Browse Topic: Statistical analysis

Items (2,293)
This study aimed to evaluate the influence of child anthropometry, seating postures (recline and rotation), seatbelt force limiting, and frontal collision scenarios on the kinematic response and injury risk in highly automated vehicles. The TUST IBMs 6YO-O model was conducted the frontal collisions in sled tests. This simulation matrix includes five percentiles six-year-old occupants (P3, P25, P50, P75, and P97), three seatback angles (20°, 30°, and 45°), four seat rotation angles (0°, 90°, 180°, and 270°), three seatbelt force limiting (2.6 kN, 3.6 kN, and 4.6 kN), and three frontal collision types. Injury risks were assessed including the child occupant's head, neck, chest/abdomen, and lumbar region in each simulation (n=540). The results indicate that the child anthropometry, the seatback angle, and the seat rotation angle have a significant influence on the motion responses. Statistically significant differences between all the groups within each independent variable category were
Wang, YanxinZhao, HongqianLi, HaiyanHe, LijuanCui, ShihaiLv, Wenle
Wet-gap crossings, which involve moving military forces across rivers and other water obstacles, remain among the most difficult operations to plan and execute. These maneuvers are complicated by choke points, fast-flowing water, and the exposure of forces and equipment to enemy fire. Despite these challenges, wet-gap crossings are critical to maintaining operational momentum during large-scale combat operations. This study examines doctrinal approaches to wet-gap crossings and explores the relationship between these operations and observed vehicle losses in the Russia-Ukraine War. Using a mixed-method approach, the analysis integrates daily operational reports from the Institute for the Study of War with visually confirmed equipment loss data from Oryxspioenkop. A custom Wet-Gap Relevance Score (WGRS) was developed using Natural Language Processing techniques to quantify the degree to which each ISW report focused on crossing operations. Statistical analysis shows that pontoon losses
Lynch, BenjaminDosan, LoganMittal, Vikram
The present study investigates optimization of ultimate tensile strength (UTS) in FSW of AA2024-T3 and SS304 in a butt joint configuration. An L18 mixed-level orthogonal array was used to design 18 experiments, varying tool rotational speed (450, 560, and 710 rpm), traverse speed (20, 25, and 40 mm/min), and pin offset (1 and 1.5 mm toward the Al side). The tool rotational speed had the greatest influence on UTS, contributing nearly one-third of the total variance, followed by pin offset and traverse speed. The optimal combination, 450 rpm, 20 mm/min, 1.5 mm offset, yielded a UTS of 344.7 MPa and a joint efficiency of 78.3%. At this setting, peak temperatures reached ~356 °C, ensuring sufficient plasticization and uniform mixing of the Al–SS interface, producing a refined stir zone with an average grain size of 4.2 μm. Fracture analysis revealed ductile failure at the optimal parameters, whereas suboptimal conditions resulted in brittle or mixed fractures due to either insufficient or
Mir, Fayaz AhmadKhan, Noor ZamanPali, Harveer Singh
Despite advances in crash avoidance, occupant restraint systems remain crucial in protecting the motoring public. Following decades of improvement in occupant protection, including several supplemental restraint systems for front seat occupants, the safety of rear seat occupants has recently undergone scrutiny. Studies evaluating rear seat occupant injury risk via field crash data have reported reduced relative safety in rear seating positions and alluded to advanced rear seat restraints, such as pretensioners and load limiters, as potential solutions. While the pursuit of novel technologies has historically improved occupant outcomes, evaluation of new systems in both controlled laboratory environments and field crashes is necessary to understand potential consequences of widespread introduction. This study analyzed the prevalence of advanced seat belts (load limiters and pretensioners) in the rear seating positions in the U.S. fleet. Additionally, occupant injury risk was compared
Rapp van Roden, Elizabeth AnnMiller, BrucePearson, JosephWilliamson, JamesBrown, Thomas
Design for durability in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality are rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for durability testing that accurately match the wide variations in real-world roads and driving. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing road response metrics like Vibration Dose Value (VDV) and statistical estimates of vehicle speed and acceleration. Data collected at the proving grounds on gravel roads, smooth roads, city-like roads
Shaurya, ShubhamRamakrishnan, SankaranDemiri, AlbionKhapane, Prashant
Sparse Stream DETR 3D object detection has become pivotal in autonomous driving, and previous methods achieve remarkable performance by aggregating temporal information, which also face a balance problem of precision and efficiency. Knowledge distillation offers a promising solution to enhance the efficiency of a small model without incurring computational overhead; however, previous methods lack the exploration of the Temporal Distillation knowledge for the DETR detector. This paper designs a novel Temporal DETR Query Guidance paradigm to impart temporal relation knowledge from a powerful teacher model to enable the student to associate object states across time, leverage historical context. The teacher’s queries grasp the temporal knowledge through self-attention, and the backbone uses the EVA-02 large-scale image model. The student utilizes the teacher's self-attention layer and its own learnable queries to compute the attention as its guidance and mimics the feature interaction
Yan, Yixiong
As motorsports evolve with technological advancements, aerodynamics plays a crucial role in race car performance. This review examines the impact of aerodynamics on car design and its evolution, presenting a statistical analysis of existing sports cars. We highlight key performance factors like engine power, top speed, drag, and weight. The key contribution of this review is the critical synthesis of the safety-performance trade-off, especially linking aerodynamic optimizations to the stability and safety of sports cars. Furthermore, we explore mathematical modeling of vehicle aerodynamics to enhance the understanding of performance aspects such as top speed, acceleration, cornering, and braking. This article also provides a review of recent active and passive aerodynamic devices to assist researchers in selecting designs, with an emphasis on the importance of ground effect. We also present recent numerical methods, particularly 3D simulations. The statistical data can help researchers
Eftekhari, HesamAl-Obaidi, Abdulkareem Sh. MahdiEftekhari, Shahrooz
Pedestrians are among the most vulnerable participants in traffic, particularly when crossing the road. Extensive research has been conducted globally on the yielding behavior analysis of vehicle–pedestrian interaction and the design of automatic vehicle braking systems to mitigate pedestrian casualties. However, few studies have comprehensively addressed lateral risks using implicit kinematic cues in pedestrian–vehicle interactions. Moreover, the design of collision avoidance systems has rarely taken into account driving behavior, along with the pedestrian’s kinematics and crossing behavior. This article presents a human-like automatic braking fuzzy control strategy for pedestrian–vehicle collision avoidance, combining the advantages of professional driver emergency braking behavior and kinematic interaction cues. First, a high-fidelity driving simulator is used to investigate the yielding behavior of pedestrian–vehicle interaction when pedestrians cross the road. Second, the
Zhang, WenyanHuang, XiaorongSun, ShuleiFu, KairongXiong, QingHuang, Haibo
The purpose of this study was to evaluate the thoracic responses of the 50th-percenitle male Hybrid III, THOR, and post mortem human surrogates (PMHS) in the rear seat during frontal sled tests using conventional and advanced restraints in multiple vehicle environments. Twenty-one sled tests were conducted using the Hybrid III and THOR in seven vehicle bucks, and 12 PMHS sled tests were performed using four vehicle bucks. Trends in chest deflections between vehicles and restraint conditions were compared between surrogates. The Hybrid III and THOR thoracic injury risk predictions were compared to the thoracic skeletal damage observed during the PMHS tests. The Hybrid III chest deflections were statistically significantly greater for vehicles equipped with conventional restraints compared to those equipped with advanced restraints. The THOR chest deflections generally followed this trend, but the differences between restraint types were not statistically significant. Hence, the THOR
Albert, Devon L.Bianco, Samuel T.Guettler, Allison J.Boyle, David M.Kemper, Andrew R.Hardy, Warren N.
This document addresses AS8879 thread inspection issues relating to selection, usage and capability of gages. It addresses the selection of calibrated measurement gages, the need for defined quality metrics, the methodology of determining the appropriate guardband factors, and the minimum inspection requirements for single element pitch diameter gages. Users of this document shall apply the information described herein for the evaluation of the capability of their measurements based on the measurement consumer risk. It involves the analysis of the measurement (product) distribution and biases of both the product and measurement system distributions. It protects the consumer from the worst case distribution results. A whitepaper has been developed to provide supporting documentation and the rationale used in the development of this standard. This whitepaper will be published by the SAE as an Aerospace Information Report (AIR6553). This document recommends the use of ASME B1.2 “Gages and
E-25 General Standards for Aerospace and Propulsion Systems
The number of female drivers in India is increasing alongside the rapid growth of the Indian automotive industry. A driving comfort survey conducted among female drivers revealed that many of them experienced discomfort when wearing safety belts—while driving and as front-seat passengers. This discomfort is primarily due to a phenomenon referred to as “neck cutting.” The root cause of neck cutting is likely related to vehicle design, which is traditionally based on Anthropometric Test Devices (ATD’s) representing the 5th, 50th & 95th percentile (%tile) of the global population. However, a literature review indicated that the anthropometric dimensions of the Indian populations are generally smaller than those of the global for the respective candidate. To validate the neck-cutting issue, various female candidates were asked to sit in the Driver’s seat for physical measurements trials. Accordingly, methodology was developed to quantify neck cutting parameters objectively. A correlation
Kulkarni, Nachiket AChitodkar, Vivek VEknath Chopade, SantoshMahajan, RahulYamgar, Babasaheb S
In the area of structural durability testing using servo hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieved better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process making it time-consuming and resource-intensive. To address this challenge, an application has been develop to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run facilitating a comprehensive review of signal deviations. Each test run is having thousands of drive files based on road-load mix and actuator settings. This application helped us in significantly optimizing the simulation workflow by reducing
Soni, YashKatake, VrishaliMullapudi, DattatreyuduChaskar, Mithun
The automotive industry is undergoing a significant technological transformation, which is continually impacting the methods used to test the functionalities, delivered to end consumer. This includes the ever-growing need to embed software-based functions to support more and more end user functionality, while at the same time retaining existing and well-established functions, all within short development timelines. This presents both opportunities and challenges, with greater potential for reuse or leverage of test assets, although the actual percentage of leverage on real world projects is practically less than anticipated for a multitude of reasons. This paper collates the various factors which effect the practical leverage of test assets from one project to another, including various workflows and the interaction across components amongst applications lifecycle management systems. Alongside, it describes the current practices of basis analysis in isolation in combination with
Venkata, ParameswaranKulkarni, ApoorvaRAJARAM, SaravananGanesh, Chamarthi
The paper aimed to improve the accurate quantification of driver drowsiness and to provide comprehensive, evidence-based validation for a Vision-Based Driver Drowsiness and Alertness Warning System. Advanced quantification of driver drowsiness is designed to enhance distinction of true positive events from False Positive and False Negative events. Methodology to pursue this included assessing inputs such as facial features, driver visibility, dynamic driving tasks, driving patterns, driving course time and vehicle speed. The system is programmed to actively learn Eye Aspect Ratio (EAR) reference and adapt personalised EAR threshold value to process EAR frames against the learnt threshold value. This method optimized the data frames to enhance the evaluation and processing of essential frames, thereby reducing delays in the processor and the Human-Machine Interface (HMI) warning module. Comprehensive validation is systematically conducted within a controlled test track environment to
Balasubrahmanyan, ChappagaddaAkbar Badusha, A
Vehicle interior noise is a crucial assessment criterion for automotive NVH. It has a significant effect on customer opinions about the quality of a vehicle. Articulation Index (AI) is one of the key sound metrics used to describe speech intelligibility and quantifies the middle and high frequency spectra associated to the internal noise of vehicle. In reality, Vehicle operating under dynamic condition experiences various air-borne noise sources such as tire rolling noise, powertrain noise, intake-exhaust noise & wind noise along with structure borne excitations such as powertrain vibrations, suspension vibrations. It is very challenging to predict cumulative effect of all these excitations to interior noise level and Articulation Index (AI) of vehicle over complete frequency range. The statistical energy analysis (SEA) is a well-known methodology being used to simulate & predict mid & high frequency noise. Objective of this paper is to present the process of development of a SEA
Doijad, Vishwajit PadmakarBillade, DayanandApte, Sr., Amol ArunShewale, AmolKothapalli, Brahmananda Reddy
Focusing on drivers in Hong Kong, this paper analyzes how social media usage contributes to inattentive driving and the associated safety consequences. Data were collected using a questionnaire-based survey and analyzed through chi-square tests, Fisher’s exact tests, and Cramér’s V effect size calculations to examine the relationships between demographic and driving-related factors—including gender, age group, education level, driving experience, and self-rated driving skills—and the level of high-risk perception. The findings reveal that gender, age, experience, and Self-assessed driving ability significantly influence drivers’ perception of high-risk situations. Furthermore, significant interaction effects were observed among these variables, indicating that they do not operate in isolation but rather interact to shape risk perception. For example, middle-aged and older female drivers with higher education levels and extensive driving experience demonstrated a heightened perception
Dong, JinhaiYe, HaochengCui, ZihengChen, Yang
In vehicle development, occupant-centered design is crucial to ensuring customer satisfaction. Key factors such as visibility, access, interior roominess, driver ergonomics, interior storage and trunk space directly impact the daily experience of vehicle occupants. While automakers rely on engineering metrics to guide architectural decisions, however in some cases doesn’t exist a clear correlation between these quantitative parameters and the subjective satisfaction of end users. This study develops a methodology which addresses that gap by proposing the creation of quantitative satisfaction curves for critical engineering metrics, providing a robust tool to support decision-making during the early stages of vehicle design. Through a combination of clinics, research, and statistical analysis, this project outlines a step-by-step process for developing (dis)satisfaction curves, offering a clearer understanding of how dimensions like headroom, glove box volume, and A-pillar obscuration
Santos, Alex CardosoSilva, GustavoBenevente, RodrigoPadua Silva, AntonioLourenço, Sergio RicardoAndrade, Cecilia NavasSobral, Piero
Traditional traffic millimeter-wave radar can obtain the distance, speed, and azimuth angle of the vehicles driving on road plane, while lacking the elevation information of the targets which is an important feature in spatial dimension for vehicle type classification. In this paper, the statistical methods are used to analyze the elevation features of different vehicle types acquired by 4D millimeter-wave radar in actual road scenario. The statistical parameters of the overall elevation data and cross-section elevation data at different horizontal distances are calculated. Besides, the probability distributions and the skewness characteristics are further presented. The data analysis results show that there are significant differences in elevation probability distribution and skewness features between small and large vehicles, providing evidence for classification of different vehicle types using 4D millimeter-wave radar.
Jing, MengyuanLiu, HaiqingGong, XiaolongGuo, Fuyang
As a crucial part of national strategic resources, petroleum is an important basic material for economic development. However, during the storage, loading and unloading, and transportation of bulk liquid petroleum products, unavoidable natural losses occur due to factors such as process technology and equipment. Therefore, studying the natural loss of liquid petroleum during storage and transportation, and adopting effective countermeasures to minimize the natural loss of liquid petroleum, has become a topic of focus in various fields. This paper uses the “Loss of Bulk Liquid Petroleum Products” approved in 1989 as the analysis standard to explore the natural loss of highway oil transportation, conduct statistical test analysis on oil data such as oil collection registration forms, and propose conclusions and suggestions, thereby providing a reference for the revision of oil loss standards. The experimental results show that the overall oil data meets the national standard for natural
Li, BixinLi, JilaiJin, Shifeng
To address the challenges of balancing detection accuracy and real-time performance in complex traffic scenarios for vehicle-mounted embedded platforms and road monitoring, this paper proposes YOLOv10n-FTAS, an optimized lightweight detection framework based on YOLOv10n. The main innovations include: (1) Designing a C2f-Faster-EAMA module in the backbone network that enhances feature representation through channel-spatial cooperative attention mechanisms; (2) Proposing a novel statistics-enhanced attention mechanism (Token Statistics-enhanced PSA, TS-PSA) by integrating Token Statistics Self-Attention; (3) Constructing a Dynamic Sample-Attention Scale Fusion module (DS-ASF) that achieves multi-scale feature fusion through deformable convolution and adaptive sampling strategies; (4) Adopting Shape-IoU loss function with geometric constraints to optimize bounding box regression. Experimental results demonstrate: The improved model reduces parameters and computations to 5.5M and 5.8G
Niu, JigaoJin, Kunming
Belt-positioning booster seats (BPBs) help promote proper seat belt fit for children in vehicles. The effectiveness of BPBs depends on occupant posture, which can be influenced by BPB design features. This study aimed to quantitatively describe how children's postures naturally change over time in BPBs, using pressure mats. Thirty children aged 5 to 12 participated in two 30-minute trials using randomly assigned seating configurations. Five configurations were studied by installing two backless BPBs in vehicle captain’s chairs, varying booster profile (high, low, or no BPB) and armrest presence (with or without BPB/vehicle seat armrests). TekScan 5250 pressure mats were placed on the seating surfaces. Children began in an ideal reference posture, and center of force (COF) data were collected continuously. Additional observations on posture, behavior, and comfort were periodically collected. Mixed models, including effects of seating configuration, time, and volunteer characteristics
Connell, RosalieBaker, Gretchen H.Mansfield, Julie A.
Accurate defect quantification is crucial for ensuring the serviceability of aircraft engine parts. Traditional inspection methods, such as profile projectors and replicating compounds, suffer from inconsistencies, operator dependency, and ergonomic challenges. To address these limitations, the 4D InSpec® handheld 3D scanner was introduced as an advanced solution for defect measurement and analysis. This article evaluates the effectiveness of the 4D InSpec scanner through multiple statistical methods, including Gage Repeatability and Reproducibility (Gage R&R), Isoplot®, Youden plots, and Bland–Altman plots. A new concept of Probability of accurate Measurement (PoaM)© was introduced to capture the accuracy of the defect quantification based on their size. The results demonstrate a significant reduction in measurement variability, with Gage R&R improving from 39.9% (profile projector) to 8.5% (3D scanner), thus meeting the AS13100 Aerospace Quality Standard. Additionally, the 4D InSpec
Aust, JonasDonskoy, Gene
In-Use emission compliance regulations globally mandate that machines meet emission standards in the field, beyond dyno certification. For engine manufacturers, understanding emission compliance risks early is crucial for technology selection, calibration strategies, and validation routines. This study focuses on developing analytical and statistical methods for emission compliance risk assessment using Fleet Intelligence Data, which includes high-frequency telematics data from over 500K machines, reporting more than 1000 measures at 1Hz frequency. Traditional analytical methods are inadequate for handling such big data, necessitating advanced methods. We developed data pipelines to query measures from the Enterprise Data Lake (A Structured Data storage system), address big data challenges, and ensure data quality. Regulatory requirements were translated into software logic and applied to pre-processed data for emission compliance assessment. The resulting reports provide actionable
Arya, Satya PrakashShekarappa, Kiran
Tillage, a fundamental agricultural practice involving soil preparation for planting, has traditionally relied on mechanical implements with limited real-time data collection or adjustment capabilities. The lack of real-time data and implement statistics results in fleet managers struggling to track performance, driver behavior, and operational efficiency of the implements. Lack of data on vehicle performance can result in unexpected breakdowns and higher maintenance costs, ensuring compliance with regulations is challenging without proper data tracking, potentially leading to fines and legal issues. Bluetooth-enabled mechanical implements for tillage operations represent an emerging frontier in precision agriculture, combining traditional soil preparation techniques with modern wireless technology. Implement mounted battery powered BLE (Bluetooth Low Energy) modules operated by solar panel based rechargeable batteries to power microcontroller. When Implement is operational turns
Kaniche, OnkarRajurkar, KartikGokhale, SourabhaVadnere, Mohan
This paper introduces a comprehensive solution for predictive maintenance, utilizing statistical data and analytics. The proposed Service Planner feature offers customers real-time insights into the health of machine or vehicle parts and their replacement schedules. By referencing data from service stations and manufacturer advisories, the Service Planner assesses the current health and estimated lifespan of parts based on metrics such as days, engine hours, kilometers, and statistical data. This approach integrates predictive analytics, cost estimation, and service planning to reduce unplanned downtime and improve maintenance budgeting, aligning with SAE expectations for review-ready manuscripts. The user interface displays current part health, replacement due dates, and estimated replacement costs. For example, if air filter replacement is recommended every six months, the solution uses manufacturer advisories to estimate the remaining life of the air filter in terms of days or
Chaudhari, Hemant Ashok
In today’s competitive landscape, industries are relying heavily on the use of warranty data analytics techniques to manage and improve warranty performance. Warranty analytics is important since it provides valuable insights into product quality and reliability. It must be noted here that by systematically looking into warranty claims and related information, industries can identify patterns and trends that indicate potential issues with the products. This analysis helps in early detection of defects, enabling timely corrective actions that improve product performance and customer satisfaction. This paper introduces a comprehensive framework that combines conventional methods with advanced machine learning techniques to provide a multifaceted perspective on warranty data. The methodology leverages historical warranty claims and product usage data to predict failure patterns & identify root causes. By integrating these diverse methods, the framework offers a more accurate and holistic
Quadri, Danishuddin S.F.Soma, Nagaraju
The reliability of vehicle steering systems is extremely important to ensure safety, vehicle performance and gain customer satisfaction. Life data analysis conducted to analyze how the steering systems are performing in the field and assess whether the steering systems can meet the reliability target when deployed in the field. This article discusses about the systematic process to conduct the field data analysis of Hydraulic Powered Steering System (HPS) from the warranty claim data, usage of Weibull distribution to derive the life characteristic parameters. Based on the process described in this article, the statistical analysis of the warranty claim data performed and identified that, “the Hydraulic Power Steering Gears demonstrated more than 99% reliability in the field with statistical confidence of 90% and able meet the ZF’s Internal target for the HPS Systems”.
Ravindran, MohanSugumar, Ganesh
This paper presents measurement results of emissions and fuel economy on real-world driving of two-wheelers in India using a state-of-the-art FTIR PEMS technology. The study aimed to characterize the emissions profiles of a small motorcycle under typical Indian driving conditions, including congested urban traffic and highway driving. This is the continuation of the study conducted previously on bigger motorcycle using gas analyzer [1], with necessary adaptations to suit the specific conditions of Indian roads and traffic. Key parameters such as NOx, CO, CO2 and Fuel consumption were measured during real-world driving cycles and comparison is done with standard WMTC emission testing cycle. The findings of this study provide valuable insights into the actual on-road emissions of two-wheelers in India, which can be used to develop more accurate emission models and guide the development of cleaner and more efficient two-wheeler technologies. Key Considerations: Specifics of Indian Driving
Agrawal, RahulJaswal, RahulYadav, Sachin
The current automotive development cycle is becoming shorter and shorter, therefore research is needed to improve the efficiency of wind noise transient calculation. This article summarizes 14 internal and external factors that affect the efficiency and accuracy of transient analysis of wind noise, and uses the ULH algorithm to design DOE for these 14 factors. A total of 200 efficiency improvement schemes are generated, and transient analysis is conducted on each of the 200 schemes. The simulation results and calculation time of wind noise inside the vehicle are statistically analyzed. And aerodynamic acoustic wind tunnel tests were conducted to verify this, with the optimization objectives of simulation values approaching 86.1 AI% (experimental values) and shortened calculation time. NSGA-II algorithm was used to optimize and obtain five sets of efficiency combination schemes that meet the requirements. Develop five appearance feature schemes for areas such as A-pillar and rearview
Li, XiangliangZhang, XiangdongLiu, XuelongWang, HaiyangHuang, Zhongyuan
In contemporary global commerce, swift advancements are observed within the maritime transportation sector. The frequency of seafaring voyages increases apace, from which it is discerned that navigational safety emerges as an indispensable concern. Paramount to safeguarding vessel operations and diminishing the susceptibility to maritime mishaps has become the integration of ship domain models. Through incorporation of AIS datasets alongside mathematical statistical evaluations melded with insights derived from ship captains, this discourse introduces a novel risk domain paradigm tailor-made for ships. The curated data amalgamated with maritime captaincy was stratified and overlayered, utilizing techniques such as the maximum density method juxtaposed with least squares calculation to ascertain the periphery defining the ship’s risk precinct. This newly conceived model interweaves aspects of ship maneuverability in concert with evasion protocols predicated on extant ship domain models
Xiong, JuntingZhang, YongChen, XiaofengMeng, FanjunZhang, Junpeng
The effectiveness of fare collection systems (FCS) plays a critical role in ensuring operational efficiency and passenger convenience in public rail transit, including Metro Rail Transit Line 3 (MRT-3). However, the current contactless smart card-based FCS faces challenges such as technical malfunctions, long queues, and limited payment options. While modernization efforts focus on automated payment solutions, passenger acceptance remains a key determinant of its successful adoption. This study examined the demographic and preference-based factors affecting FCS adoption using a two-phase approach: statistical association tests assessed demographic influences, while Partial Least Square - Structural Equation Modeling (PLS-SEM) evaluated behavioral predictors. Findings revealed that income level and frequency of use are the strongest predictors of FCS preference, highlighting economic constraints and travel habits as key factors in its adoption. The PLS-SEM results revealed that
de Ocampo, Randel BorisEstores, Gilford
The United States Environmental Protection Agency (US-EPA) requires nitrogen oxides (NOx) measurement using Chemiluminescent Detectors (CLDs), Non-dispersive Ultraviolet (NDUV), and Zirconia Oxide (ZrO2) analyzers, as outlined in the 40 CFR Part 1065. Quantification of NO2 by CLD requires dual-CLDs; one dedicated to measuring the NO and another coupled with a NO2-to-NO converter to measure the total NOx. Measurement by using dual-CLDs involves mathematically subtracting NO from total NOx to get NO2 information. This requires perfect time alignments of both CLDs assigned for measuring NO and NOx to maintain accurate NO2 calculations. The NO2-to-NO converters can degrade over time and need to be replaced to get accurate total NOx measurement. In this study, Infra-red Laser Absorption Modulation (IRLAMTM) technology, which is an advanced QCL-IR spectroscopy proposed in the previous study [1], is used to measure NO and NO2 simultaneously in the exhaust gas of light-duty vehicles. This
Rahman, MontajirNevius, TimIsrael, JoshuaHara, KenjiNagura, Naoki
Knowledge of real-world driving behavior is fundamental to the development of drive systems. The derivation of representative requirements or driving cycles for use case-specific vehicle use allows a customer-centered drive system design. These datasets contain data such as distance, standstill times, average accelerations or a customer driving style estimation. In addition, the real-world data can be used for regulatory purposes such as the definition of utility factors or the definition of real driving emission cycles. In a research project funded by FVV e.V., we have developed a universal database software including data storage, user interface and general data plausibility functions for real driving data. The database contains detailed time series measurement data on component and vehicle level such as torque and speed of electric motors and internal combustion engines as well as general mobility data such as driving distance statistics. A key objective of the database development
Sander, MarcelSturm, Axel WolfgangMartínez Medina, ÓscarHenze, RomanKühne, UlfEilts, Peter
With ongoing microelectronic supply chain issues, the demand for genuine field-programmable gate arrays (FPGAs) is increasing – but so is the occurrence of counterfeit devices. Frequently, devices are used, salvaged from old systems, and repackaged as new. Recycled devices represent the largest class of counterfeit devices and are becoming more rampant with ongoing supply chain challenges. Therefore, it is often necessary to test whether a device is genuine before employing it in a new system. Current methods for evaluating devices are frequently destructive allowing for only small sample testing within lots. Other methods require complex external equipment and cannot be readily deployed throughout the supply chain. Graf Research Corporation has developed a methodology for using soft sensor telemetry bitstreams to characterize an FPGA device and subsequently classify whether a device is a repackaged counterfeit via statistical and machine learning models. The new method utilizes
Batchelor, WhitneyCrofford, CodyKoiner, JamesWinslow, MargaretTaylor, MiaPaar, KevinHarper, Scott
A statistical method for analyzing momentum deflection angles of fuel injectors based on Computational Fluid Dynamics (CFD) simulation of the internal nozzle flow is proposed. This method is especially relevant for large marine two stroke engines where the spray is often deflected due to an eccentric and asymmetric design of the internal injector geometry. Unsteady Reynolds-Averaged Navier-Stokes (URANS) CFD simulations are employed to analyze the internal flow of different cavitating injectors which have four and five nozzle holes, respectively, for a 50 cm bore and a 95 cm bore dual-fuel engine operating on methanol. The in-nozzle flow dynamics vary from one to another significantly. The use of the statistical analysis on the distribution of deflection angles at the fuel nozzle hole exit further assists at explaining differences in measured surface temperatures of the exhaust valve bottom and piston bowl. The corrected spray angles obtained from these in-nozzle simulations also serve
Quist, Nicolai ArentMatlok, SimonPang, Kar MunNorman, Thomas SchaldemoseMayer, StefanWalther, Jens Honoré
In this article, a three-dimensional transient CFD simulation method is used to simulate the wind noise of a vehicle model’s external flow field. The transient noise excitation of external noise sources outside each window glass are analyzed, and the statistical energy analysis method is used to calculate the articulation index of the front and rear passenger inside the vehicle. Then, the variation range of the thickness of each window glass is set, and the side window glass is also divided into two types: single-layer glass and laminated glass. After the design parameters are defined, the design space is established. The articulation index of the front and rear passengers and the total weight of the glass are the three design objectives for multi-objective optimization simulation, based on the results of optimization simulation, the change trend of each design parameter and design objective is analyzed; the sensitivity of the design objective to each design parameter is studied; the
Xiong, ZhenfengZhang, XiaoLiu, PingLi, BoYuan, QingpengChen, ShiwenTo, Chi Hin
Gears are essential components in industrial machinery, and their design needs to be optimized to ensure the proper functioning of mechanical systems across various industrial applications. In this study, an optimization approach is proposed to determine the optimal design of a spur gear. This approach is based on an improved Jaya algorithm, which features a straightforward formulation without any algorithm-specific control parameters. Utilizing a simple and parameter-free updating mechanism, the strength of this algorithm lies in its iterative ability to enhance candidate solutions by moving them toward the best solution while avoiding the worst one, providing a flexible framework for optimization. However, since the original Jaya algorithm was primarily designed for continuous optimization problems, this research incorporates adjustments to adapt it effectively for mixed-variable optimization problems and to manage multi-objective functions. The effectiveness of the proposed
Rezki, InesFerhat, DjeddouHamouda, AbdelatifAbderazek, Hammoudi
Experimental testing in automotive development sometimes relies on ad hoc approaches like ‘One Factor at a Time’, particularly in time- and resource-limited situations. While widely used, these approaches are limited in their ability to systematically capture parameter interactions and system complexities, which poses significant challenges in safety-critical applications like high-voltage battery systems. This study systematically investigates the factors influencing thermal runaway in lithium-ion battery cells using a statistical full-factorial experimental design. Key parameters, including state of charge, cell capacity and heating trigger power, have been analyzed under controlled conditions with an autoclave setup, enabling precise measurement of thermal and mechanical responses. The use of automotive-grade lithium-ion cells ensures relevance for next-generation applications. By employing factorial regression and statistical analysis, the study identifies critical temperatures
Ceylan, DenizKulzer, André CasalWinterholler, NinaWeinmann, JohannesSchiek, Werner
While many individual technical descriptors exist to quantify and describe different kinds of acoustic phenomena, they each only describe the technical aspects of a sound itself without considering any additional non-acoustic context. Human perception, however, is greatly informed by this context. For example, humans have different expectations for the sound of an electric razor than they do for an internal combustion engine, despite both objects being able to be described by sound pressure level or a measure of roughness. No single technical descriptor alone works in all contexts as a gold standard which objectively determines whether a sound is “good.” Jury tests, however, are a great aid towards gaining a measure of this context. When seeking to effectively quantify the sound quality of a device, it is necessary to combine the perceptive information from the results of a jury test alongside one or more technical descriptors in order to provide a meaningful method of evaluation. The
Thiede, Shane
As India’s economy expands and road infrastructure improves, the number of car owners is expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines. Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development
Rai, NiteshMehta, MakrandRavindran, Mugundaram
A good Noise, Vibration, and Harshness (NVH) environment in a vehicle plays an important role in attracting a large customer base in the automotive market. Hence, NVH has been given significant priority while considering automotive design. NVH performance is monitored using simulations early during the design phase and testing in later prototype stages in the automotive industry. Meeting NVH performance targets possesses a greater risk related to design modifications in addition to the cost and time associated with the development process. Hence, a more enhanced and matured design process involves Design Point Analysis (DPA), which is essentially a decision-making process in which analytical tools derived from basic sciences, mathematics, statistics, and engineering fundamentals are used to develop a product model that better fulfills the predefined requirement. This paper shows the systematic approach of conducting a Design Point Analysis-level NVH study to evaluate the acoustic
Ranade, Amod A.Shirode, Satish V.Miskin, AtulMahamuni, Ketan J.Shinde, RahulChowdhury, AshokGhan, Pravin
Composite sandwich beams are widely favored for their high strength-to-weight ratio, so understanding their vibration characteristics is important for optimizing designs in critical industries. This study investigates, through experimental and statistical analyses, the impact of core geometry on the vibration characteristics of epoxy/carbon fiber composite sandwich beams featuring sinusoidal and trapezoidal cores. Modal tests were conducted to determine natural frequencies, damping ratios, and mode shapes. The height and angle of the cores were treated as key independent factors influencing the beams’ vibration characteristics. In both of the cores the damping ratio values increased about 25% and 35% with increasing the height and angle of the sinusoidal and trapezoidal cores, respectively. Additionally, response surface methodology (RSM) was used for statistical analysis of these input parameters’ effects on damping properties, and the optimal values of core’s geometries were
Alwan, Majeed A.Abbood, Ahmed Sh.Farhan, Arkan J.Azadi, Reza
Wind noise is an important indicator for evaluating cabin comfort, and it is essential to accurately predict the wind noise inside the vehicle. In the early stage of automotive design, since the geometry and properties of the sealing strip are often unknown, the contribution of the sealing strip to the wind noise is often directly ignored, which makes the wind noise obtained through simulation in the pre-design stage to be lower than the real value. To investigate the effect of each seal on wind noise, an SUV model was used to simulate the cases of not adding body seals, adding window seals, and further adding door seals, respectively. The contribution of each seal to wind noise was obtained and verified by comparing it with the test results. The influence of the cavity formed at the door seal was also addressed. In the simulations, a CFD solver based on the lattice Boltzmann method (LBM) was used to solve the external flow field, and the noise transmitted into the interior of the
Zhang, YingchaoHe, TengshengWang, YuqiNiu, JiqiangZhang, ZheShen, ChunZhang, Chengchun
There are many riders who drive motorcycles on winding mountain roads and caused single motorcycle traffic accidents on curved roads by lane departure. Driving a motorcycle requires subtle balancing and maneuvering. In this study, in order to clarify the influence of lane departure caused by inadequate driving maneuvers against road alignment, the authors analyzed the required curve initial operation and driving maneuvers in curves depending on the traveling speed using a kinematics simulation for motorcycle dynamics. In addition, it was analyzed how inadequate driving maneuvers for curved roads can easily cause lane departure. As a result, it shows that the steering maneuvers and the lean of motorcycle body during the curves are highly affected by the vehicle speed, and the required maneuvers increases rapidly with increasing speed. The inadequate maneuver in the curves, especially for the lean of motorcycle body and steering torque, even by 10%, may cause failure to follow the
Kuniyuki, HiroshiTakechi, So
Multiple-ion-probe method consists of multiple ion probes placed on the combustion chamber wall, where each individual ion probe detects flame contact and records the time of contact. From the recorded data, it is also possible to indirectly visualize the inside of the combustion chamber, for example, as a motion animation of moving flame front. In this study, a thirty-two ion probes were used to record flames propagating in a two-stroke gasoline engine. The experiment recorded the combustion state in the engine for about 3 seconds under full load at about 6500 rpm, and about 300 cycles were recorded in one experiment. Twelve experiments were conducted under the same experimental conditions, and a total of 4,164 cycles of signal data were obtained in the twelve experiments. Two types of analysis were performed on this data: statistical analysis and machine learning analysis using a linear regression model. Statistical analysis calculated the average flame detection time and standard
Yatsufusa, TomoakiOkahira, TakehiroNagashige, Kohei
Growth in the EV market is resulting in an unprecedented increase of electrical load from EV charging at the household level. This has led to concern about electric utilities’ ability to upgrade electrical distribution infrastructure at an affordable cost and sufficient speed to keep up with EV sales. Adoption of EVs in the California market has outpaced the national average and offers early insight for other regions of the United States. The Sacramento Municipal Utility District (SMUD) partnered with two grid-edge Distributed Energy Resource Management System (DERMS) providers, the OVGIP (recently incorporated as ChargeScape, a joint venture of Ford, BMW, Honda, and Nissan) and Optiwatt, to deliver a vehicle telematics-based active managed charging pilot. The pilot program, launched in Summer 2022 enrolled approximately 1,200 EVs over two years including Tesla, Ford, BMW, and GM vehicles. The goal of this pilot program was to evaluate the business case for managed charging to mitigate
Liddell, ChelseaSchaefer, WalterDreffs, KoraMoul, JacobKay, CarolAswani, Deepak
Real-world data show that abdominal loading due to a poor pelvis-belt restraint interaction is one of the primary causes of injury in belted rear-seat occupants, highlighting the importance of being able to assess it in crash tests. This study analyzes the phenomenon of submarining using video, time histories, and statistical analysis of data from a Hybrid III 5th female dummy seated in the rear seat of passenger vehicles in moderate overlap frontal crash tests. This study also proposes different metrics that can be used for detecting submarining in full-scale crash tests. The results show that apart from the high-speed videos, when comparing time-series graphs of various metrics, using a combination of iliac and lap belt loads was the most reliable method for detecting submarining. Five metrics from the dynamic sensors (the maximum iliac moment, maximum iliac force drop in 1 ms, time for 80% drop from peak iliac force, maximum pelvis rotation, and lumbar shear force) were all
Jagtap, Sushant RJermakian, Jessica SEdwards, Marcy A
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