MétaCan
Menu
Back to cohort
Record W1992487647 · doi:10.1121/1.2161433

On the use of a diffusion equation for room-acoustic prediction

2006· article· en· W1992487647 on OpenAlexafffund
Vincent Valeau, Judicaël Picaut, Murray Hodgson

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsDiffusion equationRoom acousticsDiffusionReverberationGeneralizationComputer scienceBoundary (topology)Architectural acousticsField (mathematics)Boundary value problemRay tracing (physics)AcousticsMathematical analysisMathematicsPhysicsOptics

Abstract

fetched live from OpenAlex

This paper presents an alternative model for predicting the reverberant sound field in empty rooms with diffusely reflecting boundaries, based on the generalization and the numerical implementation of a diffusion equation for the energy density. The paper focuses on the source term and the boundary conditions of the diffusion equation, both for the steady state and the time-varying state, in order to make computational use of the model. In addition, theoretical analysis of the diffusion equation shows that the diffusion model may be considered as an extension of the classical theory of reverberation to nondiffuse sound fields. The numerical model is first applied to a cubic room and shows a very good agreement with statistical theory. Two numerical applications are also given for a long room and a flat room; results are in good agreement with numerical results from a ray-tracing software. The main advantage of the present model is its capability to be applied regardless of the complexity of the room shape, and that it gives results at any receiver location, with a low calculation time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.271
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations76
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicHearing Loss and RehabilitationFrench-language works237,207