exhaust design research paper

Development of Muffler for Automobile Exhaust System Based on Numerical Simulation

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• First Online: 25 February 2024
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• Xihang Li 38 ,
• Guiqin Li 38 ,
• Heqing Dong 38 ,
• Ming Li 38 &
• Peter Mitrouchev 39  

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The development and design of the muffler for automobile exhaust system is often limited by the resources of the engine and the whole vehicle, which makes it difficult to meet the noise target requirements in a short time. This paper firstly designs a three-dimensional model of the exhaust system by using the surrounding data model of the exhaust system and the minimum safe distance, and then establishes the acoustic simulation model of the system according to the boundary conditions. Five kinds of muffler combination schemes are designed. The simulation analysis is carried out by the finite volume method of one-dimensional computational fluid dynamics. Finally, the validity and practicability of the simulation are proved by the experimental verification method. A specific improvement method of the rear muffler is proposed to meet the needs of acoustic design. This research can realize the development of exhaust system muffler in advance, reduce the frequency of later tests of the project, and provide a new method for the development of exhaust system muffler.

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Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai, 200072, China

Xihang Li, Guiqin Li, Heqing Dong & Ming Li

University Grenoble Alpes, G-SCOP, 38031, Grenoble, France

Peter Mitrouchev

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University of Bedfordshire, Luton, UK

Shanghai University of Engineering Science, Shanghai, China

Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway

Kesheng Wang

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Li, X., Li, G., Dong, H., Li, M., Mitrouchev, P. (2024). Development of Muffler for Automobile Exhaust System Based on Numerical Simulation. In: Wang, Y., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation XIII. IWAMA 2023. Lecture Notes in Electrical Engineering, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-97-0665-5_37

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The ways people engage with technology, through its design and functionality, determine its utility and acceptance in everyday use, setting the stage for widespread adoption. When computing tools and services respect the diversity of people’s experiences and abilities, technology is not only functional but also universally accessible. Human-computer interaction (HCI) plays a crucial role in this process, examining how technology integrates into our daily lives and exploring ways digital tools can be shaped to meet individual needs and enhance our interactions with the world.

The ACM CHI Conference on Human Factors in Computing Systems is a premier forum that brings together researchers and experts in the field, and Microsoft is honored to support CHI 2024 as a returning sponsor. We’re pleased to announce that 33 papers by Microsoft researchers and their collaborators have been accepted this year, with four winning the Best Paper Award and seven receiving honorable mentions.

This research aims to redefine how people work, collaborate, and play using technology, with a focus on design innovation to create more personalized, engaging, and effective interactions. Several projects emphasize customizing the user experience to better meet individual needs, such as exploring the potential of large language models (LLMs) to help reduce procrastination. Others investigate ways to boost realism in virtual and mixed reality environments, using touch to create a more immersive experience. There are also studies that address the challenges of understanding how people interact with technology. These include applying psychology and cognitive science to examine the use of generative AI and social media, with the goal of using the insights to guide future research and design directions. This post highlights these projects.

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DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing   Priyan Vaithilingam, Elena L. Glassman, Jeevana Priya Inala , Chenglong Wang   GUIs used for editing visualizations can overwhelm users or limit their interactions. To address this, the authors introduce DynaVis, which combines natural language interfaces with dynamically synthesized UI widgets, enabling people to initiate and refine edits using natural language.  

Generative Echo Chamber? Effects of LLM-Powered Search Systems on Diverse Information Seeking   Nikhil Sharma, Q. Vera Liao , Ziang Xiao   Conversational search systems powered by LLMs potentially improve on traditional search methods, yet their influence on increasing selective exposure and fostering echo chambers remains underexplored. This research suggests that LLM-driven conversational search may enhance biased information querying, particularly when the LLM’s outputs reinforce user views, emphasizing significant implications for the development and regulation of these technologies.  

Piet: Facilitating Color Authoring for Motion Graphics Video   Xinyu Shi, Yinghou Wang, Yun Wang , Jian Zhao   Motion graphic (MG) videos use animated visuals and color to effectively communicate complex ideas, yet existing color authoring tools are lacking. This work introduces Piet, a tool prototype that offers an interactive palette and support for quick theme changes and controlled focus, significantly streamlining the color design process.

The Metacognitive Demands and Opportunities of Generative AI   Lev Tankelevitch , Viktor Kewenig, Auste Simkute, Ava Elizabeth Scott, Advait Sarkar , Abigail Sellen , Sean Rintel   Generative AI systems offer unprecedented opportunities for transforming professional and personal work, yet they present challenges around prompting, evaluating and relying on outputs, and optimizing workflows. This paper shows that metacognition—the psychological ability to monitor and control one’s thoughts and behavior—offers a valuable lens through which to understand and design for these usability challenges.  

Honorable Mentions

B ig or Small, It’s All in Your Head: Visuo-Haptic Illusion of Size-Change Using Finger-Repositioning Myung Jin Kim, Eyal Ofek, Michel Pahud , Mike J. Sinclair, Andrea Bianchi   This research introduces a fixed-sized VR controller that uses finger repositioning to create a visuo-haptic illusion of dynamic size changes in handheld virtual objects, allowing users to perceive virtual objects as significantly smaller or larger than the actual device. 

LLMR: Real-time Prompting of Interactive Worlds Using Large Language Models   Fernanda De La Torre, Cathy Mengying Fang, Han Huang, Andrzej Banburski-Fahey, Judith Amores , Jaron Lanier   Large Language Model for Mixed Reality (LLMR) is a framework for the real-time creation and modification of interactive mixed reality experiences using LLMs. It uses novel strategies to tackle difficult cases where ideal training data is scarce or where the design goal requires the synthesis of internal dynamics, intuitive analysis, or advanced interactivity. 

Observer Effect in Social Media Use   Koustuv Saha, Pranshu Gupta, Gloria Mark, Emre Kiciman , Munmun De Choudhury   This work investigates the observer effect in behavioral assessments on social media use. The observer effect is a phenomenon in which individuals alter their behavior due to awareness of being monitored. Conducted over an average of 82 months (about 7 years) retrospectively and five months prospectively using Facebook data, the study found that deviations in expected behavior and language post-enrollment in the study reflected individual psychological traits. The authors recommend ways to mitigate the observer effect in these scenarios.

Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming   Hussein Mozannar, Gagan Bansal , Adam Fourney , Eric Horvitz   By investigating how developers use GitHub Copilot, the authors created CUPS, a taxonomy of programmer activities during system interaction. This approach not only elucidates interaction patterns and inefficiencies but can also drive more effective metrics and UI design for code-recommendation systems with the goal of improving programmer productivity. 

SharedNeRF: Leveraging Photorealistic and View-dependent Rendering for Real-time and Remote Collaboration   Mose Sakashita, Bala Kumaravel, Nicolai Marquardt , Andrew D. Wilson   SharedNeRF, a system for synchronous remote collaboration, utilizes neural radiance field (NeRF) technology to provide photorealistic, viewpoint-specific renderings that are seamlessly integrated with point clouds to capture dynamic movements and changes in a shared space. A preliminary study demonstrated its effectiveness, as participants used this high-fidelity, multi-perspective visualization to successfully complete a flower arrangement task. 

Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastination   Ananya Bhattacharjee, Yuchen Zeng, Sarah Yi Xu, Dana Kulzhabayeva, Minyi Ma, Rachel Kornfield, Syed Ishtiaque Ahmed, Alex Mariakakis, Mary P. Czerwinski , Anastasia Kuzminykh, Michael Liut, Joseph Jay Williams   In this study, the authors explore the potential of LLMs for customizing academic procrastination interventions, employing a technology probe to generate personalized advice. Their findings emphasize the need for LLMs to offer structured, deadline-oriented advice and adaptive questioning techniques, providing key design insights for LLM-based tools while highlighting cautions against their use for therapeutic guidance.

Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI Collaboration   Haotian Li, Yun Wang , Huamin Qu This paper evaluates data storytelling tools using a dual framework to analyze the stages of the storytelling workflow—analysis, planning, implementation, communication—and the roles of humans and AI in each stage, such as creators, assistants, optimizers, and reviewers. The study identifies common collaboration patterns in existing tools, summarizes lessons from these patterns, and highlights future research opportunities for human-AI collaboration in data storytelling.

Learn more about our work and contributions to CHI 2024, including our full list of publications , on our conference webpage .

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Dynavis: dynamically synthesized ui widgets for visualization editing, generative echo chamber effects of llm-powered search systems on diverse information seeking, understanding the role of large language models in personalizing and scaffolding strategies to combat academic procrastination, sharednerf: leveraging photorealistic and view-dependent rendering for real-time and remote collaboration, big or small, it’s all in your head: visuo-haptic illusion of size-change using finger-repositioning, llmr: real-time prompting of interactive worlds using large language models, reading between the lines: modeling user behavior and costs in ai-assisted programming, observer effect in social media use, where are we so far understanding data storytelling tools from the perspective of human-ai collaboration, the metacognitive demands and opportunities of generative ai, piet: facilitating color authoring for motion graphics video, continue reading.

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A Detailed Investigation of Exhaust System Design in High Performance Two-Stroke Engines 942515

The performance of two-stroke, high specific output engines, is largely dependent on the exhaust system. This paper describes an experimental study on the effect of each of the exhaust pipe sections on the actual engine performance. The exhaust system has been designed with interconnecting flanges that allow the various sections to be bolted together for testing on a dynamometer. This allows numerous combinations of various section designs to be evaluated. In an effort to understand the exact mechanisms involved in the pressure wave action within the engine, several pressure transducers have been located in the intake, crankcase, cylinder and exhaust.

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CFD Simulation and Validation of the Scavenging Process in a 125cc 2-Stroke Racing Engine

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Validation of a Computer Simulation of a High Performance Two-Stroke Motorcycle Racing Engine

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The Relationship Between Port Shape and Engine Performance for Two-Stroke Engines

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• Active workplace design: current gaps and future pathways
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• http://orcid.org/0000-0001-9384-5456 Mohammad Javad Koohsari 1 , 2 , 3 ,
• Andrew T Kaczynski 4 ,
• Akitomo Yasunaga 5 ,
• Tomoya Hanibuchi 6 ,
• Tomoki Nakaya 7 ,
• Gavin R McCormack 8 ,
• Koichiro Oka 2
• 1 School of Advanced Science and Technology , Japan Advanced Institute of Science and Technology , Nomi , Japan
• 2 Faculty of Sport Sciences , Waseda University , Tokorozawa , Japan
• 3 School of Exercise and Nutrition Sciences , Deakin University , Geelong , Victoria , Australia
• 4 Arnold School of Public Health , University of South Carolina , Columbia , South Carolina , USA
• 5 Faculty of Health Sciences , Aomori University of Health and Welfare , Aomori , Japan
• 6 Graduate School of Letters , Kyoto University , Kyoto , Japan
• 7 Graduate School of Environmental Studies , Tohoku University , Sendai , Japan
• 8 Department of Community Health Sciences , University of Calgary , Calgary , Alberta , Canada
• Correspondence to Dr Mohammad Javad Koohsari, Japan Advanced Institute of Science and Technology, Nomi, Japan; koohsari{at}jaist.ac.jp

https://doi.org/10.1136/bjsports-2024-108146

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• Public health
• Sedentary Behavior
• Health promotion

Introduction

Insufficient physical activity and excessive sitting time among office-based workers have been linked to various health risks and economic consequences. While health promotion interventions are important, the role of workplace design in encouraging active behaviours is increasingly recognised. However, significant gaps exist in knowledge about how workplace design influences these behaviours. This paper identifies the need to investigate the interactive effects of workplace norms and culture and the role of building layouts on workers’ behaviours, as well as the need for more accurate behavioural measures. Bridging these gaps is crucial for designing workplace interventions and promoting active, healthy and productive work environments.

Workplace design: encouraging movement in workplace settings

Existing gaps and future directions, interactive effects of workplace social environments.

Workplace social environments such as norms and culture can significantly influence sedentary behaviours among office-based workers 4 and can affect how workplace design influences workers’ behaviour. Most previous studies have tested the effects of workplace design on employees’ active and sedentary behaviours within Western contexts, 5 leaving a gap in how these relationships vary in other geographical settings with unique workplace norms and cultures. For instance, in a workplace where extended sitting is a cultural norm, employees may still predominantly engage in sedentary behaviour, regardless of having activity-promoting features in their workplace. Conversely, an activity-promoting environment might help mitigate norms towards sitting or even produce multiplicative positive effects in contexts where activity in the workplace is already customary. Conducting studies across varied geographical settings is necessary to identify similarities and differences in the impact of workplace norms and design on workers’ active and sedentary behaviours. Cross-cultural studies can shed light on the generalisability of findings and help develop customised interventions that address specific norms and cultural challenges. Future research can also employ mixed methods to gain a more thorough understanding of the complex interplay between workplace design, norms and culture, and employees’ behaviour. Additionally, the rise of home and hybrid working arrangements indicates that office social norms could extend to home work environments. For example, a culture of regular stretch breaks in the office might encourage similar practices at home, influencing physical activity behaviours remotely. Understanding the detailed relationship between workplace design, norms and employee behaviour is critical for developing targeted contextually relevant interventions that promote active workplace environments.

Precision in tracking workplace behaviours

Accurately measuring employees’ active and sitting behaviours and identifying the ‘locations’ where these behaviours occur is essential to understand their relationships with workplace design attributes. Global positioning systems (GPS) have been commonly used in combination with accelerometer devices to measure and spatially track people’s active and sedentary behaviour in outdoor environments, such as neighbourhoods and cities. 6 Nevertheless, GPS signals have limited accuracy or can be disrupted within indoor environments, resulting in less precise location data.

An indoor positioning system (IPS) can address the limitations of GPS in indoor environments. 7 IPS is a wayfinding technology that uses existing low-cost WiFi and Bluetooth to provide precise locations of individuals inside buildings. The IPS can be integrated with activity-tracking wearable devices, such as accelerometers, pedometers and heart rate monitors, as well as traditional methods like behavioural mapping. This integration allows for the collection of employees’ location data, movement patterns, activity intensities and other biometric data within workplaces. Additionally, the synergy between IPS and wearable devices effectively differentiates between occupational and leisure physical activities in workplaces. This distinction is key to better understanding the health paradox of the different health effects of these two types of physical activities. 8 Furthermore, with the growth of artificial intelligence (AI), there has been a unique opportunity to employ geospatial AI (GeoAI) in workplace environments and health research. GeoAI techniques aim to integrate innovations in spatial sciences with AI, particularly deep learning. 9 The joint application of IPS and GeoAI would enable precise location data of individuals within the workplace while using the power of spatial analysis. GeoAI can analyse workers’ movement patterns derived from IPS in combination with geospatial layers such as spatial layouts, access to common places, and light conditions. For instance, a GeoAI trained by tracking data on people’s movements in various indoor environments would predict people’s movements and derive estimates of the amount of sedentary behaviour of employed people only from planned indoor layout. This analysis allows for identifying hotspots or areas within the workplace where active and sedentary behaviour is prevalent.

Beyond individual design elements: exploring the influence of building layout on workplace behaviour

Most previous studies have primarily examined individual design elements but fail to consider how the overall spatial layout influences movement and behaviour. Building layout encompasses the spatial arrangement of building elements such as walls, doors, windows, and access ways, and plays a fundamental role in defining the functionality of interior spaces. Once a building layout has been established, making substantial alterations to it becomes challenging or, in some cases, impossible. Therefore, designing (and, if feasible, retrofitting) building interiors to promote health is imperative, but it is still unclear which workplace layouts are most supportive of workers’ active behaviours.

The urban design theory of space syntax has the potential to partially address this gap in knowledge. Space syntax uses a set of graph-based estimators to quantify spatial layouts. 10 It offers a framework to investigate the impact of building layout factors, such as workstation arrangement, common area location, and space accessibility, on workers’ movement patterns and behaviours. It goes beyond isolated design elements and considers the spatial configuration as a whole ( figure 1 ). Additionally, more research on ‘how’ people use and perceive their workspaces could complement the space syntax evaluations of building design.

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Space syntax examines building layouts as a whole, using the graph theory: (A)a schematic workplace layout, (B)space syntax axial lines (i.e., longest and fewest lines traversing all spaces) of the layout, and (C)the connectivity of all spaces based on the graph theory.

Conclusions

Future research should investigate the interactive effects of workplace norms and culture on behaviour and conduct cross-cultural studies to identify similarities and differences. Innovative measurement methods can also be employed to accurately measure behaviours and locations where those behaviours occur within workplaces. Additionally, exploring the influence of spatial layout, and using the urban design theory of space syntax, can offer valuable insights into the design of work environments that facilitate workers’ engagement in active behaviours.

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• Sugiyama T ,
• Eakin EE , et al
• Yoshikawa A ,
• Qiu L , et al
• Koohsari MJ ,
• Liao Y , et al
• Waters CN ,
• Chu AHY , et al
• Hadgraft N ,
• Clark BK , et al
• Katapally TR ,
• Pollard B ,
• Engelen L ,
• Held F , et al
• Holtermann A ,
• Hansen JV ,
• Burr H , et al
• Laden F , et al
• Hillier B ,

Contributors MJK conceived the idea and wrote the initial draft of the manuscript. All authors contributed to the writing and assisted with the analysis and interpretation. All authors have read and approved the final manuscript and agree with the order of the presentation of authors.

Funding MJK is supported by the JSPS KAKENHI (grant 23K09701). KO is supported by the JSPS Grants-in-Aid for Scientific Research program (grant 20H04113).

Competing interests None declared. In particular, none of the authors has a financial interest in the Space Syntax Limited company.

Provenance and peer review Not commissioned; externally peer reviewed.

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A Sharp Test for the Judge Leniency Design

We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed sharp test is asymptotically valid and consistent and will not make discordant recommendations. When the judge’s leniency design assumptions are rejected, we propose a way to salvage the model using partial monotonicity and exclusion assumptions, under which a variant of the Local Instrumental Variable (LIV) estimand can recover the Marginal Treatment Effect. Simulation studies show our test outperforms existing non-sharp tests by significant margins. We apply our test to assess the validity of the judge leniency design using data from Stevenson (2018), and it rejects the validity for three crime categories: robbery, drug selling, and drug possession.

Mourifie and Wan thank the support from the SSHRC Insight Grant #435190500. Hsu gratefully acknowledges the research support from the National Science and Technology Council of Taiwan (NSTC112-2628-H-001-001), the Academia Sinica Investigator Award of the Academia Sinica, Taiwan (AS-IA-110-H01), and from the Center for Research in Econometric Theory and Applications of National Taiwan University (Grant No. 113L8601). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Understanding External Validity and its Role in Research Design

This essay discusses external validity in scientific research and its significance in ensuring that study findings are applicable beyond specific experimental conditions. It examines how external validity helps researchers determine whether results can be generalized to different populations, settings, and contexts. The essay highlights challenges in achieving high external validity due to the specificity of research environments, participant characteristics, and timing. It also explains strategies like replication studies and field experiments that help increase the generalizability of results. The essay emphasizes the importance of balancing internal and external validity, acknowledging that while highly controlled studies can ensure internal accuracy, they might not reflect real-world conditions. Ultimately, external validity is crucial for producing research that informs effective policies, clinical guidelines, and societal changes.

How it works

Within the domain of scientific inquiry, the concept of external validity assumes paramount importance, serving as a linchpin for ensuring the relevance and broad applicability of research findings beyond the confines of a singular study. Put succinctly, external validity scrutinizes the extent to which the outcomes of a given investigation can be extrapolated to diverse populations, environments, temporal epochs, or contextual milieus. This conceptual framework assumes significance by bridging the chasm between meticulously controlled research settings and the kaleidoscopic intricacies of real-world scenarios, thereby furnishing researchers with the assurance that their conclusions possess trans-situational validity.

External validity assumes a pivotal role in buttressing the overall veracity of scientific inquiry, furnishing scientists with the means to discern whether their revelations hold substantive import and utility for wider swathes of humanity. Nonetheless, attaining elevated levels of external validity often presents an arduous undertaking owing to the idiosyncratic nature of experimental methodologies. Numerous investigations are conducted within controlled environs or with highly circumscribed samples to mitigate the influence of confounding variables, thereby complicating the process of extrapolating findings to disparate cohorts. For instance, a psychological study confined to the precincts of university campuses might furnish insights germane solely to that demographic stratum, precluding facile generalization to alternative age cohorts or cultural constellations.

Pivotal determinants impinging upon external validity encompass the demographic attributes of study participants, the ambient ambiance of experimental locales, and the temporal dynamics of data accrual. Researchers routinely resort to random sampling methodologies to obviate selection biases and assemble a heterogeneous cohort reflective of the broader populace. The ambient setting assumes salience as outcomes gleaned within sterile laboratory settings might not seamlessly transmute into real-world vicinities. Furthermore, external validity can be influenced by the temporal dimension of investigations, particularly when grappling with phenomena susceptible to temporal vicissitudes induced by cultural, economic, or technological flux.

Researchers endeavor to fortify external validity through recourse to replication studies, which seek to reproduce experimental paradigms under varying conditions to corroborate the robustness of findings. Engaging in multi-site investigations spanning disparate geographical realms or demographic constituencies also serves to validate the generalizability of findings across multifarious locales and participant profiles. Augmenting the verisimilitude of study designs by approximating real-world conditions more faithfully or deploying field experiments conducted within natural habitats constitutes an additional stratagem employed to enhance external validity.

Nonetheless, a judicious equilibrium between internal and external validity is indispensable. While internal validity safeguards against spurious attributions of causality by delineating the genuine effects attributable to independent variables as opposed to extraneous factors, an undue emphasis on this facet may inadvertently compromise external validity. For instance, a rigorously controlled laboratory investigation might succeed in eradicating most confounding variables but might concurrently engender an artificial milieu divorced from real-world veracity.

On occasion, external validity is consciously sacrificed to scrutinize a phenomenon within a specific subgroup or contextual milieu. Clinical trials, for instance, might pivot towards patients exhibiting highly circumscribed medical afflictions or demographic profiles. While such findings might lack broad generalizability, they furnish invaluable insights germane to the target demographic.

In summation, the salience of external validity cannot be overstated. Research endeavors endeavoring to inform policy formulation, clinical dictums, or societal transformations necessitate a degree of generalizability to obviate the formulation of recommendations that are ineffectual or even deleterious. Researchers ought to meticulously orchestrate their investigations, cognizant of the demographic cohorts and environmental terrains that their findings aspire to impact. By acknowledging and redressing the vicissitudes of external validity, scientists can engender more resilient and universally applicable research findings that withstand the rigors of real-world complexity.

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PapersOwl.com. (2024). Understanding External Validity and Its Role in Research Design . [Online]. Available at: https://papersowl.com/examples/understanding-external-validity-and-its-role-in-research-design/ [Accessed: 22 May. 2024]

"Understanding External Validity and Its Role in Research Design." PapersOwl.com, May 21, 2024. Accessed May 22, 2024. https://papersowl.com/examples/understanding-external-validity-and-its-role-in-research-design/

"Understanding External Validity and Its Role in Research Design," PapersOwl.com , 21-May-2024. [Online]. Available: https://papersowl.com/examples/understanding-external-validity-and-its-role-in-research-design/. [Accessed: 22-May-2024]

PapersOwl.com. (2024). Understanding External Validity and Its Role in Research Design . [Online]. Available at: https://papersowl.com/examples/understanding-external-validity-and-its-role-in-research-design/ [Accessed: 22-May-2024]

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