Science topics: PhysicsAcoustics
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# Acoustics - Science topic

Acoustics is the interdisciplinary science that deals with the study of all mechanical waves in gases, liquids, and solids including vibration, sound, ultrasound and infrasound.
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Dear ResearchGate members,
On one hand, there is a theory giving the reflection/transmission coefficients when acoustic planes waves propagating in a medium (rho0, c0) reach a finite thickness object (rho1, c1) with normal incidence. Such theory basically gives the thicknesses (n*lambda1/2) at which the object is theoretically acoustically transparent - of course, the width of the reduced reflection depends on the impedance mismatch between the 2 media – and the thicknesses ([2n-1]*lambda1/4) at which the object is fully reflective.
On the other hand, there is also theory giving the variation of the reflection coefficient depending on the incident angle of acoustic plane waves at the interface between two semi-infinite media (rho0, c0; rho1, c1). Over a critical angle (depending on the impedance mismatch between the two media), the reflection is theoretically total.
Now, here is my question: What is the behavior of the acoustic waves when the two phenomena are considered at the same time? If the plane waves reach a surface with an incident angle, and the reflective medium is finite in thickness (acoustic mirror)?
By experience and through simulations, it appears that over the critical angle, the reflection is not total, even with a mirror thickness for which the reflection is theoretically total.
The second part of your question was too complex. I submitted some supplemental info.
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I’m currently in the process of selecting a research topic for my doctoral studies. I have a keen interest in the field of acoustic metamaterials. I would really appreciate if you are helping me to provide your expertise and suggestion to select the topics in the field of acoustic metamaterials
Here's another list for you Mk Karthi .
1. Adaptive Acoustic Cloaking: Investigate the development of adaptive acoustic cloaking devices capable of real-time response to changing acoustic conditions. Explore applications in sonar technology and materials science for enhanced stealth capabilities.
2. Metamaterials for Urban Noise Mitigation: Research acoustic metamaterials designed to reduce noise pollution in urban environments. Focus on sound-absorbing and deflecting structures to enhance acoustic comfort and urban sustainability.
3. Quantum Acoustics with Metamaterials: Explore the use of metamaterials in the emerging field of quantum acoustics. Investigate how metamaterials can manipulate quantum acoustic phenomena, potentially leading to advancements in quantum information processing.
4. Advanced Ultrasound Imaging with Metamaterials: Develop acoustic metamaterials to improve ultrasound imaging resolution and depth. Investigate the design of acoustic lenses and sensors for enhanced medical diagnostics and healthcare applications.
5. Underwater Acoustic Exploration: Pioneer the use of acoustic metamaterials for underwater exploration, including improved sonar and underwater communication systems. Explore applications in marine research and defense technology.
6. Acoustic Solutions for Space: Research the application of acoustic metamaterials in space habitats and spacecraft to address noise and vibration challenges. Enhance the acoustic environment for astronauts during space missions.
7. Bio-Inspired Acoustic Metamaterials: Draw inspiration from natural structures to create bio-inspired acoustic metamaterials. Investigate their potential for advanced sensors, biomimetic materials, and underwater communication systems.
8. Acoustic Energy Harvesting: Explore the development of acoustic metamaterials for energy harvesting, converting acoustic energy into electricity. Investigate applications for sustainable power generation in remote or off-grid areas.
9. Quantum-Secure Acoustic Communication: Research quantum-secure acoustic communication networks using metamaterials. Explore the potential for unbreakable acoustic encryption methods with applications in secure communication.
10. Metamaterials in Extreme Environments: Develop metamaterials for use in extreme environments, such as deep-sea exploration, space travel, or industrial settings with high temperatures and pressures. Investigate their resilience and adaptability.
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Dear expert,
How to do Distributed Acoustic Sensing for MASW purpose, if it can be done can the geophone planted on surface in vertical, for subsurface imaging ?
Really appreciate if it can be done?
Mel,
Distributed Acoustic Sensing (DAS) can indeed be used for the Multichannel Analysis of Surface Waves (MASW) purpose, and it offers a unique and versatile approach to seismic data acquisition. Typically, DAS utilizes a fiber optic cable as a distributed sensor to capture ground motion along its entire length. However, using traditional geophones planted on the surface in a vertical arrangement may not be the most effective way to complement DAS for MASW. Here's how you can effectively use DAS for MASW:
1. Fiber Optic Cable Installation:
• Install a fiber optic cable along the surface or in a borehole at the site of interest. The choice between surface and borehole installation depends on your specific objectives, geological conditions, and depth of investigation.
2. DAS Interrogation System:
• Connect the fiber optic cable to a DAS interrogation system. DAS works by sending laser pulses down the fiber and measuring the backscattered light to detect acoustic signals.
3. Seismic Source:
• Generate seismic waves using appropriate sources, such as a sledgehammer impact, a seismic vibrator, or a controlled explosive source. These sources create ground motion that interacts with subsurface geological layers.
4. DAS Data Acquisition:
• The DAS system continuously records ground motion along the entire length of the fiber optic cable in real-time as the seismic waves propagate.
5. Data Processing:
• Process the acquired DAS data to extract dispersion curves. Dispersion curves provide valuable information about the shear wave velocity as a function of depth, which is the primary goal of a MASW survey.
6. Inversion:
• Invert the dispersion curves to obtain a shear wave velocity profile of the subsurface. This profile aids in characterizing geological layers and assessing geotechnical properties.
Advantages of Using DAS for MASW:
• Continuous sensor coverage along the entire length of the fiber optic cable allows for high-resolution data collection.
• DAS can be deployed in various environments, including boreholes, which can be beneficial for deeper subsurface imaging.
• It offers real-time data acquisition and the ability to capture subtle seismic signals effectively.
Considerations:
• The choice between surface installation and borehole deployment of the fiber optic cable depends on site-specific conditions and survey objectives. Borehole deployment is often preferred for deeper investigations.
• Ensure proper calibration and validation of the DAS system to obtain accurate and reliable results.
• DAS for MASW requires careful planning, execution, and data processing to achieve meaningful subsurface imaging.
While DAS is a powerful tool for MASW surveys, the use of traditional geophones in a vertical arrangement on the surface may not be necessary in this context. DAS alone can provide comprehensive and high-resolution data for MASW purposes, making the additional use of geophones less common in such applications. However, the choice between DAS installation on the surface or in boreholes should be guided by the specific requirements of your project.
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In general, it is difficult to effectively divide the difference between tuff and dacite by natural gamma curve and acoustic time difference curve in some work areas, and both show low GR value and low DT value.
I wish I could help. Here's a shot in the dark:
Problem Statement:
The task is to effectively differentiate between tuff and dacite formations in work areas where both formations exhibit low GR (Gamma Ray) values and low DT (Acoustic Time Difference) values using well log data, specifically the natural gamma curve and acoustic time difference curve.
Solution Steps:
1. Data Collection and Preparation:
- Gather calibrated well log data, including natural gamma curve and acoustic time difference curve measurements.
2. Data Visualization and Analysis:
- Plot the well log data to identify depth intervals with low GR and DT values.
3. Statistical Analysis:
- Calculate mean, median, and standard deviation for both GR and DT curves in these depth intervals.
4. Threshold Determination:
- Set threshold values for GR and DT based on statistical analysis.
5. Formation Classification:
- Develop a classification algorithm to categorize formations as tuff or dacite.
6. Validation and Refinement:
- Validate results using core samples or nearby wells, refine the classification algorithm if needed.
7. Mapping and Visualization:
- Generate lithology maps using classified data.
8. Integration with Geological Models:
- Integrate classifications with geological models.
9. Documentation and Reporting:
- Document methodology, data sources, thresholds, and results.
10. Continuous Monitoring:
- Implement monitoring for changes in lithology.
References:
1. "Well Logging and Formation Evaluation" by Toby Darling
2. "Pattern Recognition and Machine Learning" by Christopher M. Bishop
3. Geological Society of America (GSA) Bulletin
4. "Introduction to Well Logs and Subsurface Maps" by Jonathan C. Evenick
5. "Geological Interpretation of Well Logs" by Malcolm Rider
6. "Log Analysis Handbook" by E. R. Crain
7. "Geological Well Logs: Their Use in Reservoir Modeling" by Mark S. Fayers
8. "The Log Analysis Handbook: A Comprehensive Guide to the Science of Log Analysis" by Oberto Serra
9. "Geostatistics for Natural Resources Evaluation" by Pierre Goovaerts
10. "Geostatistics: Modeling Spatial Uncertainty" by Jean-Paul Chilès and Pierre Delfiner
11. "Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy
12. "Petroleum Geoscience" by Jon Gluyas and Richard Swarbrick
13. "Introduction to Artificial Intelligence" by Wolfgang Ertel
14. "Introduction to Geological Data Analysis" by Gareth Shaw
15. "Geological Methods in Mineral Exploration and Mining" by Roger Marjoribanks
These additional references cover various aspects of well log analysis, geological interpretation, machine learning, and geostatistics, providing a comprehensive resource list for tackling the problem effectively.
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It is well-known from the literature that there exist diverse acoustic waves in compact astrophysical objects, such as white dwarfs, neutron stars, etc. Can anyone please give us a concise glimpse of the state-of-the-art astronomical observations of such existent acoustic wave spectra?
Individual viewpoints may please be put forward as per the above request
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As the eigen room modes of a room are complex. So How to remove the complex eigen modes? Is there a way to remove the acoustic damping by air in SOLVER SETTING?
#COMSOL #ROOM ACOUSTIC
Raja Kumar Can you share the finite element of the room in an appropriate ASCII format?
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We have observed in literature regarding the optical mode and acoustic mode in FMR spectra.
How to identify which one is acoustic and which one is optical?
Kindly clarify.
In case of two coupled FM layers magnetized in-plane: For positive (FM-like) coupling, optical mode has higher resonant frequency, for negative (AFM-like) coupling, it is acoustic one which is higher in frequency.
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It seems to me that everyone just refers to J. W. Goodman's book "Speckle phenomena in optics: Theory and Applications". I agree this is a good book, however in my opinion there are some differences in ultrasound.
I would like to find answers to the questions:
- how realistic is it to assume that the ultrasound signal has a single spectral component (monochromatic light assumption in Goodman)? Is this assumption required?
- what is the effect of ultrasound transducer and the transformation from pressure to RF signal?
Not recent but ...
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Hi All,
I wonder how I can use infinite elements in CEL (Coupled Eulerian-Lagrangian) models in Abaqus to absorb waves at the boundaries of the soil domain. The only available element type in CEL is EC3D8R (Eulerian hexahedral 3D elements with Reduced integration) and acoustic or infinite elements are not available. As an alternative, I created a non-Eulerian (deformable) part, tied it to the Eulerian part, and intended to assign infinite elements to this (non-Eulerian) part in the input file. However, I encountered an error that "Eulerian elements can not be tied to non-Eulerian elements".
Thank you very much.
Pourya
Hi Pourya,
In Abaqus, infinite elements cannot be directly combined with Eulerian (CEL) elements. However, there are alternative approaches you can use to simulate wave propagation and absorption at the boundaries of your soil domain in a CEL model.
One such approach is to implement a non-reflecting boundary condition using a user subroutine. The following steps outline a possible procedure:
1. Create a user-defined boundary condition to simulate non-reflecting boundaries:
• To implement this, you'll need to write a user-defined subroutine in Abaqus using FORTRAN. The subroutine should be designed to calculate the appropriate boundary conditions at the edges of your soil domain to minimize wave reflections.
• Set up your CEL model in Abaqus/CAE as usual.
• Ensure that the boundaries of the soil domain where you want to minimize wave reflection are properly meshed and defined.
1. Assign the user-defined boundary condition:
• In the Abaqus input file, use the *USER DEFINED FIELD option to call the user subroutine you have written. This will apply the non-reflecting boundary condition at the specified soil domain boundaries.
1. Run the simulation:
• Execute the analysis in Abaqus, making sure to specify the appropriate user subroutine with the 'user' keyword.
It's important to note that writing and implementing user subroutines in Abaqus may require some experience with FORTRAN programming and a solid understanding of the problem at hand. If you're not familiar with this, you may want to seek the help of someone with experience in writing Abaqus subroutines.
Additionally, keep in mind that this approach may not be as efficient as using infinite elements, but it should provide a reasonable approximation of wave absorption at the boundaries of your Eulerian soil domain.
I hope this helps!
Best regards,
Alessandro
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discussing about sand monitoring on deep water subsea wells, is there any threshold that we can refer to when we read ASD (Acoustic Sand Detector)?
when we can saya that the value reading is representing sand or representing the fluid flow?
thanks and please correct me if there is anything wrong with my appellation
Sorry for the delay in response. When monitoring sand in deep water subsea wells using an Acoustic Sand Detector (ASD), there are a few threshold values that can be used to indicate the presence of sand versus fluid flow. However, it's important to note that these thresholds may vary depending on the specific well conditions and the type of ASD being used.
Generally, an ASD will produce an output signal that represents the amplitude of the acoustic signal reflected from the wellbore. When sand is present in the fluid flow, it can cause a higher amplitude signal due to the reflection of acoustic waves from the sand particles. This signal can be analyzed to determine the amount and size distribution of sand particles present.
One threshold that can be used is the Sand Rate Threshold, which is the amplitude level at which the ASD output signal is considered to represent sand flow rather than fluid flow. This threshold value can vary depending on the specific ASD used, the well conditions, and the desired sensitivity of the sand monitoring system.
Another threshold that can be used is the Sand Alarm Threshold, which is a higher amplitude level at which an alarm signal is triggered to alert operators of high sand production rates. This threshold value is typically set based on the maximum acceptable sand production rate for the well, and can also vary depending on the specific well conditions and ASD being used.
It's important to note that these threshold values are not fixed and may need to be adjusted over time as the well conditions change. Additionally, it's important to have a good understanding of the specific ASD being used and its limitations to accurately interpret the output signals and make informed decisions about sand production rates in deep water subsea wells.
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• Isotropic metals in a stress free state have a stiffness matrix. Under the action of prestress, an equivalent stiffness matrix containing the third order elastic constants l, m, n can be established based on the acoustic elastic effect. Its acoustic elastic constants in the natural coordinate system are shown below. I wonder if these formulas are correct? Where can I find the formulas for these coefficients
The formula is as follows
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Specific: frequency or time domain? acoustic or elastic media? with attenuation or without? using CPUs or GPUs? ... ...
I find that multiparameter FWI from DUG is now commercialized. Then, you can use it to simultaneously estimate multiple parameters. Check this paper: https://doi.org/10.1190/tle42010034.1
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The results of our research determined for the first time that for the entire frequency range of acoustic waves, the range of their propagation, measured not in units of measurement of distance, but in cycles, is a constant: the same number of cycles corresponds to the same absorption of acoustic energy. Due to the difference in the lengths of acoustic waves, the range of sound propagation is determined by the wavelength, which for the conditions of the practical absence of sound dispersion in water, has a statistical relationship with the wave frequency. Due to this, the researchers got the wrong impression about the dependence of the sound propagation distance on the frequency. But the presence of correlation in this case is not related to the presence of a cause-and-effect relationship between the frequency of acoustic waves and their propagation distance. Thus, for the first time, the basis for a complete rethinking of the theory of the process of absorbing the energy of acoustic waves in water is presented.
It should be noted that there are signs that the obtained regularity can be extended to transverse waves in water. This is evidenced by the fact that, unlike shorter wind waves, long ocean surface (transverse) waves of "surge" spread over a distance of more than 1000 km. Tsunami waves, which have a length greater than the length of "Zibu" waves, spread over a distance of tens of thousands of kilometers. Seismic waves that propagate in the solid shell of the Earth, at lengths close to the length of tsunami waves, also propagate for tens of thousands of kilometers. In the future, different types of waves propagating in different environments can be considered, which does not exclude the possibility of confirming the general (universal) physically justified and understandable regularity of wave attenuation put forward by us.
Howdy Borys Kapochkin,
My wife told me about the joy/sorrow event of an earthquake close to home there. Nature is unaware of kindness ~Tao Te Ching. You may enjoy learning while you experience sorrow: survivors in centuries to come will benefit from what you learn by study of the current events that are tragic for today's casualties .
I had been concerned about the emphasis that developed in this thread on pressure that does enhance evaporation, since it is only a small effect, while "that lucky old sun" is far more important in supplying energy for the molecular unrest. When you again have time for evaporation it will be good to feel the energy in the molecular unrest without undue emphasis on pressure. Just a thought for future discussion.
Happy Trails, with sympathy for unhappy experiences, Len
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Recently, I want to study the acoustoelastic effect of Lamb wave in composites, and use this property to measure the stress of carbon fiber reinforced composite T300/QY8911. The third order elastic modulus parameters of materials are required for the acoustic elastodynamics modeling. However, I only found the relevant parameters of T300/5208 in the paper, and did not find any relevant parameters of T300/QY8911. I wonder if anyone knows these parameters and would like to share them, I would appreciate it!
Harold Berjamin "The effect of applied stress on the phase and group velocity of guided waves in anisotropic plates". It was in this paper that I discovered the third-order elastic constant of T300/5208. In fact, I need the third order elastic constants in order to build the stress measurement model based on the Lamb wave acoustoelastic effect. Because the acoustoelastic effect of Lamb wave has the dispersive and multi-modal characteristics, it is necessary to select the optimized mode-frequency combination to achieve a better measurement effect. Moreover, the consistency between experimental and theoretical analysis results can better illustrate the accuracy of the measurement method.
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Hi all,
Is there any tutorial on acoustic Fresnel lens simulation in COMSOL? I want to start the simulation of the fresnel lens in COMSOL.
Unfortunately not in my field of expertise. My main expertise is in Acoustics relating to assessment and prediction of environmental and building acoustics and the same for ground borne vibration. You have presumably done an online search on Google for this topic?
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I am working on a project in which I need to analyse acoustic data taken from voice recordings of a person in different rooms. I wanted to know if there are any parameters that are independent of the environment and therefore do not change by changing the room setting (e.g. standard deviation of acoustic pitches). Also, I would like some reference if you have.
many thanks!
it depends on purpose of your acoustic analysis or method used i guess.
If you are trying analyze voice of the speaker, then ceptral measures may remain constant( CPP) or HNR as well. F0 may remain similar, but other parameter such as jitter and shimmer may be influenced by noise and revrbration of the room.
If it is speech of speaker is the focus of analysis, then intonation pattern , no of pauses, may remain unaffected by room changes.
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I wish to perform acoustic phonetic analysis of Oral and Nasal vowel phones in a language. I am aware of F1-F2 plot helps in plotting oral vowel phones, but having the confusion of same can be used for nasal vowels. Please suggest me some good reading materials related to acoustic phonetic study of nasal vowels.
you can read articles published on acoustic analysis of children with cleft palate by different authors. formant freq is just one of features important for characterizing nasal vowels. bandwidth, amplitude and antiresonance features etc..are also need to be considered.
2. Chen MY. Acoustic correlates of English and French nasalized vowels. J Acoust Soc Am. 1997 Oct;102(4):2360-70. doi: 10.1121/1.419620. PMID: 9348695.
book : Speech Science Primer: Physiology, Acoustics, and Perception of Speech
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Acoustic inside the mosque is affected by different creteria such as form, space design , material, insulations, AC,...
What do you think?
yes , there are tests of hearing that are routinely done to detect changes in hearing thresholds when a subject is exposed to loud level of noise for a prolonged period of time.
1. Pure tone audiogram is a basic evaluation which can show some typical changes ( 4Khz notch)if some one is exposed hazardous level of noise
2. high frequency extended audiometry is important when exposure is recent. Effect on hearing maynot be that much. So High freq audiometry is an early warning sign
3. OAE- otoacoustic emissions are sensitive test of inner ears. Any changes , temporary or permanent can be pickedup early on , On this test.
Again like many opined here, duration of exposure is important factor along with frequency of sound and level of sound. For continuous noises like machinery noise / music, there is an occupational hearing health standards.
if noise level is 90dB and exposure is 8hrs/ day for 5 days a week then it can be damaging. levels of sound lower than 80dB are generally not considered hazardous.
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Dear Researchers,
I am looking into deriving the particle displacement for pressure acoustics in the frequency domain or transient domain. If I solve a acoustics problem in comsol I get the pressurefield and derived variables like acoustics velocity and acoustic acceleration. How could I derive acoustic displacment from these variables. Displacement is the Timeintegral of velocity and in simple cases It is easy to derive the displacement, but in more complex cases I am lost onto how to solve for particle displacement.
Can anyone pont me in the right direction?
That is right, there are as well analytical equations like u = a/omega^2 or u = v/omega. Unfortuntely this only holds true for a plane wave, as i assume your is with you reflection theorie.
I would like to find a way, to derive particle displacement in every FE solution, which does seem to be alot more difficult.
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Conceptually, as well as source of wave propagation and wave equation
In an unbounded solid, there are two types of elastic waves: 1) dilatational (longitudinal waves), and 2) distortional (transverse waves); the distortional waves arise because solids can support shear, which true liquids and gases cannot support. In a bounded solid, the surface is subjected to Rayleigh waves (surface waves). Rayleigh waves are similar - but not identical - to gravity waves found at the surface of a bounded liquid.
[1] H. Kolsky; Stress Waves in Solids; Dover Publications, Inc.; 1963; pp. 4 & 16.
[2] Francis Weston Sears, Mark W. Zemansky; University Physics, Part 1 - Mechanics, Heat, and Sound; Addison-Wesley Publishing Company, Inc.; 1963; pp. 488-491.
Regards,
Tom Cuff
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Dear RG community,
I'm starting a photoacoustic project, and I need to acquire some ultrasonic receivers.
Acoustics is not my expertise, so I'm asking here for help! :D
Where to buy, what is the price range, and what to pay attention to?
Take a look at acoustic sensors based on piezo-polymer such as pvdf film. We produced such sensors\transducers with wideband spectral range 0.1-15 MHz and it works fine for high precision photo/optoacoustical mesurements. But unfortunately can't provide any information where to buy one
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I am looking for the maximum bit rate for underwater acoustic communication and communication distance. Please suggest to me some related papers.
Depends on the characteristics in the subsea environment etc. generally, in a short distance channel (tens/hundreds of metres) you can get tens of kb/sec maximum depending on the system, in a long distance channel (several km) it diminishes down accordingly.
There are research papers studying acoustic MIMO systems that are looking to improve this.
M. Stojanovic has numerous papers in this field, I refer to her works regularly myself.
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Microphone array is heavily used in acoustical techniques such as detection, DOA, target tracking and so on. I'm wondering if there is a user-friendly code or toolbox that can be used for demos in the classroom for an acoustic course for master/bachelor students.
I and my undergrad student put together a list with several toolboxes at this address:
Matlab and Python based.
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We've recently been investigating alternatives to glass/plastic particles for Acoustic Doppler Velocimeter seeding material that can be disposed of without environmental concerns and are less costly. One alternative we have tried is kaolin clay, which has seemed to be quite effective in initial tests. I was wondering whether anyone else has experience using this or if there are any other alternatives that we should consider?
Hello everyone, I'm sorry I don't have an answer. But since this thread is related to flow visualization, I would like to let you know that we've started a Flow visualization Stack exchange forum. We are building a community currently. Once we have 60 people we will be allowed to proceed to a private beta version of the forum. Please join us if you are interested in flow vis and have questions to ask. Here's the link: https://area51.stackexchange.com/proposals/127312/flow-visualization?referrer=NTJlZjIyYzI3Zjk4N2I1NDZmMTJhZDUxMTViODcwMWUyNTM4OTI1YTU1OTYxN2ZkNDcwY2U2ZWI5NmU2OTY5OGhTtnNa4jEjFBFgB4o_K-u-LTdCqWX8yd8vul6HHcUb0
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explain to me the parameters that can influence the acoustic and elastic properties of materials
The elastic properties are described by the youngs moduluses, the density, the poissons ratios and any twisting moduluses (G-modules), as well as the damping. Harder materials have higher moduluses and tend to have lower damping, but not necessarily.
Next, the geometry of the material play an important role, as well as the boundary conditions. Eg a thicker plate will be more bending stiff. It vibrational mode shapes depend on the boundary conditions. Free free, simply supported edges, clamped edges, or combinations of these. The resulting damping will depend on the boundary conditions too, as in general damping is mode shape dependant.
If the material is isotropic the description becomes simpler. For ortotropic plates eg more elastic parameters and direction dependant damping may occur, as for wood or wood composite plates.
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I have studied the literature and found that combining a Helmholtz resonator and membrane results in a negative effective mass density and a negative effective bulk modulus. Typically, in double negative acoustic metamaterials, we find two resonant frequencies, one due to the Helmholtz resonator and one due to the membrane. Is there any possibility that we get only one resonant frequency in double negative acoustic metamaterials?
Well, you might imagine designing the membrane to have the same resonant frequency as the Helmholtz resonator; but I think that I would prefer to call that (e.g.) two degenerate resonant frequencies (due to their different underlying mechanisms); rather than to call it "one resonant frequency".
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I want to model a vibrating solid (ultrasonic horn) in liquid filled structure and observe the acoustic pressure field in the liquid.
I used solid mechanics (frequency domain) and laminar flow (stationary), but it didn't work.
I think it is because solid mechanics is frequency domain but fluid mechanics is not.
If I don't use fluid mechanics, I can't select the properties of the liquid.
Can I get some comments or examples?
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Can anyone recommend a usable resource/tool for species detection from acoustic data please? A middle ground between a phone app and something like Arbimon would be about the level. Briefly, a phone app lacks flexibility in data collection, i.e. it cant be left out all night or left running for long periods. However, Arbimon is not that useful to anyone below ecologist level, as it only tells the user what species is present if the user completes their own validation, i.e. the user has to identify all species themselves. I'm looking for something that can analyse data from an AudioMoth, uploaded by citizen scientist participants, and actually identify species.
Very interesting project.
I stumbled upon
There also are some other interesting findings when doing a google search for "training data animal sounds"
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I'm preparing a model related to the phenomenon of leak detection by acoustics in gas pipeline . The case is transient encountering injecting of an acoustic wave signals in the domain . After invistigation of results , i found that the results are mixed with reflected wave coming from the end of the pipe.So i need to eliminate the reflected waves by means of end condition that can absorbes all the reflected waves . NOTE (I already used perfect matched layer for frequancy steady state studies but it doesn't work with transient studies ) .
If you use Pipe Acoustics Transient Interface apply End Impedance and set zero reflection condition.
See COMSOL Documentation:
Acoustics Module > User's Guide > Pipe Acoustics Interfaces > The Pipe Acoustics Frequency Domain and Transient Interfaces > End Impedance
Good luck!
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Could anybody tell me the name for acoustic counterpart of RFID? Any references on that? Thank you!
Do you mean like "speaker recognition"? If so, wikipedia provides the following summary of methods:
"Speaker recognition is a pattern recognition problem. The various technologies used to process and store voice prints include frequency estimation, hidden Markov models, Gaussian mixture models, pattern matching algorithms, neural networks, matrix representation, vector quantization and decision trees. For comparing utterances against voice prints, more basic methods like cosine similarity are traditionally used for their simplicity and performance. Some systems also use "anti-speaker" techniques such as cohort models and world models. Spectral features are predominantly used in representing speaker characteristics. Linear predictive coding (LPC) is a speech coding method used in speaker recognition and speech verification".
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Dear RG specialists, I am wondering if is there a phase transition to a localized transversal phonon sort of coherent state? We know that there is one for the diffuse photon field when light scattering becomes strong enough (frozen light limit [1,2]).
This question arises only for transverse waves [3,4].
Following [1] Frozen light, Sajeev J. Nature volume 390, pp. 661–662, 1997:
Are there strong interference effects, due to the wave-like nature of transverse phonons, which severely obstruct their diffusion?
We already know that electrons & photons can be localized, please see the following articles & references therein:
The following research article is related to this thread:
Best Regards.
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I am required to make a report on the relation between the mechanical waves' domain and the Electromagnetic waves' domain.
I understand both are fundamentally independent of one another so I am confused of the request and willing to learn if there exists a direct relation (as in physics of the two waves) between the two types.
Dear Mohammed Helal,
There are some mechanisms of interaction of electromagnetic and acoustic waves. For example Acoustooptics and Optoacoustics effects. You can find the theory in Internet
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Sensor is designed for maximal temperature of 130°C, pipe surface depending on application reaches 200-450°C. The isolation pad must have satisfactory acoustic conductivity of ultrasonic signal in frequency range between 0,2 to 5 MHz. The isolating pad should be several mm thin. Maybe some kind of cooling layers in required dimensions could be used. Contact surface of the sensors is in dimesions up to 40x80 mm.
Dear colleague Miroslav Rusko, thank you for the information
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I have, as the outcome of data collection, three groups of music that have been used for different purposes. I have collected many different types of information about the individual pieces of music (pitch range, speed, acoustic properties, perceptual ratings of emotional content etc.) and I wish to determine what combination of these variables best explains the original grouping of the music. What statistical analysis method should I use? Thanks in advance.
شكرا جزيلا زميلي العزيز
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I am at loss how to start my acoustic analysis. In fact, I downloaded many softwares and none of them could serve the purpose.
Hello again, Farah. I see from your profile that your interest is primarily in phonetics. I am not a phonetics expert, but I know that Praat (https://www.fon.hum.uva.nl/praat/) is a very widely used package in this field, specifically designed for phonetic analysis, with a large set of features. It is free and open source and runs on most operating systems. Although it can be challenging to learn, there is an enormous amount of documentation online provided by the many users around the world.
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Hi,
I'm looking for a small (less than 0.5m of max length) underwater sound source to do some experimental measurements, any recommendations?
I'm looking for something robust and reliable but with prices ranging from lowcost to lab equipment.
All the best
Hello Rolf,
I plan to use it on an aquarium / lab during days, a couple of weeks maximum.
We were using this (https://dnhloudspeakers.com/loudspeakers/underwater/aqua-30-2/) during a time but didn't work very good and easily get broken when we use more than 100 dB. I'm looking for something similar but more durable.
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which is efficient model to generate band gaps for acoustic meta materials
The following RG link is also very useful:
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Hello,
I just want to discuss a few things about the non-reflecting boundary condition (NRBC) function in LS-DYNA. In fact, I am studying a fluid-structure interaction problem using LS-DYNA Finite element explicit code. My main interest is to study the propagation of shock wave as well as its interaction with the structure. So, I modelled the fluid part using solid acoustic elements (along with *MAT_ACOUSTIC) in LS-DYNA. Then, I applied the pressure to the fluid elements. But, the problem is that I cannot introduce both loading and boundary conditions (NRBC) on the same segment at the same time. It happened that the non-reflecting boundary condition that I introduced does not seem to be working.
So, I would like to know if there is any way to activate the non-reflecting boundary at a later time step different from the load application time (preferably at the end of my loading phase).
Thank you very much.
Regards
Ye Pyae Sone Oo
I am not sure but Restart analysis could work in your case. Define input parameter (dot_k) for the time limit up to the loading phase. Termination time should be equal to the time duration of the loading phase. After, normal termination you should have a dump file. Further, modify your dot_k file based on the requirement of non-reflecting surface and then do a Full restart analysis using earthe lier created dump file and modified input file.
I hope that this will work for you.
Thanks,
Suman
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As we know Maa et all have pioneered the theoretical calculations on Acoustics Impedance and Absorption by introducing the concept of micro-perforations. While preparing some theoretical predictions over the experimentally generated data many of the calculations in literature contradicts and seem a little confusing with imaginary terms and differential equations.
Are there any suggestions on some simplified calculations and methods that can be applied for theoretical modeling in MPP acoustics for the determination of Sound absorption Coeeficeint?
Dear Abhishek,
If I understand well your question, you are looking for a simple analytical model for the prediction of MPPs impedance.
Such model is given by Maa (1998) [ ], Eq. (5).
Note that the impedance is a complex number.
I hope that helps
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Experimental results of the Sound absorption coefficient of material have mostly been found to be in good terms with the Theoretical models. But the calculations look confusing. With imaginary terms and differential equations.
Are there any simplified calculations and methods for theoretical modeling in acoustics?
Regarding your question on the Nocke paper, Equation 6 is derived from the previous 5 equations. The numerical value of Equation 6 depends on the values chosen for the parameters b, d, t and D. If the system is linear, the impedance should not be dependent on sound pressure, so I am guessing that the p in the denominator should not be there.
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I am using 2 ultrasonic assembly for cleaning purpose and I want to increase cavitation intensity.
(1) a ceramic transducer with a diameter of 30 mm and a horn with a end diameter of 8 mm.
(2) a ceramic transducer with a diameter of 40 mm and a horn with a end diameter of 8 mm.
Since the input power of (2) is higher than that of (1), I expected that the sound pressure of (2) is higher than that of (1), but it was not.
I think it is because the acoustic impedance of (2) is much lower than that of (1) (even though the power is high, sound pressure can be lower since Z=p/v is lower).
1. Am I misunderstanding something??
2. If not, how to increase the acoustic impedance of the ultrasonic assembly??
3. How can I estimate the acoustic impedance of the ultrasonic assembly??
4. What is the best?? the acoustic impedance of the ultrasonic assembly should be equal to the acoustic impedance of the media (water in my case) or as high as possible?
However, If you look up matching layers in general, you will find that they are quarter wave (in the matching layer material) thick and of impedance (Zh*Zw)^.5, where Zh is the acoustic impedance of the horn material and Zw the acoustic impedance of the water (1.5 MRayls). Ideally, you should also have a matching layer from the transducer into the horn as well, same formula but using the impedances of the ceramic and horn material. The matching layer is designed for one frequency (where the matching layer is a quarter-wave thick) so will not help a lot for high bandwidth (very short) pulses.
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I think if the amplitude is large then the acoustic pressure also high.
I have tried to increase the acoustic pressure and use the ultrasonic booster which is known to increase amplitude.
But it did not work. The acoustic pressre measured by hydrophone was almost same as the acoustic pressure of the transducer without booster.
I am wondering
1. What is the relationship between the acoustic pressure and the amplitude.
2. What is the ultrasonic booster. Does it can increase the acoustic pressure??
I think you may find what you need on the website of the transducer manufacturer, who may have application notes about the use of transducers, or the website of the horn manufacturer. They may all be optimised for water, or IPA or MEBK.
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If yes, please indicate an example.
I am currently looking for the concept of Sezawa wave. And I find one review paper on Sezawa SAW devices ( ).
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i am doing thermal evaporation of pentacene and dntt polymer. just want to know the acoustic impeadence
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I am asking about how to find a formula for acoustic impedance for a porous wall with a variable thickness. The impedance is defined as a function of acoustic resistance (R) and acoustic reactance (X). The formula for the impedance is attached. In the case of having a wall of the same porous material, but the thickness is changing.
How the formula should be modified?
where,
R : acoustic resistance
X: acoustic reactance
X1: Mass coefficient
X2:cavity coefficient
w:frequency
Yes.
If you want to learn more about acoustic of porous media, you can refer to the book of Allard and Atalla, "Propagation of sound in porous media" or to the Matelys lab website https://apmr.matelys.com/
The propagation models are listed and explained in both references.
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Greetings! Looking for an advice on possible technical literature about specific subject: Influence of an acoustic waves on electronics and it's failure mechanics. If anyone is familiar with respectable source of information, please let me know. Thanks in advance!
Thomas Cuff , of course I am at liberty. But this is more general, than you think. For example, ballistic calculator in rifles upon shooting.
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I have two IDTs (interdigitated transducers) orthogonal to each other o a piezoelectric substrate. I want to know what happens when an RF signal is applied to both the IDTs at the same time. how to find out the orthogonal interference of two acoustic waves?
The article says that high intensity waves are non-linear. If waves are non-linear they interact with each other. If they are linear, then that do not interact with each other. This means that they each behave as if the other is not there.
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1) I would like to know how to choose the acoustic sum rule for phonon calculation in Quantum Espresso for polar materials and also for any materials in general.
2) Based on what criteria we have to choose the acoustic sum rule for a particular material under study.
3) I would also like to know the detailed theoretical explanation behind this.
Calculations using ASR help us to get rid from the first three mahipal negative frequencies which sometimes is because of the computational errors .
So there are many methods of ASR as implemented in quantum espresso like
asr ='simple'
asr= 'crystal'
In q2r.in and matdyn.in you can add these blocks and can compare the phonons for better understanding.
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The aim is to characterize a DAS instrument connected to a fiber optic cable.
what are the properties that I should look into ? white noise ? Dynamic range? SNR ?
I did some choc tests and I'm thinking on how should I calculate the SNR. Should I calculate a SNR for different frequency band ?
At any way statistically standard deviation can be used to refer for the root mean square value, of signal, then separate information signal from noisy signal by the means of signal processing to calculate SNR.
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I have to understand the use of green's function in acoustics . What does it signify ?
Dr. Utkarsh Chhibber, in addition to all the instructive & pedagogical answers to your thread, I would like to mention that in acoustics, the Green function method can be used also to study the time-reversal invariance problem.
Please look at this very instructive review article:
.../royalsocietypublishing.org/doi/10.1098/rsta.2015.0156
Best Regards.
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I want to optimize the placement of the sensors on a 3d terrain which is created in the arcmap.
I want to find the optimum no of sensors to be used on the terrain,
can you help me in the algorithm part.
Try to calculate the lighting and shadow zones from light sources placed at different points on the relief. Naturally, the light sources should be higher than the treetops. The situation is paradoxical in that the points that create the maximum illuminated area are located near the depressions of the relief, and not near the peaks.
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Acoustic field modelling, structure fluid coupled responses
I have a suggestion for you the Comsol Multiphysics to model the acoustic systems, it's a software wich based on finit element metod to solve the model. you can also found a librery on acoustics field integreted in this software .please check the link:
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Hello,
I am trying to find acoustic round-trip latency of Android smartphones. I have using the technique of where I play a beep and listen to it through the phone and then perform convolution and get time index where we get the peak value.
Issues:
Here the issue is that when we play our beep, the AEC and NS of Android smartphones cancel and attenuate the beep and it cant be seen in recorded data.
Background & Relevant Information:
Most of the applications that measure acoustic latency such as the OboeTester app etc. use VOICE_RECOGNITION (https://developer.android.com/reference/android/media/MediaRecorder.AudioSource#VOICE_RECOGNITION) mode. In this mode, no DSP is performed and we get raw data. But this excludes the latency of DSP algorithms performed by the built-in components.
What I want:
I want to find the round trip latency using VOICE_COMMUNICATION mode. In this mode, all components of AEC, AGC, and NS are activated. But this cancels our beep and we can't get accurate results.
Is there any want to find latency while AEC and NS are working. Looking forward for the solution.
Regards,
Khubaib
Let's say I play a voice signal that will from a phone speaker and then capture it with the same phone's mic. If AEC is there, a played signal will be set as a reference signal and it will remove the captured signal. That's what I think.
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We know that by using a microphone array we gain extra SNR. In the meantime, vector sensors are also with that advantage, and moreover, able to achieve that with a single sensor without the necessity of using an array. However, the reality is nowadays most acoustic products are using a microphone array instead of a vector sensor. Why is that?
There isn’t always a sharp distinction between microphones and vector sensors. As an example, any directional microphone, such as cardioid and super-/hypercardioid, is a 1d vector sensor.
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The shell is made of metal, the inside and exterior are inviscid fluids.
The ratio of shell thickness to radius (h/a) ranges from 0.5 % to 2 %.
I have written Fortran programs for the models described in the papers listed below but they are all unsatisfactory in some respect. Hickling used full exact elasticity, but there seem to be misprints in the paper. The others are thin-shell models and yield a resonance frequency of zero at particular values of h/a. I will give further details to anyone who asks and is acquainted with the issue.
Hickling 1964
Lou & Su 1978
Felippa & Geers 1980 (same result as preceding paper)
Dean & Werby 1992
Do you have measurements or a numerical model to compare with (validation/verification)? If not, then it is difficult to judge which is 'best', unless there are some clear errors or unrealistic assumptions in the different models.
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Are the broadband noise results taken from ANSYS fluent trustable?
(Acoustic > Broadband noise) for a turbulent flow case.
Hello,
Keeping in mind that it is a near-field approach, the model does not predict the sound at receivers far away from the flow field. Otherwise, it is a fairly good prediction.
The model can also be employed to extract diagnostic information on the noise source to check portions of the flow primarily responsible for noise generation.
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Hello everyone,
I am trying to set up a 3D model with acoustic infinite elements along the boundaries. To accomplish this I have taken the following steps:
1. create a 3D part. 2. create a material that has acoustic medium property. 3. create a section that is acoustic infinite. 4. assign a section to the part. The problem is in step 4: I cannot see the acoustic infinite section I created. Do you know how can I fix this?. I thank you very much for any help in advance.
In what way and why would you like to see acoustic infinite elements? They are just there to approximate a BC free of reflection (or a Sommerfeld condition). Thus, by them self there is noting to see, but an incoming wave will not result in a reflected sound field.
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Dear all,
I am learning acoustic analyzes and saw a paper about powertrain acoustic, which is:
At the end of the paper, there is a graph about mesh frequency and harmonic responses. What exactly does the attached graphic mean? Can I kindly ask your help?
Thanks and regards.
Just to complement the accurate comment of Malcolm, it shows this test bed allows a well mastered rotational speed increase, because the sloping bands are so perfectly linear! When doing such measurement on an assembled machine in standard operation, the powertrain RPM increase with time would not generally be linear: anyway all sloping bands would appear homothetic as they are perfectly harmonic (the number of teeth of each gear is invariant). The graph would not be easy to read if the measurement would be taken at constant speed as the gears signatures would show-up as vertical lines, possibly confused with the natural frequencies. So to follow the gearbox vibrational signature you better monitor the start or stop periods, unless you look for possible unsteadiness issues (e.g. instabilities) where constant speed tests are more relevant...
As a whole this graph is usually described as a "waterfall plot". It belongs to the global family of time-frequency representations. In this example, the right setting of the colour scale is essential for maximizing the legibility of the gears signatures!
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I am modelling an axisymmetric piezoelectric transmitter in COMSOL 5.6 and use Exterior Field Calculation (full integral) to find the pressure outside my simulation domain. This works fine when I want to find the pressure in a single point (e.g. acpr.pext(1,0)), but I want to find the average pressure over a plane surface coaxial with the transmitter, i.e. a line average due to the axial symmetry.
I haven't been able to define a line average in "Result -> Derived Values" since there is no boundary outside my simulation domain, and if I add a line in the geometry outside my simulation domain, it does not get meshed. An alternative approach would be to export acpr.pext at the line of interest (with a suitable sampling) to a text file and compute the average outside COMSOL, so far I haven't been able to export the pressure for multiple points.
Does anybody have an idea as to how I could compute the average pressure?
Eivind Nag Mosland I think you can just add a domain which has the surface that you want to be averaged. Mesh it. And make an average operation over pext on that surface. Works fine.
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Hi,
I am working on a problem that involves multiple smartphones/tablets. All devices are playing the same sound with synchronization difference up to +- 5ms. Now, there is an echo issue and I want to cancel acoustic echo on the phones.
So, keeping this problem as simple I have to create an echo canceller for multiple speakers and one mic scenario. I have already read papers regarding stereo echo cancellers but that doesn't solve my problem.
Any help will be appreciated.
Regards,
Khubaib
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Hello,
I have been working on acoustic echo cancellation while following the research paper :
Since I am working on real-time audio data so my problem is as follows:
• I have a buffer that stores Far-end (packets being played by phone) data in terms of 21.33ms chunk equivalent to 1024 shorts.( Sampling rate 48000 Hz)
• A near-end packet is recorded i.e 21.33ms of data with the same format as mentioned above.
Problem Statement:
• Let's suppose we have a Far-end packet containing the word "hello"
------------------------------
| |
| H E L L O |
------------------------------
is being played by phone and now its echo is being recorded in a Near-End packet. Now the cases arise here are that this could be recorded as:1
------------------------------
1. | |
| H E L L O |
------------------------------
Hello completely recorded in one packet.
2. ------------------------------ ------------------------------
| | | |
| H E | | L L O |
------------------------------ ------------------------------
Distributed in two Near-end packets
3. ------------------------------ ------------------------------
| | | |
| H | | E L L O |
------------------------------ ------------------------------
and so on random distribution of far-end audio between multiple chunks of near-end audio.
Now, I want to detect echo and perform cancellation. That can be done if I get an accurate chunk of far-end whose echo is in the near end chunk. Right now I am making overlapped chunks with the shift of 1 sample equivalent to 0.020833 ms of data. But this is quite computationally over expensive.
So 2 questions arise here:
1. What should be the optimal length of overlapping?
2. What could be the minimum resolution of acoustic echo in terms of time in ms? i.e minimum echo delay change? Can it be like 0.1ms or 0.02 ms ?
I hope my question will be cleared. I tried to explain it yet keep it concise.
Any help will be appreciated.
Regards,
For the part relating to the listeners, yes. For the recognition and measurement an earlier echo detection may be useful for potential risky ones. I have never processed this myself, but have a lot of room acoustics measurement and prediction experience. To figure out if there are echoes in rooms or measured impulse responses listening to the impulse responses is the best method in my experience. You need to take that further. Althoiugh video conference systems and possibly mobile phones have such algoritmes already. Theree should be vast amounts of literature on the phenomenon.
I also have a conference article on the acoustics of coupled rooms. The environments needs to be drier than usual to work well. It is impossible to get rid of reverb that are already on the signal..
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Test a gas stove at, e.g., five different powers. Record the acoustic signal and the sound pressure level [this latter will not be a precise value, but their ratios will be]. For the acoustic signal, you can use, e.g., the Spectroid or Spectrogram app (there are a lot of apps out there to do FFT on the microphone signal). For the sound pressure level, you can use, e.g., the Andro sensor app.
need recommendations for above statement..
I just want to get output of it and also 2-3 pages of of its diagram .
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1- I have to use Perfectly matched layer while using port boundary condition or not.
2- My port shape is hexagonal.
So from available options, I am choosing user defined port. But while computation it is showing error.
Plz suggest.
Thanks.
Thank you very much sir. René Christensen
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Goal: I would like to make a plate of wood of equal acoustic path length (transversely).
Question: Is there any simply way to measure the acoustic path length (something similar to optical path length).
In optics, because light travel in various speed, we have optical length.
How about acoustics? Is there any acoustic path length?
Is there any convenient method to measure it?
I want to measure the acoustic path length within a wood. Because every place within a wood structure may have different density. I want to make a wood plate of equal acoustic path length every (therefore the physical thickness may differ). Is it possible?
I think the following research work related to the acoustical studies on wood can be of some use to you to figure out the answer to your question.
Acoustic Studies on Wood - University of Canterbury
ir.canterbury.ac.nz › handle › thesis_fulltext
PDF
by HJ Hansen · 2006 · Cited by 13 — structural timber in housing, wood-based panels and pulp and paper. Wood shows ... thought that the acoustic waves find their fastest path within a distance of.
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I am using boosted regression trees (BRT) to investigate the environmental influences of shark presence at a single location. I have a year-long dataset of acoustic tag detections and environmental data (e.g. current speed and direction etc.) which I have split into 1hrly time bins, i.e. the number of detections every hour and the hourly mean for each environmental variable. Having researched BRTs extensively, it seems that temporal autocorrelation (serial correlation) is not addressed (although spatial autocorrelation is). Having built several models I used the acf() function and a Durbin–Watson test on the model's residuals and it is showing some degree of autocorrelation (DW test = 1.09). Is serial correlation a problem with BRTs? If so, can anyone suggest a way to 'fix' the issue? Many thanks!
I can now answer my own question - BRT models circumvent temporal autocorrelation by randomly selecting (without replacement) a proportion of the data at each iteration, which is controlled by the bag fraction argument. This data is also further split during the cross-validation (CV) process. Thus, the probability of a contiguous time-series being used is extremely small.
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I am doing AE experiment in FRC concrete by keeping the threshold as 30 db (as low as possible to get maximum number of hits without noise). I want to verify whether the AE data obtained is correct or not. Is there any standard process for AE data validation.
The threshold level depends strongly on what material system you are looking at in general. Composites will produce a high level of incoherent (but structured) noise. I would suggest testing at small distances and going farther and father but I guess you can't go too far because of the large attenuation. After all, this will be very much like empirical where some preliminary efforts are required. Good luck!
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I have modelled a unit-cell of an anechoic structure using ANSYS. The layer is silicone and has been assigned as an acoustics physics region, with an air cavity inside (the air has been modelled and also assigned as an acoustics physics region). There is a steel backplate as well that is structural. In order to simulate the water closure on the silicone layer face I have applied an impedance boundary condition, assigned a port to this front surface and used the body of the same layer to assign the inside surface bodies. A planar wave has been applied using a 'port in duct' excitation condition (with 10000 Pa) and the acoustic absorbance is calculated.
I have used the same material parameters that I have seen in many papers, however I am getting very different results and wondered if anybody could please highlight where I have modelled it incorrectly or explain the observed behaviour? I have included an image of the absorption coefficient with regards to frequency in a 0-6000 kHz range.
Thank you for any help.
Hi
A hand sketch or similar of the setup would help.
Impedance BC only apply for normal angle of incidence. They work on boundaries at a distance from the source, say one wavelength out or so and then, still are reflecting.
As per usual - the advice when tweaking models - start with simulating a Kundt's tube experiment first, as you there can use impedance BCs. Move to 3d from there.
/C
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Hi,
I have been working on multi-loudspeaker and single mic acoustic echo canceller ( more than a typical stereophonic echo canceller). I have researched and came to know that we have to decorrelate the signals in order to correctly identify the estimated echo signal (i.e replicate impulse response). So, I want to know if there are any decorrelation techniques for let's say N number of loudspeakers?
Regards,
Hello,
Here are 2 papers that are related to your problem. They can be uploaded following this link : http://www.buchner-net.com/mcaec.html
• H. Buchner and S. Spors, "A general derivation of wave-domain adaptive filtering and application to acoustic echo cancellation," Proc. Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, Oct. 2008.
• H. Buchner, "Acoustic echo cancellation for multiple reproduction channels: From first principles to real-time solutions," Proc. ITG Conf. on Speech Communication, Aachen, Germany, Oct. 2008. Best Paper Award.
I hope this will help,
Pascal
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I am using Audacity to analyse the presence of birds and frogs recorded with a SM4 recorder (Wildlife Acoustic). Background noise (rainfall, wind) is an important variable to consider that can affect the detection of some species. What bioacoustic variable can be taken to quantify this noise? The RMS dB is an option.
Mariano J. Feldman, when considering the effects of background noise on detection capabilities of specific sounds, you would want to measure sound levels over the frequency range of the signal (sound) of interest. For example if frogs produce sounds from 50 Hz to 1 kHz, you may find it useful to look at background noise over that bandwidth. Filters can be used to measure the RMS levels over specific bands of frequencies, but PSD values are probably more useful as you can integrate those values over the desired frequencies. Also 1/3 Octave and Octave levels are useful for monitoring patterns in sound levels over standardized frequency ranges. I am not sure if you are familiar with R or Matlab, but I would search for a program called PamGuide by Merchant et al. if you do not want to write your own code. There is also a paper associated with that software that is useful for understanding those measurements, also by Merchant et al. Lastly, when considering background noise, you will need to be aware that the signals of interest will likely influence those background noise levels. Picking a time when those signals do not occur will give you an understanding of baseline sound levels in the absence of those sounds.
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I have used ICA for the problem of mixing acoustic and UHF signals from partial discharges. I know that it has been used in Biomedical, Acoustic, and many other fields. Do you comment on how you have used it?
I have used it for feature selection purposes in my study but did not work better than other methods (PCA and LDA).
rica(X,q,Name,Value is the implemented function in MATLAB2019.
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In ANSYS, as in also e.g. COMSOL Multiphysics, you can calculate a far-field acoustic pressure outside the explicit FEM domain. However, whereas in COMSOL Multiphysics you define a certain closed surface on which you calculate the far-field pressure via the Helmholtz-Kirchhoff integral, it is unclear which surface is actually being used in ANSYS (or what is actually being calculated).
Far-feild acoustic pressure is measured from the field at a point which is atleast two wavelenghs away from the source.
By subtracting the total pressure from the mean pressure we get the acoustic pressure.
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Hi,
I am keen to know the basics to remove echo knowing FarEnd Signal and NearEnd Signal. I have read research papers in which its commonly said:
y(n) = hTx
where hT is the room impulse response and echo signal estimated is y(n).
Now, what I really want to understand is the computation of room impulse response. Given two-time frame arrays of PCM 16 bit. Let's say:
Near_end_sig = [x1,x2,x3,x4,....,xN] (one time frame)
Far_end_sig = [y1,y2,y3,....,yN] (one time frame)
Here I want to know in this case working on digital acoustic signals (PCM-16 bit arrays of size let's assume 1024). How do I compute room impulse response h and how do I estimate echo signal? My main concern is the computation of room impulse response and the echo signal estimation based on the time frames.
Regards,