Sound Simulation Model Research Articles

Validation measurement of vehicle pass-by models for dynamic urban environments

Simulation and auralization of urban traffic noise can help city planners and residents to improve existing urban areas or plan new attractive living spaces while enabling discussions about shared auditory experiences, regardless of expertise. Evaluating street noise in the context of urban areas requires careful consideration of their urban surroundings, such as landscapes, buildings, and other structures. Obtaining measurements to validate simulations may be difficult given the variety and complexity of sounds within an urban setting. Recreating the real urban scenario on a test track, e.g., including building facades and exact source and receiver positions, helps validate simulations but also poses challenges due to varying road surfaces, weather conditions, and disturbances such as industrial or fly-over sounds. This research represents a method of bringing a measurement set-up consisting of source (e.g., vehicle), receiver (e.g., pedestrian), and surfaces (e.g., walls) to the more controlled environment of a hemi-anechoic chamber. The method is intended for the validation of previous vehicle pass-by measurements by utilizing sine sweeps with walls parked at varying distances. These environments aim to deliver more insight into the relevance of diffracted sound for configuration of urban sound simulation models.

Retracted] Construction and Research of Guqin Sound Synthesis and Plucking Big Data Simulation Model Based on Computer Synthesis Technology

The application and economic efficiency evaluation mode of traditional composition in the field of modern music cannot meet the needs of various types of music in China, especially Guqin music. Based on this, this paper studies the big data simulation model of Guqin sound synthesis and plucking based on computer composition technology. The computer composition technology uses the discrete dynamic modeling technology of complex system to complete the computer simulation of Guqin sound through the analysis of the correlation between Guqin music data and realizes the storage and analysis of the generated Guqin sound data. In addition, the technology can analyze the data information of composition mode in the piano sound plucking simulation model with the classical Guqin music data stored in the cloud system over the years and then feed it back to relevant professionals for verification. The experimental results show that the Guqin sound simulation model can efficiently compare and analyze the melody and other data of classical Guqin sound with the simulated Guqin sound and can realize secondary data mining. This paper studies the application of computer composition method based on discrete dynamic modeling technology in Guqin sound simulation, which has certain reference significance for improving the cloud data in China’s modern music field and the intelligent construction of Guqin sound data cloud storage system.

Physically-based statistical simulation of rain sound

A typical rainfall scenario contains tens of thousands of dynamic sound sources. A characteristic of the large-scale scene is the strong randomness in raindrop distribution, which makes it notoriously expensive to synthesize such sounds with purely physical methods. Moreover, the raindrops hitting different surfaces (liquid or various solids) can emit distinct sounds, for which prior methods with unified impact sound models are ill-suited. In this paper, we present a physically-based statistical simulation method to synthesize realistic rain sound, which respects surface materials. We first model the raindrop sound with two mechanisms, namely the initial impact and the subsequent pulsation of entrained bubbles. Then we generate material sound textures (MSTs) based on a specially designed signal decomposition and reconstruction model. This allows us to distinguish liquid surface with bubble sound and different solid surfaces with MSTs. Furthermore, we build a basic rain sound (BR-sound) bank with the proposed raindrop sound clustering method based on a statistical model, and design a sound source activator for simulating spatial propagation in an efficient manner. This novel method drastically decreases the computational cost while producing convincing sound results. Various experiments demonstrate the effectiveness of our sound simulation model.

Brass Instruments Design Using Physics-Based Sound Simulation Models and Surrogate-Assisted Derivative-Free Optimization

This paper presents a method for design optimization of brass wind instruments. The shape of a trumpet's bore is optimized to improve intonation using a physics-based sound simulation model. This physics-based model consists of an acoustic model of the resonator, a mechanical model of the excitator, and a model of the coupling between the excitator and the resonator. The harmonic balance technique allows the computation of sounds in a permanent regime, representative of the shape of the resonator according to control parameters of the virtual musician. An optimization problem is formulated in which the objective function to be minimized is the overall quality of the intonation of the different notes played by the instrument. The design variables are the physical dimensions of the resonator. Given the computationally expensive function evaluation and the unavailability of gradients, a surrogate-assisted optimization framework is implemented using the mesh adaptive direct search algorithm (MADS). Surrogate models are used both to obtain promising candidates in the search step of MADS and to rank-order additional candidates generated by the poll step of MADS. The physics-based model is then used to determine the next design iterate. Two examples (with two and five design optimization variables) demonstrate the approach. Results show that significant improvement of intonation can be achieved at reasonable computational cost. Finally, the perspectives of this approach for computer-aided instrument design are evoked, considering optimization algorithm improvements and problem formulation modifications using for instance different design variables, multiple objectives and constraints or objective functions based on the instrument's timbre.

Developing a framework for statistical process control approaches in project management

Different statistical process control (SPC) approaches were proposed over the years for project management using earned value management/earned schedule. A detailed examination of these approaches has led us to express a need for a unified framework in which to test and compare them. The main drivers for this need were the lack of a formal definition for a state of control, the unavailability of a benchmark dataset, the absence of measures to quantify the SPC performance and the lack of consensus on how to overcome and test the normality assumption. In this paper, we present such a framework that combines a classification from empirical data, a known project dataset, a sound simulation model and two quantitative measures for project control efficiency. Four SPC approaches from prior literature have been implemented and an exhaustive experiment was set up to compare and to discuss their value for the project management practice.

An anatomically sound surgical simulation model for myringotomy and tympanostomy tube insertion

ObjectiveMyringotomy and tympanostomy tube insertion (MT) is a common surgical procedure. Although surgical simulation has proven to be an effective training tool, an anatomically sound simulation model for MT is lacking. We developed such a model and assessed its impact on the operating room performance of senior medical students. Study designProspective randomized trial. MethodsA randomized single-blind controlled study of simulation training with the MT model versus no simulation training. Each participant was randomized to either the simulation model group or control group, after performing an initial MT procedure. Within two weeks of the first procedure, the students performed a second MT. All procedures were performed on real patients and rated with a Global Rating Scale by two attending otolaryngologists. Time to complete the MT was also recorded. ResultsTwenty-four senior medical students were enrolled. Control and intervention groups did not differ at baseline on their Global Rating Scale score or time to complete the MT procedure. Following simulation training, the study group received significantly higher scores (P=.005) and performed the MT procedure in significantly less time (P=.034). The control group did not improve their performance scores (P>.05) or the time to complete the procedure (P>.05). ConclusionOur surgical simulation model shows promise for being a valuable teaching tool for MT for senior medical students. Such anatomically appropriate physical simulators may benefit teaching of junior trainees.

Invariant conditions in value system simulation models

This paper presents a framework for the integration of supply chain (or logistics/distribution), value chain (or financial), and business process (or operational/manufacturing) simulation models, which should facilitate assessing the impact of supply chain and operational changes on an enterprise's financial performance. A Design Science approach is taken to demonstrate that the REA ontology, which provides a shared conceptual ground for these three model types, and its axioms, which describe invariant conditions for value systems, can help to build conceptually sound simulation models and identify the integration points between these models. It is further shown how these three types of simulation models can be integrated into one value system model for discrete event simulation, making use of the ExSpecT simulation tool. With this ontology-based framework, simulation model builders should be able to scope their models better and define integration points with other models, which is expected to promote the (re)use of simulation models for different purposes (e.g., simulating logistical, operational and financial performance).

Improving Software Flexibility for Business Process Changes

In times of continuous change, companies need to adjust their business processes to gain sustainable competitive advantage. Resulting changes in the company’s IT currently require the involvement of developers from departments that are mostly not aligned with the business. These changes often result in high transaction and labor costs. The article presents a platform-based method to adjust business processes with the aim of increasing both efficiency and flexibility compared to current approaches. The core of our work is an evaluation against traditional component-based software development using a sound simulation model. Three real-world scenarios of business process change show that – despite a slight increase in transaction costs – our suggested method decreases labor costs while increasing operational flexibility.

Modelling crop growth and yield under the environmental changes induced by windbreaks 1. Model development and validation

Yield advantages of crops grown behind windbreaks have often been reported, but underlying principles responsible for such changes and their long-term consequences on crop productivity and hence farm income have rarely been quantified. Physiologically and physically sound simulation models could help to achieve this quantification. Hence, the APSIM systems model, which is based on physiological principles such as transpiration efficiency and radiation use efficiency (termed here APSIMTE), and the Soil Canopy Atmosphere Model (SCAM), which is based on the Penman–Monteith equation but includes a full surface energy balance, were employed in developing an approach to quantify such windbreak effects. This resulted in a modified APSIM version (APSIMEO), containing the original Penman equation and a calibration factor to account for crop- and site-specific differences, which were tested against field data and simulations from both the standard APSIMTE and SCAM models. The APSIMEO approach was tested against field data for wheat and mungbean grown in artificial enclosures in south-east Queensland and in south-east Western Australia. For these sheltered conditions, daily transpiration demand estimates from APSIMEO compared closely to SCAM. As the APSIMEO approach needed to be calibrated for individual crops and environments, average transpiration demand for open field conditions predicted by APSIMEO for a given site was adjusted to equal that obtained using APSIMTE by modifying a calibration parameter β. For wheat, a β-value of 1.0 resulted in best fits for Queensland, while for Western Australia a value of 0.85 was necessary. For mungbean a value of 0.92 resulted in the best fit (Qld). Biomass and yields simulated by APSIMTE and the calibration APSIMEO for wheat and mungbean grown in artificial enclosures were generally distributed around the 1:1 line, with R2 values ranging from 0.92 to 0.97. Finally, APSIMEO was run at 2 sites using long-term climate data to assess the likely year-to-year variability of windbreak effects on crop yields. Assuming a 70% reduction in wind speed as representing the maximum potential windbreak effect, the average yield improvement for the Queensland site was 13% for wheat and 3% for mungbean. For wheat at the WA site the average yield improvement from reduced wind speed was 5%. In any year, however, effects varied from negative, neutral to positive, highlighting the highly variable nature of the expression of windbreak effects. This study has shown how physical and biological modelling approaches can be combined to aid our understanding of systems processes. Both the environmental physics perspective and the biological perspective have shortcomings when issues that sit at the interface of both approaches need to be addressed. While the physical approach has clear advantages when investigating changes in physical parameters such as wind speed, vapour pressure deficit (VPD), temperature or the energy balance of the soil–plant–atmosphere continuum, it cannot deal with complex, biological systems adequately. Conversely, the crop physiological approach can handle such biological interactions in a scientific and robust way while certain atmospheric processes are not considered. The challenge was not to try and capture all these effects in 1 model, but rather to structure a modelling approach in a way that allowed for inclusion of such processes where necessary.