Hasil untuk "Acoustics in engineering. Acoustical engineering"

Jorge Melegati

The adoption of Generative AI (GenAI) suggests major changes for software engineering, including technical aspects but also human aspects of the professionals involved. One of these aspects is how individuals perceive themselves regarding their work, i.e., their work identity, and the processes they perform to form, adapt and reject these identities, i.e., identity work. Existent studies provide evidence of such identity work of software professionals triggered by the adoption of GenAI, however they do not consider differences among diverse roles, such as developers and testers. In this paper, we argue the need for considering the role as a factor defining the identity work of software professionals. To support our claim, we review some studies regarding different roles and also recent studies on how to adopt GenAI in software engineering. Then, we propose a research agenda to better understand how the role influences identity work of software professionals triggered by the adoption of GenAI, and, based on that, to propose new artifacts to support this adoption. We also discuss the potential implications for practice of the results to be obtained.

Cláudio Lúcio do Val Lopes, João Marcus Pitta, Fabiano Belém et al.

The integration of Artificial Intelligence (AI) into clinical settings presents a software engineering challenge, demanding a shift from isolated models to robust, governable, and reliable systems. However, brittle, prototype-derived architectures often plague industrial applications and a lack of systemic oversight, creating a ``responsibility vacuum'' where safety and accountability are compromised. This paper presents an industry case study of the ``Maria'' platform, a production-grade AI system in primary healthcare that addresses this gap. Our central hypothesis is that trustworthy clinical AI is achieved through the holistic integration of four foundational engineering pillars. We present a synergistic architecture that combines Clean Architecture for maintainability with an Event-driven architecture for resilience and auditability. We introduce the Agent as the primary unit of modularity, each possessing its own autonomous MLOps lifecycle. Finally, we show how a Human-in-the-Loop governance model is technically integrated not merely as a safety check, but as a critical, event-driven data source for continuous improvement. We present the platform as a reference architecture, offering practical lessons for engineers building maintainable, scalable, and accountable AI-enabled systems in high-stakes domains.

Allison M King, David R. Dowling

Acoustic waves are well-suited for remote sensing applications and structural health monitoring because they convey information about their source and can be recorded using non-contacting methods. An important structural health monitoring task is localization of an impact excitation. However, traditional array signal processing techniques for source localization are ill-suited for many structural engineering applications because of geometrical complexity, dispersive acoustic wave propagation in structures, and the coupling of the vibrating structure and the surrounding medium. Plus, many traditional methods use contacting sensors, which can permanently alter the structure. This study utilizes Bartlett matched field processing (MFP), a localization technique initially developed for underwater acoustics, to localize an impact source on a metal plate. A 14-microphone array recorded the sound radiated by a 0.64-cm-thick 91.4-cm-diameter round aluminum plate after the impact of a 1.3-cm-diameter stainless-steel ball bearing. MFP and a physics-based finite-element acoustic environment model were used to localize the impact on the plate. Results are presented as ambiguity surfaces where the predicted source location was typically found to be within 1.1 cm of the true source location. Localization performance was also assessed in a noisy environment, with success down to a signal-to-noise ratio of -7.5 dB.

Wang Qiaochu, Hongwei Wang, Cai Yangsheng et al.

Previous studies suggested that introducing fountain sound could mitigate the discomfort and memory disturbance caused by structure borne sound from a metro, and proposed the prediction models for the discomfort after mitigation. However, these studies failed to identify the primary, secondary and significant influencing factors on the discomfort after mitigation, which hindered the proposal of optimal masking strategy and undermined the scientific validity of models. Additionally, previous analyses overlooked the primary, secondary and significant influencing factors on the memory disturbance after mitigation and lacked prediction model for it. Therefore, this study explored these aspects further. Based on auditory experiments, using partial least squares model and prediction model, this study found that considering total impact degree, the discomfort was predominantly influenced by the subjective loudness. However, the sound levels were the most important factors in determining the memory disturbance. The signal-to-noise ratio significantly influenced the discomfort but had no significant impact on the memory disturbance. Moreover, the subjective loudness emerged as the most effective predictor of the discomfort. While predicting the memory disturbance predominantly depended on the sound levels, and among the prediction models based on the sound levels, the predictive effectiveness of the energy summation model was comparable to that of the independent effects model. Furthermore, as global equivalent A-weighted sound level increased, the mitigation effect on discomfort became more evident, but its effectiveness in mitigating the memory disturbance gradually decreased. These conclusions could provide optimal strategies for enhancing such masking effects, and more effective prediction tools for such effects.

Blau Matthias, Roden Reinhild, Hauenschild Nele et al.

In this study, the problem of experimentally identifying the own-voice generated objective occlusion effect in hearables is addressed. Challenges arise from the sub-optimal properties of one’s own voice as a test signal, namely, poor reproducibility, limited bandwidth, and the induction of time-variant behavior of the effect being measured. Based on experiments with 19 participants wearing a vented hearable and producing running speech and a sung vowel, it was found that (a) running speech is better suited than vowels in most respects, except for the time-variance of the occlusion effect, (b) the use of transfer function-based estimates of the occlusion effect results in more problems than advantages in comparison to estimates based on power spectral densities, and (c) the popular method of measuring the occlusion effect by simultaneously measuring inside and outside the occluding device entails systematic errors of up to about 3–4 dB, even in the frequency range in which it was previously considered valid. In contrast, the simultaneous measurement with reference to the open contralateral ear is accurate throughout the frequency range in which an acceptable SNR is achieved.

Haibo Wang, Zhuolin Xu, Shin Hwei Tan

Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.

Ziyou Li, Agnia Sergeyuk, Maliheh Izadi

Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflows. We present Prompt-with-Me, a practical solution for structured prompt management embedded directly in the development environment. The system automatically classifies prompts using a four-dimensional taxonomy encompassing intent, author role, software development lifecycle stage, and prompt type. To enhance prompt reuse and quality, Prompt-with-Me suggests language refinements, masks sensitive information, and extracts reusable templates from a developer's prompt library. Our taxonomy study of 1108 real-world prompts demonstrates that modern LLMs can accurately classify software engineering prompts. Furthermore, our user study with 11 participants shows strong developer acceptance, with high usability (Mean SUS=73), low cognitive load (Mean NASA-TLX=21), and reported gains in prompt quality and efficiency through reduced repetitive effort. Lastly, we offer actionable insights for building the next generation of prompt management and maintenance tools for software engineering workflows.

Marina Araújo, Júlia Araújo, Romeu Oliveira et al.

[Context] Domain knowledge is recognized as a key component for the success of Requirements Engineering (RE), as it provides the conceptual support needed to understand the system context, ensure alignment with stakeholder needs, and reduce ambiguity in requirements specification. Despite its relevance, the scientific literature still lacks a systematic consolidation of how domain knowledge can be effectively used and operationalized in RE. [Goal] This paper addresses this gap by offering a comprehensive overview of existing contributions, including methods, techniques, and tools to incorporate domain knowledge into RE practices. [Method] We conducted a systematic mapping study using a hybrid search strategy that combines database searches with iterative backward and forward snowballing. [Results] In total, we found 75 papers that met our inclusion criteria. The analysis highlights the main types of requirements addressed, the most frequently considered quality attributes, and recurring challenges in the formalization, acquisition, and long-term maintenance of domain knowledge. The results provide support for researchers and practitioners in identifying established approaches and unresolved issues. The study also outlines promising directions for future research, emphasizing the development of scalable, automated, and sustainable solutions to integrate domain knowledge into RE processes. [Conclusion] The study contributes by providing a comprehensive overview that helps to build a conceptual and methodological foundation for knowledge-driven requirements engineering.

Chen Shen, Shuaiguo Zhao, Zhenhua Tian et al.

Recent years have witnessed the surge of topological wave phenomena as a versatile platform to engineer exotic wave energy transport which is robust to defects and disorders. Most demonstrations in acoustics remain in a single phase of matter such as solid or air. Here, we introduce the realization of valley phononic crystals for surface acoustic waves and their interaction with fluids in an acoustofluidic setup. It is shown that the interplay between megahertz elastic waves and hydrodynamics where two phases of materials are involved offers rich physics and new engineering potentials of topological matter. By electroplating hexagonal copper pillars on a lithium niobate substrate and adding a liquid layer on top of it, the excited elastic valley spin is transferred at the interface of solid-fluid domains. The interactions lead to valley streaming vortices in the fluid domain that support backward-immune particle transport. In addition, it is found that pressure wells are formed around the small pillars, which enable the concentration of DNA molecules in the nm size range. The studies may open new avenues for applying topological acoustic waves in particle manipulation and life sciences.

G. Fusaro, D. D’Orazio, Massimo Garai

Acoustic metamaterials (AMMs) have emerged as a promising strategy for low-frequency noise control in ventilation ducts, offering subwavelength, tunable solutions that overcome key limitations of conventional silencers, such as high pressure drop and reduced long-term performance. This review presents a structured analysis of 54 studies on AMMs for duct acoustics, with civil, mechanical, aerospace, and biomedical engineering applications. AMM unit designs are categorized by physical mechanism, including resonant cavities, acoustic membranes, Herschel-Quincke tubes, Fano-like interference structures, duct shape modifications, micro-perforated panels, and porous materials. The associated acoustic and flow-related performance parameters, such as insertion loss, transmission loss, absorption coefficient, flow velocity, temperature, pressure drop, Reynolds number, and Mach number, are systematically examined. Analytical, numerical, and experimental approaches are reviewed with attention to their respective merits and limitations, particularly in capturing multi-physical interactions between acoustics, fluid flow, and structural dynamics. Of the studies surveyed, 35 employed monophysical models, 8 used loosely coupled (monophysical parallel) methods, and only 11 adopted fully coupled multi-physical frameworks. This review highlights the need for integrated design methodologies and standardized evaluation under realistic flow conditions to advance the effective implementation of AMMs in ducted acoustic systems.

Xinwei Li, Shuwei Ding, Xinxin Wang et al.

Lattice structures with customizable acoustical and mechanical properties show significant promise as practical engineering materials. However, the geometry of traditional lattice structures simultaneously dictates both acoustical and mechanical properties, with alterations in one impacting the other, leaving little room for customization. Herein, leveraging the mechanism of Helmholtz resonators, a general recipe is presented to independently introduce sound absorption and mechanical properties in lattice structures. The sound absorption component is based on a perforated plate, while the mechanical component is based on a truss structure. Through a high‐fidelity analytical acoustics model is developed, and finite element analysis outlines the range of properties achievable through the proposed structures. The design encompasses structures with effective absorption, characterized by a resonance peak with coefficient ≥0.7, across almost every frequency in a broad range from 1000 to 5000 Hz, within a range of lattice thicknesses from 21 to 25.5 mm. Also, diverse range of stiffness and strength, and large‐strain deformation modes, can be achieved through the implementation of different trusses. Finally, the concept is validated experimentally through 3D‐printed samples. This innovative approach allows for the tailored creation of lattice structures that specifically address the acoustical and mechanical requirements in diverse applications.

Daniel Fink

A revised comprehensive new definition of noise is proposed. Noise: a) For living things, noise is unwanted and/orharmfulnd. b) In engineering and electronics, noise is any unwanted disturbance within a useful frequency band, such as undesired lectric waves in a transmission channel or device. c) In scientific measurements, noise is erraic, intermittent, or statistically random oscillation. The revised comphrehensive new definition builds on the Acoustical Society of America/American National Standards institute definition to include technical considerations, and acknowledges the harmful effect of noise on plants. It updates the noise definition presented at the 2019 Acoustical Society of America winter meeting, noise is unwanted and/or harmful sound. Unlike the standard definition, noise is unwanted sound, that new definition emphasized that unwanted sound is harmful, able to cause adverse auditory and non-auditory health effects, and that wanted sound can also caus auditory damage. The Proceedings of Meetings on Acoustics article based on that presentation has been cited 37 times. The prevvious new definition opens the 2021 American Public Health Association policy statement, Noise as a Public Health Hazard, was adopted for use by the International Commission on Biological Effects of Noise (ICBEN) in 2023, and added to the ICBEN Constitution.

Ning Xiang, Ziqi Chen

Noise control engineering and architectural acoustics practice have widely applied diffusing elements and devices to create surface scattering and diffuse reflections. An acoustical goniometer in the form of a circular microphone array has been used to characterize scattered responses for various types of diffusing elements/devices. This research is also intended for experimental validation of diffraction simulations of diffusing devices based on the physical theory of diffraction (PTD). To cope with experimental challenges, particularly for the research in the physical theory of diffraction, an acoustic goniometer must achieve a high enough angular resolution in addition to fulfilling far-field requirements. This paper discusses practical implementations and experimental results of portable goniometers with a radius of up to five meters and an angular resolution of 1.25 degrees. The practical implementation is intended to be easily deployable in empty, indoor spaces of sufficiently large dimensions for scattered reflection characterization. This paper discusses an effort of increasing experimental efficiency of characterization procedures for oblique incidences.

Zotter Franz, Riedel Stefan, Gölles Lukas et al.

Can uncorrelated surrounding sound sources be used to generate extended diffuse sound fields? By definition, targets are a constant sound pressure level, a vanishing active sound intensity, and uncorrelated sound waves arriving isotropically from all directions. Are there ideal source layouts to synthesize a maximum diffuse sound field within? As methods, we employ numeric simulations and undertake a series of considerations based on uncorrelated source layouts at a finite radius. Statistically expected active sound intensity and sound energy density are insightful and highlight the relation of active sound intensity to potential theory. Correspondingly, both Gauß’ divergence and Newton’s spherical shell theorem apply, and they provide valuable insights. In a circular layout, uncorrelated elementary point-source fields decaying by 1/√r ideally compose an extended sound field of vanishing active sound intensity; in spherical layouts this is the case with a 1/r decay. None of the layouts synthesizes a perfectly constant sound energy density inside. Theory and simulation offer a broad basis for understanding the synthesis of diffuse sound fields with uncorrelated sources in the free sound field.

Wang Kangxi, Li Peiwang, Sun Guanghui et al.

To ensure the reliable management of the safe operation of an underground pipeline in a chemical industrial park and accurately determine the location of the pipeline leakage point, a precise location method for the leakage point of an underground pipeline in a chemical industrial park based on ultrasonic creeping wave flaw detection and data integration is proposed. In this method, the ultrasonic creeping wave flaw detector is used to detect the underground pipelines in the chemical industry park and obtain the status signals of the underground pipelines in the chemical industry park. The improved K-means algorithm is used to fuse the signals collected by clustering to obtain abnormal signals in the signals; The wavelet transform is used to process the ultrasonic abnormal signals obtained by clustering, extract the local time energy density characteristics of the frequency band, and superimpose the image. By introducing image enhancement factors, the leakage area can be centrally located, the coordinates of the pipeline leakage points can be determined, and the leakage degree can be determined by calculating the sum of the damage probability of each leakage point. The test results show that the clustering effect of this method is good, and the separability measurement indexes are all above 0.925, which can complete the location of single point and multi-point leakage points, and the maximum location error is 11.55 mm. The reliability of the location of the leakage point is high.

Chocholaty Bettina, Roozen Nicolaas Bernardus, Hoppe Karl-Alexander et al.

Lightweight floor structures, such as timber or hybrid timber floors, face challenges associated with excessive vibrations and elevated levels of low-frequency impact sound. Especially here, accurate prediction of a floor’s vibration and acoustic behavior is essential. However, typical laboratory testing of building elements is costly and time-consuming. To reduce costs, in this study, adapted simulations are carried out on two types of hybrid steel-timber floor structures to evaluate vibrations and impact sound. The hybrid elements are made of laminated veneer lumber as the top and bottom layers and a trapezoidal steel component as the web. Vibration measurements are used in combination with Bayesian optimization to efficiently calibrate Finite Element models, which are subsequently utilized to quantify and validate the floor structures regarding vibrations and impact sound. The two types of cross-sections, i.e., closed and open, are investigated and compared. The impact sound pressure level computations reveal promising results in predicting the behavior of the hybrid structures. However, further countermeasures are required to fulfill vibration serviceability requirements.

Dreier Christian, Vorländer Michael

This paper presents a drone auralization model that reproduces the spectro-temporal and spatial characteristics of a drone during flight. Focusing on perceptual plausibility, the time-variant processes are modeled by taking into account the statistical amplitude and frequency modulation distributions of a reference drone sound. For completeness, the far-field directivity is extracted based on time-variant wave backpropagation from microphone array signals. Both components consider a combined level calibration with regard to the reconstructed sound pressure on a spherical surface around the source. With regard to reproducibility, this paper is accompanied by supplemental data to present a synthesis model including the oscillator and digital filter coefficients for procedural audio synthesis. From evaluation, the model shows good agreement by comparison of psychoacoustic measures of the synthesized drone to a recorded reference. The drone auralization model can be applied in future research on urban soundscapes where Unmanned Aerial Vehicles (UAV) may appear in a great variety of use cases. Furthermore, it can deliver input data for simulation tools where the spatial radiation characteristics of a drone should be included, such as the development of array-based drone detection.

Cuiyun Gao, Xing Hu, Shan Gao et al.

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have demonstrated an unprecedented capacity to understand, generate, and operate programming languages. They can assist developers in completing a broad spectrum of software development activities, encompassing software design, automated programming, and maintenance, which potentially reduces huge human efforts. Integrating LLMs within the SE landscape (LLM4SE) has become a burgeoning trend, necessitating exploring this emergent landscape's challenges and opportunities. The paper aims at revisiting the software development life cycle (SDLC) under LLMs, and highlighting challenges and opportunities of the new paradigm. The paper first summarizes the overall process of LLM4SE, and then elaborates on the current challenges based on a through discussion. The discussion was held among more than 20 participants from academia and industry, specializing in fields such as software engineering and artificial intelligence. Specifically, we achieve 26 key challenges from seven aspects, including software requirement & design, coding assistance, testing code generation, code review, code maintenance, software vulnerability management, and data, training, and evaluation. We hope the achieved challenges would benefit future research in the LLM4SE field.

Umm-e- Habiba, Markus Haug, Justus Bogner et al.

Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.

Kaleris Konstantinos, Moiragias George, Hatziantoniou Panagiotis et al.

This work provides an in-depth investigation on the effect of sound diffraction in the acoustics of the ancient theatres, with reference to the theatre of Epidaurus. It is increasingly evident that in such theaters, sound diffraction at the edges of the multiple tiers generates significant source signal amplification. Especially for the distant listener positions, an accumulation (“avalanche”) effect from lower tier diffracted energy is identified. This study examines a 3D model of an elementary slice of the seating benches (“koilon”), evaluating the generated sound field in the time, frequency, and spatial domains. The analysis accounts for direct, reflected, diffracted and mixed reflected – diffracted paths and the theatre’s acoustic response is numerically evaluated in various positions along the koilon slice, accurately matching to in-situ measurements. The contribution of the diffracted sound to the total sound field is identified through a detailed and novel analysis of energy-based acoustic parameters, via the time and frequency responses as well as of the spatial parameters relating to listener-perceived effects. In all cases, the contribution of sound diffraction components is examined via its contribution to speech intelligibility from signals generated in the theatre’s orchestra and from a virtual reconstruction of the stage-scenic building.