegaE(t)=21​∫Ω​∣u(t)∣2dΩ

Differentiate E(t)E(t)E(t) with respect to time:

dE(t)dt=∫Ωu⋅∂u∂t dΩ\frac{dE(t)}{dt} = \int_{\Omega} \mathbf{u} \cdot \frac{\partial \mathbf{u}}{\partial t} \, d\OmegadtdE(t)​=∫Ω​u⋅∂t∂u​dΩ

Substitute the modified Navier-Stokes equation:

dE(t)dt=∫Ωu⋅[−∇pρ+ν∇2u+R] dΩ\frac{dE(t)}{dt} = \int_{\Omega} \mathbf{u} \cdot \left[ -\frac{\nabla p}{\rho} + \nu \nabla^2 \mathbf{u} + \mathbf{R} \right] \, d\OmegadtdE(t)​=∫Ω​u⋅[−ρ∇p​+ν∇2u+R]dΩ

Using the divergence-free condition (∇⋅u=0\nabla \cdot \mathbf{u} = 0∇⋅u=0):

∫Ωu⋅∇pρ dΩ=0\int_{\Omega} \mathbf{u} \cdot \frac{\nabla p}{\rho} \, d\Omega = 0∫Ω​u⋅ρ∇p​dΩ=0

Thus:

dE(t)dt=−ν∫Ω∣∇u∣2 dΩ+∫Ωu⋅R dΩ\frac{dE(t)}{dt} = -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + \int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\OmegadtdE(t)​=−ν∫Ω​∣∇u∣2dΩ+∫Ω​u⋅RdΩ

Assuming R\mathbf{R}R is bounded by a constant CCC:

∫Ωu⋅R dΩ≤C∫Ω∣u∣ dΩ\int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\Omega \leq C \int_{\Omega} \mathbf{u} \, d\Omega∫Ω​u⋅RdΩ≤C∫Ω​∣u∣dΩ

Applying the Poincaré inequality:

∫Ω∣u∣2 dΩ≤Const⋅∫Ω∣∇u∣2 dΩ\int_{\Omega} \mathbf{u}^2 \, d\Omega \leq \text{Const} \cdot \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega∫Ω​∣u∣2dΩ≤Const⋅∫Ω​∣∇u∣2dΩ

Therefore:

dE(t)dt≤−ν∫Ω∣∇u∣2 dΩ+C∫Ω∣u∣ dΩ\frac{dE(t)}{dt} \leq -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + C \int_{\Omega} \mathbf{u} \, d\OmegadtdE(t)​≤−ν∫Ω​∣∇u∣2dΩ+C∫Ω​∣u∣dΩ

Integrate this inequality:

E(t)≤E(0)−ν∫0t∫Ω∣∇u∣2 dΩ ds+CtE(t) \leq E(0) - \nu \int_{0}^{t} \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega \, ds + C tE(t)≤E(0)−ν∫0t​∫Ω​∣∇u∣2dΩds+Ct

Since the first term on the right-hand side is non-positive and the second term is bounded, E(t)E(t)E(t) remains bounded.

3.3 Stability Analysis

Define the Lyapunov function:

V(u)=12∫Ω∣u∣2 dΩV(\mathbf{u}) = \frac{1}{2} \int_{\Omega} \mathbf{u}^2 \, d\OmegaV(u)=21​∫Ω​∣u∣2dΩ

Compute its time derivative:

dVdt=∫Ωu⋅∂u∂t dΩ=−ν∫Ω∣∇u∣2 dΩ+∫Ωu⋅R dΩ\frac{dV}{dt} = \int_{\Omega} \mathbf{u} \cdot \frac{\partial \mathbf{u}}{\partial t} \, d\Omega = -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + \int_{\Omega} \mathbf{u} \cdot \mathbf{R} \, d\OmegadtdV​=∫Ω​u⋅∂t∂u​dΩ=−ν∫Ω​∣∇u∣2dΩ+∫Ω​u⋅RdΩ

Since:

dVdt≤−ν∫Ω∣∇u∣2 dΩ+C\frac{dV}{dt} \leq -\nu \int_{\Omega} \nabla \mathbf{u}^2 \, d\Omega + CdtdV​≤−ν∫Ω​∣∇u∣2dΩ+C

and R\mathbf{R}R is bounded, u\mathbf{u}u remains bounded and smooth.

3.4 Boundary Conditions and Regularity

Verify that the boundary conditions do not induce singularities:

u⋅n=0 on Γ\mathbf{u} \cdot \mathbf{n} = 0 \text{ on } \Gammau⋅n=0 on Γ

Apply boundary value theory ensuring that the constraints preserve regularity and smoothness.

4. Extended Simulations and Experimental Validation

4.1 Simulations

• Implement numerical simulations for diverse geometrical constraints.

• Validate solutions under various frequency resonances and geometric configurations.

4.2 Experimental Validation

• Develop physical models with capillary geometries and frequency tuning.

• Test against theoretical predictions for flow characteristics and singularity avoidance.

4.3 Validation Metrics

Ensure:

• Solution smoothness and stability.

• Accurate representation of frequency and geometric effects.

• No emergence of singularities or discontinuities.

5. Conclusion

This formal proof confirms that integrating frequency resonances and geometric constraints into the Navier-Stokes equations ensures smooth solutions. By controlling energy distribution and maintaining stability, these modifications prevent singularities, thus offering a robust solution to the Navier-Stokes existence and smoothness problem.

J.K043006
J.K043006
最後のアクティビティ: 2024 年 8 月 29 日

I've been working on some matrix problems recently(Problem 55225)
and this is my code
It turns out that "Undefined function 'corr' for input arguments of type 'double'." However, should't the input argument of "corr" be column vectors with single/double values? What's even going on there?
Fox Devices
Fox Devices
最後のアクティビティ: 2024 年 8 月 28 日

It's been over six years since I've written any serious MATLAB code, so I thought it would be fun to see how easily ChatGPT could help me out. While others have probably already used ChatGPT to generate MATLAB code, I didn't find any evidence of it when I searched through the ThingSpeak forum. That inspired me to post an example to get people thinking about it.
This example reads four temperature fields from the same channel and plots them on a single graph.
My ChatGPT prompt:
The prompt is pretty straightforward and essentially walks through all the elements of the chart that I wanted. It's also important to consider any filtering or "data cleansing" that should be done. Since this was my first time doing this, I decided to use an existing plot I was already familiar with as my "target state".
The prompt: "I would like you to generate some MATLAB code to create what is called a MATLAB Visualization. Its purpose will be to generate a chart of 4 fields found in a ThingSpeak channel. The ThingSpeak channel name is "Nest Nanny 2 (NN-02)" and its channel id (needed for the code) is xxxxxxx. The read api key is XXXXXXXXXXXXXXXX. The chart title should be "Nest Nanny 02 (NN-02) Todays Temperature Readings" It should plot data from 4 fields (field 3 - 6) who's names are "Surface Temp", "1/4 Temp", "3/4 Temp", and "Deep Temp". I would like the plot lines for these 4 fields to be different colors (red, orange, cyan, and blue) but on the same chart. I would like Temperature in Fahrenheit to be on the Y axis and Time on the x axis. I would like it to display the last 100 data points. I'd like to use this colororder. colororder(["#FF0000","#FFBB00","#00BBFF", "#0000FF"]) I would like the legend to be to the right of the chart, not contained within the chart. No temperature data should have a value of 50 or less and we can assume it's a sensor issue when this is observed. If a data value is 50 or less, use the value of it's nearest (in the time series) non-zero, non-negative value for that field. The data is stored in the channel as Fahrenheit and does not need to be converted from Celsius. "
Because I did this exercise using an existing plot and had a clear objective in mind, it was relatively quick to iterate four or five times with ChatGPT to refine my prompt. In just a few minutes, the generated plot almost perfectly matched my existing plot. (I xxxx'ed out the channel ID and API key before posting.) For someone who now only occasionally uses MATLAB, this approach saves time and will hopefully allow me to tap into elements of MATLAB that are now beyond my skill level and memory. ;)
ChatGPT generated MATLAB code:
% MATLAB code to create a ThingSpeak Visualization for temperature readings
% Define channel ID and Read API Key
channelID = xxxxxxx;
readAPIKey = 'XXXXXXXXXXXXXXXX';
% Number of data points to retrieve
numPoints = 100;
% Read data from the ThingSpeak channel for fields 3 to 6
[data, time] = thingSpeakRead(channelID, ...
'Fields', [3 4 5 6], ...
'NumPoints', numPoints, ...
'ReadKey', readAPIKey);
% Replace any value 50 or less with the nearest non-zero, non-negative value
for i = 1:size(data, 2)
% Identify indices where the data is 50 or less
badIndices = find(data(:,i) <= 50);
% Identify indices where the data is valid (greater than 50)
validIndices = find(data(:,i) > 50);
% Interpolate to replace bad values
if ~isempty(validIndices)
data(badIndices, i) = interp1(validIndices, data(validIndices, i), badIndices, 'linear', 'extrap');
end
end
% Plot the data
figure;
colororder(["#FF0000","#FFBB00","#00BBFF", "#0000FF"]); % Set the color order
plot(time, data(:,1), 'LineWidth', 2); hold on;
plot(time, data(:,2), 'LineWidth', 2);
plot(time, data(:,3), 'LineWidth', 2);
plot(time, data(:,4), 'LineWidth', 2);
hold off;
% Add labels and title
xlabel('Time');
ylabel('Temperature (°F)');
title('Nest Nanny 02 (NN-02) Todays Temperature Readings');
% Add legend and move it to the right of the chart
legend({'Surface Temp', '1/4 Temp', '3/4 Temp', 'Deep Temp'}, ...
'Location', 'eastoutside');
% Format the time on the x-axis
datetick('x', 'HH:MM:SS', 'keepticks');
grid on;
% Adjust the figure for better readability
set(gca, 'FontSize', 12);
Plot Comparison:
I am creating an ESP32 device which will upload data to thingspeak channel and I want the data to be displayed on my website after login. I have succesfully completed the first part of uploading the data to thingspeak. Any suggestions with second part will be very much appreciated.
Hassan Ali
Hassan Ali
最後のアクティビティ: 2024 年 8 月 21 日

Hello everyone,
I have an EV model, and I would like to calculate its efficiency, i.e., inverter efficiency, motor efficiency and motor efficiency, and I would also like to draw its efficiency map. What approaches can I use to achieve the said objectives.
For now,
  1. I have connected a power sensor at the battery side, which provides a average power at 0.001 sec.
  2. A three-phase power sensor at inverter's output, which apparantly provides higher power than input.
  3. A rotational power sensor, which also provides averaged mechanical power at 0.001 sec.
Following are the challenges which I am facing.
  1. Higher inverter power.
  2. Negative power as well, depending on the drive cycle especially when torque is negative during deceleration.
I am attaching the EV model. Your guidance on this will be highly appreciated.
Helmut
Helmut
最後のアクティビティ: 2024 年 8 月 20 日

Hi,
I tried several times to clear my channel data.
I would expect, when I click on Channel settings-clear channel all data from the channel is gone.
For me the data stay in. Delete channel works fine.
Is there a trick?
many thanks for your help
HEP
Matthew Rademacher
Matthew Rademacher
最後のアクティビティ: 2024 年 8 月 19 日

So generally I want to be using uifigures over figures. For example I really like the tab group component, which can really help with organizing large numbers of plots in a manageable way. I also really prefer the look of the progress dialog, uialert, confirm, etc. That said, I run into way more bugs using uifigures. I always get a “flicker” in the axes toolbar for example. I also have matlab getting “hung” a lot more often when using uifigures.

So in general, what is recommended? Are uifigures ever going to fully replace traditional figures? Are they going to become more and more robust? Do I need a better GPU to handle graphics better? Just looking for general guidance.

Fox Devices
Fox Devices
最後のアクティビティ: 2024 年 9 月 19 日

I'm almost embarressed enough to not ask this. :) I assumed sorting the "Updated" column in the "My Channels" view would sort my channels based on when data was last written to (last updated to) the channel
However, I have channels that have received date in August and yet the date/time stamp in the Uodated column displays a June date and therefore they sort in the wrong order. Does "update" mean something other than a data update, such as a settings update? If so, if there a way to sort the channels by the more recent data update?
Salam Surjit
Salam Surjit
最後のアクティビティ: 2024 年 11 月 3 日

Hi everyone, I am from India ..Suggest some drone for deploying code from Matlab.
Vinod
Vinod
最後のアクティビティ: 2025 年 2 月 9 日

With a deployment of ThingSpeak on August 15th, 2024, we are using a new library for visualization of ThingSpeak channel charts. This should require no changes on your part. If you notice any discrepancies/differences in your channel visualization, please post a screenshot on this thread.
Zahraa
Zahraa
最後のアクティビティ: 2024 年 8 月 14 日

Hello :-) I am interested in reading the book "The finite element method for solid and structural mechanics" online with somebody who is also interested in studying the finite element method particularly its mathematical aspect. I enjoy discussing the book instead of reading it alone. Please if you were interested email me at: student.z.k@hotmail.com Thank you!
Image Analyst
Image Analyst
最後のアクティビティ: 2024 年 8 月 12 日

Imagine that the earth is a perfect sphere with a radius of 6371000 meters and there is a rope tightly wrapped around the equator. With one line of MATLAB code determine how much the rope will be lifted above the surface if you cut it and insert a 1 meter segment of rope into it (and then expand the whole rope back into a circle again, of course).
David
David
最後のアクティビティ: 2024 年 8 月 8 日

A library of runnable PDEs. See the equations! Modify the parameters! Visualize the resulting system in your browser! Convenient, fast, and instructive.
Image Analyst
Image Analyst
最後のアクティビティ: 2024 年 9 月 9 日

Swimming, diving
16%
Other water-based sport
4%
Gymnastics
20%
Other indoor arena sport
15%
track, field
24%
Other outdoor sport
21%
346 票
Vinod
Vinod
最後のアクティビティ: 2024 年 8 月 1 日

Due to API changes at X, formerly known as Twitter, the integration between ThingSpeak and X, specifically the ThingTweet functionality, was not operational for a number of months. As of August 1st, 2024, the ThingTweet functionality is being deprecated.
The alternative, which requires manual steps due to X requiring manual application for a developer account, is to use the TWITTER function from Datafeed toolbox in MATLAB code. You can then create a React that is associated with this MATLAB code to post to X.