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Related Concept Videos

Mixing Time01:19

Mixing Time

566
The concept of mixing time is significant in producing a uniform concrete mix with the required strength. The mixing period starts once all components are in the mixer. Initially, the mixer is charged with 10% of the water, followed by the consistent addition of solids and then 80% of the water. The remaining water is added later, within the first quarter of the mixing period. The minimum mixing time varies according to the mixer's capacity; for example, mixers with up to 1 cubic yard...
566
Echo01:06

Echo

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The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
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Related Experiment Video

Updated: Apr 17, 2026

Quantifying Mixing using Magnetic Resonance Imaging
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Quantifying Mixing using Magnetic Resonance Imaging

Published on: January 25, 2012

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Mixing time prediction using spherical microphone arrays.

Philipp Götz1, Konrad Kowalczyk1, Andreas Silzle1

  • 1Fraunhofer Institute for Integrated Circuits IIS, Audio & Multimedia Division, 91058 Erlangen, Germany philipp.goetz@iis.fraunhofer.de, konrad.kowalczyk@agh.edu.pl, andreas.silzle@iis.fraunhofer.de.

The Journal of the Acoustical Society of America
|February 21, 2015
PubMed
Summary
This summary is machine-generated.

A new method predicts room acoustics mixing time by analyzing spatiotemporal sound field properties. This diffuseness-based approach correlates well with human perception, improving acoustic predictions.

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Area of Science:

  • Acoustics
  • Psychoacoustics
  • Signal Processing

Background:

  • Human perception of room acoustics is influenced by the transition from early reflections to late reverberation.
  • This transition period is defined as the mixing time in room impulse responses.

Purpose of the Study:

  • To propose a novel multi-channel mixing time prediction method.
  • To account for spatiotemporal properties of the sound field, unlike existing channel-based predictors.

Main Methods:

  • A diffuseness-based prediction method was developed.
  • The proposed method was compared against existing model- and channel-based predictors.
  • Validation was performed using acoustic measurements and simulations.

Main Results:

  • The diffuseness-based method showed good correlation with perceptual mixing time.
  • The proposed method effectively captures spatiotemporal sound field characteristics.
  • Insights into the relationship between prediction methods and reflection density were gained.

Conclusions:

  • The proposed diffuseness-based method offers an improved prediction of perceptual mixing time.
  • This approach enhances the understanding of room acoustic perception.
  • It provides a valuable tool for acoustic design and simulation.