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Simulation Experiments - Science topic
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Questions related to Simulation Experiments
Introduction:
Quantum physics is a branch of physics that studies the behavior of matter and energy at very small scales, on the order of atomic distances. The quantum world is governed by laws that are very different from those of the macroscopic world, and its properties are often counterintuitive.
One of the most surprising features of the quantum world is superposition. A quantum particle can be in two or more states at once, meaning that it can be in two different places at the same time, or have two different speeds.
Question:
Is it possible that the fourth dimension is the key to understanding the quantum world?
Arguments in favor:
- Shadow analogy: A three-dimensional object can be projected into two dimensions by its shadow. This suggests that our three-dimensional reality could be the projection of a four-dimensional object.
- Perception of four-dimensional beings: In a fourth dimension, a four-dimensional being could be able to see a moment in multiple states. This would explain quantum superposition, as a four-dimensional being could see a quantum particle in all its possible states at the same time.
- Inconsistencies with the macroscopic world: The properties of the quantum world are often inconsistent with those of the macroscopic world. This suggests that the quantum world is subject to different laws, which could be explained by the existence of a fourth dimension.
Arguments against:
- Lack of experimental evidence: There is no direct experimental evidence for the existence of a fourth dimension.
- Speculation: The idea that the fourth dimension is the key to understanding the quantum world is a speculation.
Keywords:
- Fourth dimension
- Quantum world
- Superposition
- Shadow
- Beings of four dimensions
- Experiments
- Quantum laws
- Controversy
Abaqus can be used to calibrate material data. To do this, you need experimental data and a simulation of the experimental set-up. Experimental and simulated results are then compared to determine how good the fit is. If the fit is not satisfying, the material properties are modified and the simulation is rerun, trying to obtain a better fit. This can be done manually, but it is labour intensive. So I am trying to automate this optimisation in Python for my summer undergraduate research project.
The attached file is the logic flow chart showing the summary of needs to be done.
I am trying to compare simulated data to experimental data and match them by adjusting Johnson-Cook material parameters (A, B, C, n , m).
So far I have been using GEKKO optimisation module in Python. The Python file is also attached to this question. Last time, the code worked for a stress-strain data for another material and the problem was in units of data.
Currently, I am using force-displacement data which is stored in the attached .txt files (force_2 and displ_02). The attached image is the result of running the code.
Could anyone help me to find a problem in either my logic or my code,please? Is the problem in values of parameters and force-displacement data?

Hello,
I would like to know what should be the magnitude of displacement in abaqus in order to simulate experimental tensile test on mild steel and verify the stress/strain values?
I tried using the displacement magnitude as 1 but I am unable to reach the desired strain at the end increment.
My data line for boundary condition is,
*BOUNDARY,OP=MOD,TYPE=DISPLACEMENT
TOPP,2,2,1
Note: TOPP - Node set and its a non-linear problem with plasticity defined
Any sort of help will be appreciated.
Thanks!
What are the available tools for conducting simulation experimentation on natural fiber composites?
Hi, I wanna ask for opinions/suggestions to reduce the percentage error between experimental and simulation results in the ANSYS workbench ( static structural).
First, let me explain my research.
I have cubic lattice structure samples (60mm x 60 mm x 60 mm) made from ABS thermoplastic material using FDM additive manufacturing. These samples were compressed using INSTRON 5585 universal compression test machine. The data from the test were analyzed to get the stiffness, young modulus, yield stress, etc. However, the results from simulation using ANSYS static structural were nowhere near the experimental results. For example, to get the stiffness, I divided the exerted force to the deformation and I get +82% error (simulation >> experimental). for young modulus, I divided the equivalent stress to strain and get -234% error (simulation >> experimental). I suspect these as the factors for the error
1. The samples made from FDM AM have too many manufacturing defects (interlayer failure+ porosity), yet to try using other AM techniques.
2. During the experiment, the area used was 60 mm x 60 mm as I cannot specify exactly the contact area (much less contact area) for the lattice to the bottom platen as the machine only asked me to put in the width and length of the sample. where probably (I'm not sure) the area used in the calculation in ANSYS is the actual contact area to bottom platen.
3. The structure is simply too complex.
I've tried using actual density and young modulus I get from experimental in engineering data and use force distribution plate to the top and bottom of the samples in ANSYS environment but not much changes.
also for case #1 is there any way I can render the geometry in ANSYS to have layers and voids as in actual samples?

For an interaction study, what would be the ideal temperature range for REMD simulation? Is 300 - 350 range having close to 55 replicas be too short a range to consider this under Replica exchange MD?
I am working decision making in social robotics using reinforcement learning. Regarding that real world scenarios usually do not provide the necessary reproducibility for experiments, i am looking for a simulation environment and benckmarking. Thanks in advance.
Dear Colleagues,
As Guest Editor I have a great pleasure to invite you to submit papers to the Special Issue "Additive Manufacturing of Cellular Structures Based on Metal Materials" in MDPI Metals, IF: 2.259. The main aim of this Special Issue is to publish scientific papers covering the recent problems related to the additive manufacturing of 2D and 3D regular cellular structures using metal materials, including the following:
mechanical behavior in terms of energy-absorption and crashworthiness capabilities;
- experimental testing under quasi-static and dynamic conditions;
- numerical modelling and simulation coupled with experimental tests;
- microscopic studies of additively manufactured materials;
- fracture and damage under low and high strain rates;
- and others...
Keywords
- additive manufacturing
- regular cellular structure
- energy absorption
- numerical simulation
- experimental testing
- behavior of material
- fracture
- damage
For more information please go here:
Looking forward for your submitted papers!:)
Dr. Paweł Baranowski
Guest Editor
Hello everyone, i am trying to simulate experimental load-deflection curve of a reinforced concrete beam from literature with an analytical procedure using strain compatibility method.
I assume an initial strain at the extreme compression fibre of the RC beam and with the help of similar triangle concepts corresponding stress,strain in rebar, concrete bottom layer will be evaluated, moment and load are calculated using obtained stress multiplied by corresponding lever arm. The deflections are calculated by Branson's equation. My problem is that analytically obtained load-deflection curves does not match with the experimental curve available in the literature as seen in the attached picture. What could have been possibly gone wrong?
Can someone please help me?
Thank you in advance.
Best Regards
Naveen

Hi everyone, hope you all are having wonderful day.
I am working on a baby inverse problem. I have a simple nonlinear model. To estimate the model parameters I can obtain two different sets of simulated experimental data (inverse problem crime) in the following ways:
Set 1. Experimental data obtained from 2^k factorial design.
Set 2. Experimental data obtained from one extreme corner of the 2^k factorial design.
Interestingly, when I estimated parameters from these two data sets, I get better estimates when Set 2 was used. I thought that if the model is in good condition (without ill-posedness), using more experimental data should result in better estimates. My performance criteria is how close parameter estimates are to their assumed true values. Do you have any idea why I am seeing this behavior?
Is there any inherent limitation in FDTD (as implemented by Remcom X-Fdtd or CST) that might preclude it from solving for certain electromagnetic wave modes? Specifically, I'm trying to simulate an experimental structure where we are measuring a surface wave in a lossy dielectric, but the X-fdtd model does not show the measured behavior.
Dear all,
I hope someone help me ,i made a model by abacus of expansive soil to evaluate the influence zone of pressurize water injection in the expansive soil to determine the best place of stabilizer.now i want to make calibration between my simulation and the experimental result .my properities is (density soroption moisture swelling permeability and mohr colomb),could someone help please
While reading the literature most of papers are based on these words.Normally these words are quoted to check the effectiveness of proposed method. What is the actual difference between these?Does online means your experiments are based on real time studies?
Usually, for a damped lumped mass system, the accurate FRFs can be obtained easily. And the simulated experimental FRFs data contaminated with noise can be obtained by adding a random noise to the impulse response functions, which are then transformed back to the frequency domain. For systems with structural damping models, the impulse response functions may be unreasonable, so I want to add noise to the accurate FRFs directly to obtain the simulated experimental data.The question is how I can make it?
I remember i saw such kind of theory somewhere but can't find it anywhere now.
Is there any method (optimization) for time delay change between the time of the sample collection and when it is assessed/examined?
I am trying to create a simulation for an experiment that already has been conducted. I will then compare the obtained results with the data from the experiment. The experiment involved a 3m tall square tank full of soil, and a fragment of pipe burried 2m in it. This pipe has been then slowly pushed and pulled sideways by 4 actuators that were set to displace it for a curtain distance (e.g. 30cm) in 5 cycles back and forth. The output values were the forces on the pipe and the forces on the walls of tank that comes from soil. Is it possible to simulate this in Plaxis 2D? with the input data = displacement, and try and obtain forces on pipe.
I need to gather the diminishing wave graphs of water ripples (height over time), as caused by a water droplet or other central disturbance, in a circular tank of water. The points I'd measure would be along an arbitrary line that originates at the center and goes to an edge of the tank (because I'm assuming the central disturbance will generate circularly symmetric waves). How could I gather the data necessary to generate the diminishing wave graphs at each point? Using bobbers/floats and aiming a high-speed camera perpendicular to the water's surface with a grade scale behind the clear tank won't work because the bobbers/floats likely would move freely around in the tank and not stay still. I only want them to move up and down--to measure the height of the surface of the water as it ripples. Would multiple lasers be able to detect the water's height?
Alternatively, if there is a (preferably free) software that can simulate simple ripples and generate the needed data, I would gladly be open to that route.
Any help on this issue would be greatly appreciated! Thank you.
I am doing an experiment of damper which is made of soft steel, the damper has the characteristic of complex-damping, the Hysteresis curve of experiment is perfect,but when I use abaqus to simulate experiment, the Hysteresis curve I got has Bauschinger effect, but it not appeared in experiment, how should I set property of damper in abaqus to avoid Bauschinger effect?
The style of steel in experiment is Q195
The parameters I set in abaqus:
young`s modulus: 210000, poission`s ratio: 0.3
Yeild stress:250 ,Plastic strain:0
The comparison of Hysteresis curves I plot in the picture below, to understand my question more. Thanks for your answer

Hello,
I am simulating Wakefields/impedances of some accelerator components like taper transitions, cavity like structures and some others. I heard that indirect test beam method yields more accurate result than direct one. Is it true? If so, how can I simulate more accurately the wakefields produced by tapered structure? Can I add some PEC material at both ends to make cavity like structure?
The manual says if the cross sections at both ends are same we should be able to use indirect test beam method however in some cases, I could not use indirect test beam method though their cross section where the beam enters and leaves are same (see the following screen shot image).
Would you mind sharing your views based on your simulation experience about these issues? Thank you in advance for your answer.

Hi evryone, I want to ask where can I find " Uncapacitated Facility Location Problem " pseudo-code.
Is there any Library of Simulation Experiments or Datasets like for constrained and unconstrained optimization test functions ? Otherwise, any documentation to start with ?
I want to make combustion model of HCNG Engine then how I would start the combustion modelling
I have few questions if any one can add to it:
1. I want to run a simulation with experiments done in free surface water tunnel. Which model you think can predict good reattachment length.
2. I am using turbulent length scale 6mm and turbulent intensity of 5%. If the reattachment length is not close which parameter should i adjust.
3. I am using 0 pressure gauge as outlet boundary condition. However experiment was conducted in close recirculating water tunnel. Is it correct? or should i use outflow as boundary conditions.
Thanks
Looking forward to hear from you soon.
Hi everyone i have do some optical measurement which shows me a particle which is of 900 nm when i have performed SEM with higher magnification then i amazed that it was not a single particle instead it is the sum of the particles. now i have spent a lot of time on the simulation and experiment things the particle look like as in figure attached. i want to get the scattering near field.Now if i have to draw this type of figure in the FDTD software or FEM software like comsol can i get still right response there are about 20 particles are inside it.. Please suggest me your suggestions are really useful for me at this time. kindly if you have literature then also please suggest.i will appreciate that.thanks

I am having a problem getting my solution to converge.
- I have a tank with oil in it, and a heater in the center, the temperature difference causes natural convection flow within the tank. I am trying to simulate this experiment using FLUENT. I am fairly certain I set up the boundary conditions correctly, and my mesh seems OK. It was converging (excruciatingly slowly) but at least it was. Then it seemed to get "stuck" before reaching the convergence criteria. So I tried many different ways to get it un-stuck . All I have succeeded in doing is cause it to start to diverge again. I need some serious help. Can someone point me in the right direction please?
I would like to measure the performance and observe the pattern of I/O interactions between VM and SAN. Anyone can suggest any tools/simulators or experiment based for me to study. I'm not sure whether CloudSim can do simulation for SAN
Thank you
I am using witness to simulate a production line... I wish to do ten times replications with wotness experimenter... anypne could help ?
Would reproduce this experiment numerically to observe the turbulent behavior of the ink
I want to design some simulation-based scenarios involving students from different health care disciplines, and also assess the effectiveness of interprofessional simulation experience on student's learning.
Would you like to share some suggestions about the whole process (design, implementation, and assessment)?
Normally, the environment of a quantum system could be supposed to be a thermal state, or a squeezed vacuum state or a squeezed thermal state. Then can these baths be realized or simulated in experiments?