bluuebunny/crossref_metadata_2025 huggingface dataset:
A fotografia negra contemporânea em exposições de arte brasileiras
Authors: Rabelo Elson de Assis
Published: April 2023

Neste texto, procuro responder à questão sobre como a fotografia produzida por pessoas negras têm adentrado os espaços expositivos de arte no Brasil nos últimos anos. Tomo textos de catálogos e outros documentos de exposições de grande visibilidade, para procurar situar os critérios através dos quais as imagens produzidas por fotógrafos negros têm ocupado as mesmas instâncias que as imagens feitas por fotógrafos brancos sobre grupos e pessoas negras. Essa mudança tenta responder às demandas dos grupos sociais afrodescendentes por novas narrativas sobre seu protagonismo na sociedade brasileira e na diáspora negra, como forma de enfrentamento das desigualdades raciais que estruturam, inclusive, as relações entre os agentes sociais, as instituições e a História da Arte.
A Thorough Investigation of Various Goals and Responses for Mobile Software-Defined Networks
Authors: Sahu Somesh Kumar , Chandra J.  , Muloor Kiran , Samanta Debabrata
Published: April 2023

Cloud computing has caused some companies to modify their IT infrastructure and maintenance procedures and may eliminate their current hardware altogether. Conventional methods of setting up a switch or router may be error-prone and unable to make full use of the capabilities of current network architectures. As many intelligent networking designs as possible must be developed for intellectualization, activation, and customization in future networks. Due to software-defined networking (SDN) technology, it's possible to control, secure, and optimize network resources, eliminating the rigid coupling between the control plane and the data plane in traditional network architectures. Here, the chapter explores the problems, difficulties, and potential solutions associated with software-defined networks (SDN), a novel concept in computer networking. Through SDN, the network gains the ability to be programmable, quick, and adaptable thanks to its separation of data and its ability to control traffic.
Knowledge, attitudes and practices on healthy lifestyle related behaviours among trainees of youth training centres in Sri Lanka
Authors: Mataraarachchi Dilini , Vithana P. V. S. C. , Lokubalasooriya Ayesha , Jayasundera Chamanthi , Anton Suranutha , De Silva Chithrammalee
Published: April 2023

Introduction: The adolescent and youth health module has been introduced to the youth training centres in 2017.
Objectives: To assess the knowledge, attitudes and practices on healthy lifestyle-related behaviours including healthy eating practices, physical activity and substance misuse among youth trainees attached to youth training centres in Sri Lanka
Methods: A descriptive cross-sectional study was carried out among a sample of 425 youth trainees aged 15-29 years from six youth training centres selected using simple random sampling technique, using a pre-tested self-administered questionnaire. Scoring system was developed for measuring knowledge, attitude and practices on healthy behaviour and percentage scores were presented with median and inter quartile range (IQR). Associated factors for accepted levels were identified using Chi-squared Test or Fisher’s Exact Test.
Results: All 425 participants responded. Majority (n=365; 85.9%) were Sinhalese, while 355 (83.6%) were Buddhists. Mean age was 18.6 years (SD=1.82). Most (n=344; 80.9%) were living in their own homes. Median percentage scores for knowledge, attitudes and practices on healthy lifestyle-related behaviours were 65.2 (IQR: 52.2, 69.6), 33.3 (25.0, 50.0) and 58.5 (48.1, 66.0), respectively. A majority, 80.7% (n=243) had an acceptable level of knowledge and 72.7% (n=309) an acceptable level of practice. Only 16.0% (n=68) had accepted level of attitudes. Youth trainee’s ethnicity, religion, age, education level and participation in the youth health module training were significantly related to their knowledge in healthy lifestyle-related behaviour (p<0.05). However, none of these were significantly associated with trainee’s attitudes on healthy behaviours although a significantly higher percentage of older youth were found to have healthy attitudes towards healthy behaviour.
Conclusions & Recommendations: It is recommended to revise the training module, focusing more on attitudinal change with regards to the healthy lifestyle related behaviours. Delivery of the youth health module in both Sinhala and Tamil languages needs to be looked into.
University Health Risk Behaviour (UniHRB) Inventory (Sinhala): a tool to assess common health risk behaviours among undergraduates in Sri Lanka
Authors: Fayaz Fazla , Nilaweera Irosha , Samaranayake Dulani , Cassim Riyas
Published: April 2023

Introduction: The degree of health risk behaviour (HRB) among undergraduates has not been researched extensively in Sri Lanka and there is no tool available to assess common HRBs in a university setting.
Objectives: To develop, translate and validate a tool to measure common HRBs in Sinhalese second-year undergraduates in Sri Lanka
Methods: The UniHRB-Inventory (Sinhala) was developed using a seven-step design process for tool development. An extensive literature review, nine key informant interviews (KII), and five focus group discussions (FGD) were carried out. A combination of deductive and inductive methods was used to define the domain and identify the questions to assess. Content and consensual validity was assessed using the modified Delphi process. A validation study was conducted among 666 second-year undergraduates at the University of Kelaniya selected using stratified-cluster sampling. Construct-validity of UniHRB-Inventory-Sinhala was assessed using Principal Component Analysis (PCA) (n=333), Confirmatory Factor Analysis (CFA) (n=333), multi-trait scaling analysis and convergent validity assessment (n=80). Internal consistency and test-retest reliability was assessed in a sub-sample (n=25).
Results: There has been a deficit of choices for adapting an HRB tool for undergraduates in Sri Lanka. Violence and injuries, sexual risk behaviours, addictions to mobile phones and the internet are common among undergraduates. Students’ dismissive attitude towards violence and neglecting health behaviours, such as sleep deprivation and poor hygienic practice, were highlighted as important aspects of HRBs. The UniHRB-Inventory (Sinhala) with 70 items showed good face, content and consensual validity. A seven-factor model was identified through PCA, which was confirmed through CFA. UniHRB-Inventory domains and sensation seeking scale (SSS) total score showed correlations between 0.39-0.67. Cronbach’s alpha coefficient of 0.77 and test-retest reliability coefficients of seven domains ranging between 0.74-0.82 indicated high reliability.
Conclusions & Recommendations: The newly developed UniHRB -Inventory (Sinhala) is a valid and reliable tool to assess common HRBs among undergraduates in Sri Lanka.
The development of a tool to identify skilled meditators among meditation practitioners - ‘The University of Colombo Intake Interview to identify Skilled Meditators for scientific research (UoC-IISM)’
Authors: Outschoorn N. O. , Somarathne E. A. S. K. , Dasanayaka N. N. , Karunarathne L. J. U. , Vithanage K. K. , Dalpatadu K. P. C. , Lokupitiya E. , Gunathunga M.W. , Herath H. M. J. C. , Jayasinghe S. , Dissanayake W. D. N.
Published: April 2023

Introduction: Buddhist-derived meditation is a well-known phenomenological practice that enhances overall wellbeing of individuals. However, broad- and less-rigorous criteria in recruiting suitable meditation practitioners affect the reliability of results obtained through meditation research.
Objectives: To develop an instrument to identify skilled meditators among meditation practitioners, in order to use it in scientific research including medical research conducted to understand the physiological, psychological, social, and environmental effects of meditation
Methods: Extensive literature reviews, interviews and focus group discussions with experts in a number of related fields were utilized in developing the instrument. Judgmental validation of the generated items was ensured through establishing their face, content and consensual validity. Internal consistency reliability and factor structure of the scale were explored to analyse its psychometric properties. Cut-off marks were determined to develop a scoring system for the instrument.
Results: Twenty-five items were categorized under five sections (A, B, C1, C2, D) that addressed six factors: duration of the meditation practice, details of the meditation practice, peripheral awareness, stable attention, and alertness and emotional stability. Three further qualitative items were added under section E. An exploratory factor analysis process resulted in a two-factor structure between the Likert-scale items as theoretically expected. Scores to identify ‘skilled meditators’ were determined as: Section C1>7 (fall-back score; 7-9, ideal score; 10-12), Section C2>14 (fall-back score; 14-16, ideal score; 17-20) and Section D>25 (fall-back score; 25-29, ideal score; 30-35).
Conclusions & Recommendations: The overall findings reveal the UoC-IISM to be a valid and reliable tool to be used in identifying skilled meditators, among meditation practitioners, for scientific research in the Sri Lankan context. The instrument explores six factors through its 28 items and the importance of using a combination of these factors is discussed.
Active life and the role of community design
Authors: De Silva Weliange Shreenika
Published: April 2023

No abstract available
Assessing the knowledge, attitude and practice (KAP) measures against tuberculosis in patients in the ambulatory department facilities in Pakistan: a cross-sectional analysis
Authors: Ahmad Shoaib , Khawaja Uzzam Ahmed , Haider Syed Meeran , Mowlabaccus Wafaa binti , Mohan Anmol , Ansari Asad , Ahmad Muhammad , Garg Tulika , Ahmed Hafsa , Ahmad Shkaib , Essar Mohammad Yasir , Perez-Fernandez Javier , Yatzkan George D.
Published: April 2023

Tuberculosis (TB), at present, is the leading infectious aetiology of death globally. In Pakistan, there are approximately 510,000 new cases annually, with more than 15,000 of them developing into drug resistant TB, making the nation the fifth leading country in TB prevalence in the world. Due to the ongoing COVID-19 pandemic, focus has drifted away from TB screening, diagnostic, health awareness campaigns and therapeutic measures endangering KAP (knowledge, attitude and practices) towards TB in our population. We conducted a cross-sectional descriptive study in Pakistan to assess the knowledge, attitude and practices of Pakistani residents attending the adult outpatient departments of public hospitals for any health-related concern. Our sample size was of 856 participants, with a median age of 22 years. Occupation-wise, those who were employed had better knowledge of TB than those who were unemployed [odds ratio (OR): 1.011; 95% CI :1.005-1.8005]. No differences were observed in TB knowledge between those adherents to common preventive practices versus not adherent (OR 0.875, 95% CI: 0.757-1.403). More than 90 % of participants agreed that TB is dangerous for the community and a majority opted against stigmatising TB patients (79.1%). People who could read and write were 3.5 times more likely to have a good attitude towards TB compared to those who could not (OR: 3.596;95% CI: 1.821–70.230; p=0.037). Similarly, employed subjects had better attitude compared to unemployed ones (p=0.024), (OR: 1.125; 95% CI: 0.498, 1.852) and those having better knowledge of TB had a better attitude grade (OR:1.749; 95% CI: 0.832–12.350), p=0.020). Age, occupation, and educational status were statistically significant among the two groups (p=0.038, p=0.023, p=0.000) respectively. Literate subjects had thrice good practice towards TB than illiterate (OR: 3.081; 95% CI: 1.869–4.164; p=0.000). Future education and awareness programs should target specific groups such as the unemployed and illiterate with practice-focused approaches. Our study outcomes can enable the concerned officials and authorities taking appropriate evidence-based steps to direct the efforts in an efficient manner to curtail the burden of TB in Pakistan and to limit its progression that could potentially lead our nation to become an MDR-TB endemic territory.
Holistic Design Approach of Rocker Arm in Aluminum, Sheet Metal & Plastic Materials for Heavy Duty Commercial Application
Authors: Yaser K U  Syed Taj
Published: April 2023

Diesel engines are known for their excellent low-end torque, better drivability, performance, and better fuel economy. The increase in customer demands pushes to deliver higher power and torque along with fuel economy. This requirement puts a great challenge on the overall weight of the engine. This paper explains the holistic approach followed along with optimizing the rocker arm cover to achieve the weight target without compromising on durability and cost in the commercial segment 2.5-liter Diesel Engine.

This paper presents a complete overview of the design and development of Rocker Arm (RA) cover to meet Strength, Durability, NVH and Aesthetic in Commercial Engine where base design is in aluminum which is mounted on cylinder head with a separate breather system. From aluminum the base design of Rocker arm cover is optimized to sheet metal where in there is reduction of 43% in weight and cost saving of 13%. The proposed design is optimized to meet the durability, NVH and without compromising on functional aspects for mounting the separate breather system.

Further it was optimized such that separate breather system is integrated with rocker arm cover and the base cover is converted to plastic. As the cover is converted to plastic and the internal components of breather system (Fleece, Baffles, PRV, etc.) which aid in oil separation can be welded onto the base plastic. This reduces the assembly cost, no of bolts, cycle time. Optimized plastic RA Cover reduced the weight by 34% against sheet metal proposal along with separate breather system and 53% against aluminum metal proposal along with separate breather system. In addition, there is cost saving of approx. 40% against sheet metal proposal and 46% against aluminum proposal. Both the sheet metal and plastic proposals are optimized to meet the desired functional targets like oil separation, blow by efficiency and durability targets without any failure in simulation, vehicle durability and final proposal is good aesthetic as it is in plastic.
Freevalve: A Comparative GWP Life Cycle Assessment of E-fuel Fully Variable Valvetrain-equipped Hybrid Electric Vehicles and Battery Electric Vehicles
Authors: Elmagdoub Abdelrahman W. M. , Simaitis Joris , Halmearo Mattias , Carlson Urban , Turner James , Brace Chris , Akehurst Sam , Zhang Nic
Published: April 2023

Throughout its history, the internal combustion engine has been continuously scrutinized to achieve strict legislative emission targets. With the dawn of renewable fuels fast approaching, most Internal Combustion Engine (ICE) equipped hybrid electric vehicles (HEVs) face difficulty in adjusting their precise control strategies to new fuels. This is partly due to constrained limitations associated with camshaft-induced design-point air induction limitations. Freevalve is a fully variable valvetrain technology enabling independent control of valve lifts, durations, and timings. Additionally, the added degrees-of-freedom enable the capability to shut-off individual engine valves, optimizing combustion performance and stability through specific speed ranges. By design, it minimizes the existing breathing-related constraints that are currently hindering the extraction of the higher efficiency potential of ICEs. To explore the potential environmental benefits from improved fuel consumption and emissions, this study conducts a comparative global warming potential life cycle assessment on a HEV-configured Freevalve ICE vehicle against battery electric vehicles (BEVs) and camshaft-induced HEVs. Throughout this work, particular consideration is given to the lifecycle impact of Freevalve technology to reason its performance and efficiency gains in new generation powertrains. This is accomplished through a separate LCA study based on system bill of materials and estimated production energy usage. Additionally, the work evaluates current global average energy mixes and futuristic energy scenarios based on European projections to assess the impact of renewable energy and alternative methods of direct air capture (DAC) e-fuel production on total global warming potential (GWP) lifecycle impact. Under the fully renewable energy and fuel production scenarios, for a lifetime of 150,000 km, results suggested that e-fuel Freevalve HEVs have a net cycle GWP impact 55% lower than BEVs. Similar conclusions are observed for the global average grid case where a 50% reduction is observed in favour of the e-fuel Freevalve HEV compared to the BEV. This led to suggest that Freevalve-equipped engines coupled with next generation renewable fuels and dedicated hybrid concepts have significant potential in addressing environmental concerns and achieving global net zero CO2 emission targets.
Machine Learning Based Approach for Prediction of Hood Oilcanning Performances
Authors: Srinivasan Arunkumar , S Aravamuthan , Madhurya Bellamkonda , S Kangde Suhas
Published: April 2023

Computer Aided Engineering (CAE) simulations are an integral part of the product development process in an automotive industry. The conventional approach involving pre-processing, solving and post-processing is highly time-consuming. Emerging digital technologies such as Machine Learning (ML) can be implemented in early stage of product development cycle to predict key performances without need of traditional CAE. Oil Canning loadcase simulates the displacement and buckling behavior of vehicle outer styling panels. A ML model trained using historical oil canning simulation results can be used to predict the maximum displacement and classify buckling locations. This enables product development team in faster decision making and reduces overall turnaround time. Oil canning FE model features such as stiffness, distance from constraints, etc., are extracted for training database of the ML model. Initially, 32 model features were extracted from the FE model. Domain expertise and variable selection techniques were implemented to clean up the database for dependencies and duplicates. This resulted in identification of 21 key parameters for training the ML model. Database for buckling classification model is highly skewed with only 5% data points with buckling. Synthetic data is generated using SMOTE algorithm to overcome data imbalance. These features are then used to train and validate the ML model for buckling. Predictive model developed using Extreme Gradient boosting (XG Boost) algorithm with R2 more than 90% for training and test datasets. It predicted maximum displacement with 20% error for 80% test data points. Also, buckling data points are classified with 98% accuracy. Prediction made using the ML model is in good agreement (< 20% error) with CAE results. This resulted in substantial time savings from 11 days to 30 minutes for the prediction of key performances.
The Automated Radio Measurement System (ARMS) for Characterizing Broadband Performance of Transmitters and Receivers
Authors: Burnham Karen
Published: April 2023

Accurate prediction of RF interference (RFI) requires high fidelity measured data. There are many ways transmitters can interfere with receivers. The output spectrum of transmitting radios is made up of the fundamental signal, harmonics, spurious emissions, and broadband noise. Receiving radios are capable of detecting extremely low-level signals in their pass band, but can also be sensitive to signals outside the pass band such as mixer products and spurious responses. Manual measurements to obtain this data is very time consuming, especially when the radios can operate over hundreds or thousands of channels. This paper discusses an Automated Radio Measurement System (ARMS) that can accurately perform these broadband measurements with high dynamic range.
Data Collection for Incident Response for Vehicles with Autonomous Systems
Authors: Rayno Mars , Span Trae , Brown Weston , Daily Jeremy
Published: April 2023

First responders and traffic crash investigators collect and secure evidence necessary to determine the cause of a crash. As vehicles with advanced autonomous features become more common on the road, inevitably they will be involved in such incidents. Thus, traditional data collection requirements may need to be augmented to accommodate autonomous technology and the connectivity associated with autonomous and semi-autonomous driving features. The objective of this paper is to understand the data from a fielded autonomous system and to motivate the development of requirements for autonomous vehicle data collection.

The issue of data ownership and access will be discussed. Additional complicating factors, such as cybersecurity concerns combined with a first responder’s legal authority, may pose challenges for traditional data collection. These additional challenges pose an opportunity to develop standardized event recording and embedded software verification processes to provide sufficient data to replace firsthand vehicle operator accounts in autonomous vehicles. For this work, an autonomous mobile impact attenuator vehicle system was used to gather data that may appear from potential crash incidents. Data obtained from a combination of vehicle data from the J1939 networks, a precision GPS system as a truth source, and the onboard autonomy sensor logs for the attenuator vehicle was analyzed for completeness and usefulness in describing the incident that occurred. Findings indicate a shift in technique and strategy is needed for incident data collection for autonomous vehicles. Potential issues in the duration of the recording are also presented and discussed.
Analysis of Roadway and Tire Evidence Resulting from Aggressive Braking Maneuvers with ABS-Equipped Motorcycles
Authors: Peck Louis R. , Rubio Eloy , Doria Andre , Husher Stein , Shuman Karl
Published: April 2023

With ABS-equipped motorcycles becoming more pervasive, it is critical for collision reconstructionists to have a firm understanding of what evidence may be generated during aggressive braking events performed with these braking systems. To develop a better understanding, thirty-one instrumented braking tests were performed and are reported in this study. Three different surfaces using three current ABS-equipped motorcycles were used to study the residual visible roadway and tire evidence resulting from hard braking events involving front-only, rear-only, and maximum effort braking maneuvers. Data from these tests were analyzed to determine the resultant deceleration, which serves to add updated data to the current body of knowledge.

The majority of braking tests did not generate visible roadway evidence. Specifically, conventional public roadway surfaces exhibited no evidence of braking until the motorcycles reached very low speeds. One surface, a residential roadway with a recently applied chip seal, repeatedly displayed evidence of braking in the form of subtle, light discolorations. Conversely, all test runs produced distinct circumferential speckling on the braked tire(s) that was accompanied by localized tread abrasion when intermittent locking occurred. The average decelerations achieved during the braking maneuvers were -0.42 g, -0.80 g, -0.88 g for rear-only, front-only, and both brake configurations, respectively. These findings demonstrate modern ABS-equipped motorcycles are not likely to generate discernible roadway evidence as result of a hard braking event and highlight the need to promptly document the tires of a motorcycle involved in a collision, as the tire offers the most reliable evidence of hard braking.
Estimation of the Tire-Road Interaction Forces by using Pacejka’s Formulas with Combined Slips and Camber Angles
Authors: Marotta Raffaele , Ivanov Valentin , Strano Salvatore , Terzo Mario , Tordela Ciro
Published: April 2023

The growing market demand for highly automated and autonomous vehicles and the need to equip vehicles with ever higher standards of comfort, safety and performance requires knowledge of physical quantities that are often difficult or expensive to measure directly. The absence of direct sensors, the difficulty of implementation, and their cost have led researchers to identify alternative solutions that allow estimating the physical quantity of interest by aggregating other available information. The interaction forces between tire and road are among the most significant. Given that the dynamics of a vehicle are strongly linked to the forces exchanged between the tire and the road, their knowledge is fundamental in the development of control systems aimed at improving performance in terms of handling, road holding or comfort. This paper presents a new technique for the estimation of tire-road interaction forces based on the integration of models and measures. A Central Difference Kalman filter was applied to a Double Track Model. The non-linear Kalman filter allowed us to handle the non-linearity of the system. The tire-road interaction was modelled through Pacejka's magic formulas that into account the combined longitudinal and lateral slips and the camber angle. This version made it possible to carry out complex and realistic manoeuvres. The realized estimator also considers the influence of lateral and longitudinal load transfers and aerodynamic forces in the three spatial directions. The Camber angle used in this observer was estimated through neural networks. The measures used are longitudinal velocity, yaw rate, longitudinal slip and wheel steering angles.
The Honda Automotive Laboratories of Ohio Wind Tunnel
Authors: Best Scott , Bari Ghazi , Brooker Tyler , Flynt Guy , Walter Joel , Duell Edward
Published: April 2023

The Honda Automotive Laboratories of Ohio (HALO) includes a new aeroacoustic wind tunnel located near Marysville, Ohio that started operations in 2022. This facility provides world-class aerodynamic flow quality and acoustic testing capabilities for the development of both passenger and motorsports vehicles.

This closed-return ¾ open jet wind tunnel features a two-position flexible nozzle system with cross sections of 25 m2 and 18 m2, providing wind speeds of up to 250 km/h and 310 km/h, respectively. There is a ±180 degree turntable with boundary layer control systems, and interchangeable single belt and 5-belt moving ground plane (MGP) modules. Extensive applications of acoustic treatment in the test section and throughout the wind tunnel circuit provide a hemi-anechoic test environment and low background noise levels. A temperature control system provides uniform and stable air temperature over an operating environment between 10 °C and 50 °C.

The primary instrumentation of the wind tunnel includes the wind speed, temperature, and humidity measurement systems, a 6-component force balance integrated within the turntable, and an acoustic test system (ATS). The ATS includes four planar microphone arrays for external measurements and a spherical microphone array and binaural heads for internal measurements. A flow survey traverse system equipped with a 4-D probe holder mechanism is capable of placing a probe anywhere within the test volume.

The HALO facility includes the wind tunnel control room, secure vehicle preparation bays and office spaces for segregated customers, and a vehicle frontal and side area measurement system.

This paper provides an introduction to the HALO wind tunnel testing capabilities, design features and development, and the results of the aeroacoustic commissioning program. The background noise level and flow quality characteristics are provided.
An Ultra-Light Heuristic Algorithm for Autonomous Optimal Eco-Driving
Authors: Rabinowitz Aaron I. , Motallebiaraghi Farhang , Meyer Rick , Asher Zachary , Kolmanovsky Ilya , Bradley Thomas
Published: April 2023

Connected autonomy brings with it the means of significantly increasing vehicle Energy Economy (EE) through optimal Eco-Driving control. Much research has been conducted in the area of autonomous Eco-Driving control via various methods. Generally, proposed algorithms fall into the broad categories of rules-based controls, optimal controls, and meta-heuristics. Proposed algorithms also vary in cost function type with the 2-norm of acceleration being common. In a previous study the authors classified and implemented commonly represented methods from the literature using real-world data. Results from the study showed a tradeoff between EE improvement and run-time and that the best overall performers were meta-heuristics. Results also showed that cost functions sensitive to the 1-norm of acceleration led to better performance than those which directly minimize the 2-norm. In this paper the authors present an ultra-light heuristic method for generating optimal Eco-Driving traces for Connected Autonomous Vehicles (CAVs) which indirectly minimizes the 1-norm of acceleration. This novel method produces EE improvements in line with previously implemented meta-heuristic methods while executing in a fraction of the time.
Data-driven Trajectory Planning of Lane Change Maneuver for Autonomous Driving
Authors: Yoon Youngmin , Yi Kyongsu
Published: April 2023

This paper presents a methodology of trajectory planning for the surrounding-aware lane change maneuver of autonomous vehicles based on a data-driven method. The lateral motion is planned by sampling candidate patterns which are defined based on quintic polynomial functions over time. Based on the cost evaluation among the sampled candidates, the optimal lateral motion pattern is selected as a reference and tracked by the controller. The longitudinal motion is planned and controlled using Model Predictive Control (MPC) which is an optimal control method designed considering the surrounding traffic information. To realize the lane change motion similar to the human driving behavior in the surrounding traffic situation, the human driving pattern is modeled in the form of motion parameters and considered in planning the lateral and longitudinal motion. The motion parameters related to the lane change motion are estimated based on the host vehicle states and surrounding vehicle states, and reflected in the optimization of the lateral and longitudinal motion. The estimator of the motion parameters is constructed using a multi-layer neural network which is designed as a regression function. The neural network is trained using real-world motion information related to the lane change maneuver. The proposed trajectory planning algorithm has been validated via simulation tests in which the dynamic traffic environment is reconstructed. The simulation results show that the proposed trajectory planning algorithm secures collision safety and ride quality in multi-vehicle traffic environment. Also, the motion characteristics induced by the proposed algorithm are shown to be consistent with human driving patterns.
A Method for Building Vehicle Trajectory Data Sets Based on Drone Videos
Authors: Wang Zhenyu , Yu Zhuoping , Tian Wei , Xiong Lu , Tang Chen
Published: April 2023

The research and development of data-driven highly automated driving system components such as trajectory prediction, motion planning, driving test scenario generation, and safety validation all require large amounts of naturalistic vehicle trajectory data. Therefore, a variety of data collection methods have emerged to meet the growing demand. Among these, camera-equipped drones are gaining more and more attention because of their obvious advantages. Specifically, compared to others, drones have a wider field of bird's eye view, which is less likely to be blocked, and they could collect more complete and natural vehicle trajectory data. Besides, they are not easily observed by traffic participants and ensure that the human driver behavior data collected is realistic and natural. In this paper, we present a complete vehicle trajectory data extraction framework based on aerial videos. It consists of three parts: 1) objects detection, 2) data association, and 3) data cleaning. In particular, considering that the hovering drone can be approximated as a fixed camera, we propose an improved object detection algorithm based on classical image processing algorithms. It overcomes the shake effects of drone-based aerial videos and can be directly applied to the automatic detection of moving vehicles without manual annotation data. The output of the algorithm is the vehicle rotated bounding box information with high accuracy, including vehicle center position, vehicle heading, and vehicle dimension. In addition, the improved detection algorithm can be used for vehicle object automatic annotation.
High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application
Authors: De Ojeda William , Wu Simon (Haibao)
Published: April 2023

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. The study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.
Numerical Simulation of Ethanol-Based Fuels in an F1 Power Unit
Authors: Reeves Nick , Samuel Stephen
Published: April 2023

Formula (1) vehicles have transitioned from E5 to E10 fuel for the 2022 season to reduce carbon emissions and by 2026 the vehicles are required to use 100% sustainable fuels. The aim of this paper is to identify the operating envelope of the F1 power unit for E10-E100 fuel and the resulting emission levels for these fuel compositions using numerical simulations. To achieve this aim an F1 engine model has been developed in GT-Suite with reference to the FIA 2022 Technical Regulations. The combustion model has been validated using data obtained from literature relating to laminar and turbulent flame speed, friction and heat transfer characteristics within the combustion chamber. One of the main challenges of using ethanol-based fuels is the increased levels of formaldehyde in the tailpipe. This paper presents the operating window for achieving the optimum engine performance with ethanol fuel blends ranging from the current E10 to E100, in keeping with the current 2022 FIA F1 regulations and beyond 2026 where all fuel must be fully sustainable. The study showed that the estimated formaldehyde levels from 2026 Formula (1) engine is significantly higher than the current emission levels of automotive vehicles. This paper highlights the required regulatory changes to ensure the engine out aldehyde emissions meet WHO air quality standards.
Fatigue Behaviour of Thin Electrical Steel Sheets at Room Temperature
Authors: Tolofari Tamuno-Ibim , Behravesh Behzad , Saha Dulal , Chen Jim , Mills Marie , Zhang Wensheng , Lamonaca Gianni , Jahed Hamid
Published: April 2023

Electrical steel, also known as silicon steel, is a ferromagnetic material that is often used in electric vehicles (EVs) for stator and rotor applications. Since the design and manufacturing of rotors require the use of laminated thin electrical steel sheets, the fatigue characterization of these single sheets is of interest. In this study, a 0.27mm thick non-oriented electrical steel sheet was tested under cyclic loading in the load-controlled mode with the load ratio R = 0.1 at room temperature. The specimens were prepared using the Computer Numerical Control (CNC) machining method. The Smith-Watson-Topper mean stress correction was used to find the equivalent fully reversed stress-life (S-N) curve. The Basquin equation was used to describe the fatigue strength of the electrical steel and the fatigue parameters were extracted. Furthermore, a design curve with a reliability of 90% and a confidence level of 90% was generated using Owen’s Tolerance Limit method. The fracture mechanisms under cyclic loading were also studied using a scanning electron microscope. Crack initiation was determined to initiate from one edge and propagate to the other. Although the fracture mechanism was transgranular, the fracture surface displayed distinct regions of fatigue damage and cleavage fracture. The presence of aluminium nitrate precipitate particles contributing to crack initiation was confirmed using the energy dispersive x-ray spectroscopy technique.
Calculation of Cooling Fan Blade Deformation and Aerodynamic Performance Based on Fluid-Structure Model
Authors: Zhou Zijian , Lin HuiBin , Shangguan Wenbin , Wang Xinling , Duan Yaolong
Published: April 2023

Considering the interaction between fan blades and the surrounding air when a cooling fan rotates, the Fluid-Structure Interaction (FSI) model of the fan is established, and flow rate, static pressure, efficiency versus speed of the fan are calculated and analyzed. The aerodynamic performance of the fan is carried out, and the measured performance parameters are compared with calculated to validate the developed model. Using the established model, the performance of fans with different rotating speeds, diameters and blade installation angles is calculated. The effects of fan speed, diameter and blade installation angle on blade deformation and aerodynamic performance are studied. It is showed that: (1) Stress and deformation on the fan blade surface have changed greatly considering the FSI effect, and the maximum stress and deformation of blades have increased; (2) Because of the uneven aerodynamic pressure, deformation of blade tips at the leading edge decreases, while deformation of the blade tip at the trailing edge increases, which reduces the blade tip installation angle; (3) If fan speed and diameter are increased, blade deformation increases, and the difference of aerodynamic performance before and after blade deformation increases; if the installation angle is increased, the static pressure of the fan increases firstly and then decreased. If the blades of a fan are deformed, the installation angle and the static pressure of the fan are decreased.
Research on Control Strategy of Hierarchical Architecture Based on Drive-by-Wire Chassis
Authors: Wang Zixu , Zheng Hongyu , Zong Changfu , Kaku Chuyo
Published: April 2023

The rapid development of city traffic makes the driving conditions faced by vehicles increasingly complex. The drive-by-wire chassis vehicle has the characteristics of four-wheel independent steering, four-wheel independent drive and four-wheel independent braking, which has become a current research hotspot because that can meet various complex working conditions. However, it is precisely because of the high degree of controllability of the drive-by-wire chassis that the research on the control strategy has become difficult. In this paper, an integrated control strategy based on the hierarchical algorithm framework is designed for the drive-by-wire chassis vehicle, which includes a centralized control layer, a tire force distribution layer and an actuator control layer. The centralized control layer is based on the model predictive control algorithm, which takes the vehicle longitudinal speed, lateral speed and yaw rate as the control objectives, and solves the total longitudinal force, total lateral force and total yaw moment required by the vehicle. The tire force distribution layer assigns the control objectives to the four wheels, which adopts the optimal control method to transform the tire force distribution problem into a quadratic programming problem, and solves the problem with the tire utilization efficiency as the optimization objective to obtain the longitudinal force and lateral force of each wheel. The actuator control layer obtains the wheel angle and driving torque through the tire inverse model. The performance with the proposed strategy is demonstrated by steering wheel angle step input simulation test under the condition of low road friction coefficient which compared with the direct yaw moment control algorithm. In order to further verify the effectiveness of the strategy under various driving conditions, a simulation test of the sine input of steering wheel angle was carried out to verify that the strategy can improve the driving stability of the vehicle under various driving conditions.
Influence of Wheel Wake on Vehicle Aerodynamics: An Eddy-Resolving Simulation Study
Authors: Krüger Louis , Joksimovic Ivan , Wegt Sebastian , Burgbacher Johannes , Kuthada Timo , Wittmeier Felix , Hussong Jeanette , Wagner Andreas , Jakirlic Suad
Published: April 2023

A computational study of the vehicle aerodynamics influenced by the wake of the rotating wheel taking into account a detailed rim geometry is presently performed. The car configuration corresponds to a full-scale (1:1) notchback configuration of the well-known ‘DrivAer’ vehicle model, Heft et al. [1]. The objective of the present work is to investigate the performance of some popular turbulence models in conjunction with different methods for handling the wheel rotation – rotating wall velocity, ‘multiple reference frame’ and ‘sliding grid algorithm’. The specific focus hereby is on a near-wall RANS eddy-viscosity model based on elliptic-relaxation, sensitized to resolve fluctuating turbulence by introducing a specifically modeled production term in the scale-supplying equation, motivated by the Scale-Adaptive Simulation approach (SAS, [2]), proposed by Krumbein et al. [3]. All relevant model equations have been implemented in the OpenFOAM® Code, with which all simulations are performed. The results interpretation includes the instantaneous and time-averaged flow properties in terms of the velocity and pressure fields characterizing the underlying flow topology, the integral aerodynamic force coefficients, and finally the POD (Proper Orthogonal Decomposition) analysis, which allows to detect most energetic spatially-independent coherent structures.
Identification of Driver’s Braking Intention in Cut-In Scenarios
Authors: Li Jingyuan , Sun Yingbo , Liu Yahui , Ji Xuewu
Published: April 2023

Accurate identification of driver’s braking intention is essential in advanced driver assistance system and can make the driving process more comfortable and trustworthy. In this paper, a novel method for driver braking intention identification in cut-in scenarios was proposed by using driver’s gaze information and motion information of cut-in vehicles. Firstly, a "looking in and looking out" experimental platform including three eye-tracking cameras and one front-view camera was built to collect driver's gaze information and the vehicle motion information. Secondly, driver’s gaze features and motion features of cut-in vehicles were selected and the braking intention identification performance of several decision tree-based ensemble learning algorithms was compared. Thirdly, the feature importance was analyzed by using SHAP (SHapley Additive exPlanations) values. This novel method of braking intention identification makes full use of in-vehicle camera sensors. The signal acquisition method is non-intrusive and can be applied to real-world driving.
Research on Crack Detection Method of Self-Piercing Riveting
Authors: Wang Kun , Zhan Zhenfei , Xu Hailan
Published: April 2023

Compared with traditional welding, self-piercing riveting technology has unique advantages and is widely used in automobile lightweight technology. The riveting quality of self-piercing riveting is closely related to the safety and durability of automobiles. The detection of riveting quality has gradually become an important part of the automobile manufacturing process. The generation of surface cracks under self-piercing riveting will affect the riveting strength, which in turn affects the riveting quality. Therefore, the detection of riveting external quality is transformed into the detection of riveting surface cracks. The existing artificial vision-based riveting lower surface crack recognition technology is inefficient, subjective and cannot be applied on a large scale. Therefore, this paper will propose a local-overall strategy based on image processing and computer vision. Firstly, three sub-image crack recognition networks based on extreme learning machine and feature extraction are constructed. Considering that the crack recognition network based on feature extraction has a large room for improvement in accuracy and the limitation of feature description operator on image expression, two sub-image crack recognition networks based on convolutional neural network are constructed. Then based on the traversal search algorithm, four representative full-size images are used to show the detection effect of different crack recognition models. The final results show that the crack recognition network based on convolutional neural network has the best detection effect.
Engine O-Rings Produced Using Additive Manufacturing
Authors: Luning-Prak Dianne , Baker Brad , Cowart Jim
Published: April 2023

Additive Manufacturing (AM) using stereolithography (SLA) was applied to produce engine O-rings using two different flexible polymer printing materials, Flex 80A and Elastic 50A. Print orientation of the O-ring in the SLA 3D printer is important, with the horizontal configuration most commonly providing for the smoothest final O-ring printed surface due to the lack of printing support tabs required. AM printing tabs lead to O-ring ‘marks’ (non-smooth surfaces) that were evaluated using the Society of Automotive Engineers SAE AS871B standard. It was seen that numerous printing approaches produced ‘marks’ that were larger than acceptable, which shows that these studied AM processes can not replace traditional methods of O-ring manufacture. However, further evaluation was pursued to explore possible remote emergency usage of these O-rings.

Printed O-rings were next tested-soaked in engine related fluids in order to characterize O-ring swelling behavior. Volume swelling was greatest with acetone (100% plus increase) for both the stock O-rings tested and moderately less so with the 3D printed O-rings. Flex 80A printing material swelling was moderately less than using Elastic 50A printing material. Swell testing using motor oil and engine fuels showed significantly less swelling with volume change increases on the order of ten to fifteen percent. Pressure vessel and engine-based testing was also performed with the printed O-rings demonstrating good performance (no leaks) under operation, suggesting that shorter term emergency-based operation using these AM printed O-rings may be acceptable.