bluuebunny/crossref_metadata_2025 huggingface dataset:
Integration of Unmanned Aerial Vehicle Systems With Machine Learning Algorithms for Wildlife Monitoring and Conservation
Authors: Raffik R. , Mahima Swetha M. , Sathya Rithish Ramamoorthy , Vaishali V. , Madhana Adithya B. , Balavedhaa S.
Published: January 2024

Two cutting-edge technologies, unmanned aerial vehicle (UAV) systems and deep learning algorithms, have the potential to completely change how wildlife is monitored and conserved. Data collection across wide areas, in challenging locations, and in real time are all possible with UAVs. Data collection via UAVs is possible in locations that are difficult or impossible to reach using conventional human approaches. Along with spotting strange behavior by wild creatures, the UAV can also spot it in human activity. Deep learning algorithms can be used to recognize certain animals, follow their motions, and categorize their behavior. The ecology of wildlife populations may be better understood using this knowledge, which can also be utilized to create more successful conservation plans. A novel technique that has promise for wildlife monitoring and conservation is the fusion of UAV systems and deep learning algorithms. The anticipation is even more creative and successful methods to use UAVs and deep learning to protect animals as technology progresses.
Local Site Effects Evaluation Using Geophysical Methods
Authors: Uyanık Osman , Uyanık Nurten Ayten , Ekin Nevbahar
Published: January 2024

The waves that occur in an earthquake affect the behavior of the soil and the building due to the structural condition of the bedrock and the physical properties of the soil near the surface. To predict this interaction, the deep underground structure models of the areas considered as settlements should be determined and how the earthquake waves will be directed (macro-zoning) depending on this should be revealed. Since the near surface features of the ground can increase the effect of earthquake waves, it is necessary to determine the near surface properties and create their maps (micro-zoning). Earthquake waves are formed in thick sediments compared to the rock environment and cause great damage to both the ground and the buildings. In order to be protected from these damages, it is necessary to determine focusing and scattering conditions arising from the deep underground base topography. Therefore, parameters such as maximum horizontal ground acceleration, soil liquefaction, soil dominant vibration period, soil amplification, and near-surface soil properties should be determined.
Industry 5.0 From Automation to Autonomy
Authors: Vetrivel S. C. , Mohanasundaram T.
Published: January 2024

The advent of Industry 4.0 brought about a transformative wave of automation and digitalization in manufacturing and industrial processes. However, the next phase of industrial evolution, Industry 5.0, focuses on achieving a seamless integration of humans and machines, shifting the emphasis from automation to autonomy. This explores the key concepts, challenges, and opportunities associated with this paradigm shift. Industry 5.0 represents a paradigmatic transition that seeks to harness the power of advanced technologies such as artificial intelligence (AI), robotics, the internet of things (IoT), and cyber-physical systems (CPS) to empower human workers and enhance their capabilities. The goal is to create a collaborative and symbiotic environment where humans and machines work together to achieve higher levels of productivity, efficiency, and innovation. This chapter delves into the primary drivers behind the transition to Industry 5.0. One key factor is the increasing complexity and variability of manufacturing processes, which demand greater flexibility and adaptability.
Applications of Nanotechnology for Improving Food Safety and Security
Authors: Batool Aliza , Farooq Umar , Firdous Nida , Shafi Afshan , Khan Zulqurnain , Ahmad Shabbir , Sibt-e-Abbas Muhammad , Usman Muhammad
Published: January 2024

In order to ensure a consistent supply of nutrient-rich nutritious food, food safety and security are gaining a lot of attention on a global scale. Numerous technical activities, such as the creation of novel materials and the improvement of food safety and security, need nanotechnology. Nanomaterials are utilized to enhance food protection and aid in the detection of pesticides, toxic chemicals, and microbiological contamination. Nanomaterials are utilized to enhance the detection of pesticides, toxic chemicals, and microbiological contamination. Nanocapsulation, which enables the release of bioactive substances, raises food bioavailability, and lengthens food shelf life, improves food processing even further. The main purpose of food processing is to fortify food by adding nutrients and beneficial ingredients. This chapter covers a variety of subjects, including the use of nanotechnology in food packaging, food safety, food preservation using smart nanocarriers, the detection of allergens and food-borne viruses using nanosensors, and crop growth and yield enhancement.
Development of Edible Food Wrappers
Authors: Basharat Zunaira , Ahmed Darakhshan , Tariq Muhammad Rizwan , Ali Shinawar Waseem , Pervaiz Muhammad Usama
Published: January 2024

Edible food wrappers are safe packaging systems that can be consumed with food. Edible packaging developed using natural renewable resources come under the category of bio-based and biodegradable packaging. The main components of edible wrappers include a biopolymer solubilized in a solvent to form film casting solution and certain additives to improve functional characteristics of packaging. Biopolymers are frequently used in food packaging applications due to their flexibility in film formation and biodegradability. The development of green packaging materials utilizing discarded edible materials will be beneficial to confront the challenges associated with traditional packaging systems, attaining sustainability, and fostering recycling in the food industry. Edible food wrappers present a number of benefits over synthetic materials. These packaging systems can replace and possibly strengthen the outside layers of packed items in order to elude moisture loss, flavors, and bioactive components from the foods as well as between them.
Recent Advances in the Utilisation of Artificial Intelligence in the Food Industry
Authors: Ojukwu Moses , Ofoedu Chigozie Emmanuel , Osuji Chijioke M. , Aja Ogbonnaya Okoro
Published: January 2024

Global population growth raises food security concerns. AI, like computer vision and ML, revolutionizes agriculture. It monitors crop health, predicts yields, and automates tasks. Mobile apps diagnose crop diseases swiftly, boosting productivity. AI-driven machine vision improves food processing by flaw identification and quality control. AI sorting enhances item classification, increasing productivity. In beer production, AI ensures fermentation quality. It optimizes distribution, predicts demand, and reduces waste. AI detects contaminants for food safety. Chatbots offer personalized recommendations. Data privacy and ethics matter, requiring explainable AI (XAI) and legal frameworks must be addressed despite these advancements. AI promises a secure, efficient, and sustainable food ecosystem.
Construction and Application of a Landscape Design Teaching Platform Driven by Artificial Intelligence
Authors: Yang Xiangge , Jiang Dongfang , Liu Meng
Published: January 2024

Landscape design is a measure of the development of urbanization process and the improvement of people's happiness index. The process of urbanization will involve landscape design. The study and teaching of landscape design is the core teaching method of landscape design research. However, with the diversified development of landscape design schemes and the characteristics of landscape 3D schemes, traditional landscape teaching schemes can no longer meet the needs of students and teaching, which also limits the effect of students' understanding and learning of landscape design schemes. Digital technology has been widely used in the field of landscape design, and has shown good results. This research uses the artificial intelligence method of digital technology to study the relevant factors in the teaching task of landscape design. This article mainly discusses three characteristics of students' design preference, landscape layout, and landscape pattern in landscape design teaching, which are also important factors affecting landscape design.
Factors Affecting Online Purchasing Behaviour of Management Undergraduates of State Universities in Colombo District
Authors: Sathsarani L. C. , Senarathne S.
Published: January 2024

The online purchasing behaviour of customers has a direct impact on the revenue generation and value generation of a company. The purpose of this study is to identify the nature and intensity of factors that affect the online purchasing behaviour of management undergraduates of state universities in the Colombo district, Sri Lanka. The study was conducted based on a representative sample selected from the management undergraduates of state universities in the Colombo district. This data was collected through a questionnaire survey and analysed using a one-sample t-test and one-way ANOVA. The study finds that web design, security concerns, product information quality, and shipping/delivery time factors have an impact on the online purchasing behaviour of management undergraduates at state universities in the Colombo district. Among them, web design and shipping/delivery time are the two factors that have a significant impact on online purchasing behaviour. Furthermore, the study did not find significant differences between consumers' perceptions of online purchasing behaviour and different demographic factors such as gender, income level, and university, according to this study. The findings of the study shed light on the factors impacting the online purchase behaviour of management undergraduates at state universities in the Colombo district, which in turn reflect the implications of the value created through the financial capital and intellectual capital of companies that use online delivery systems. Hence, these findings aid managers in implementing strategies to improve customers' online purchasing behaviour by identifying factors, investors in making investment decisions on ebusiness channels, and the government in enacting regulations related to online purchasing.
Analysing the Impact of Factors on Challenges and Barriers in Supply Chain Management Implementation in the Sri Lankan Retail Industry During Covid-19
Authors: Abeyrathne S. D. , Gunawardana K. D.
Published: January 2024

The primary purpose of this research study is to analyse the impact of factors on challenges and barriers faced by the retail industry in Sri Lanka in implementing supply chain management (SCM) amidst the COVID-19 situation. Furthermore, this study attempts to examine the mitigating strategies of challenges and obstacles to implementing SCM under disaster situations. The study sample comprised 52 individuals (out of 208 individuals directly engaged with supply chain activities) from six selected supermarket chains operating within Sri Lanka, and the data was collected using a questionnaire. Descriptive statistics were used to measure the degree of internal and external challenges and barriers to implementing SCM. Correlation and regression analysis were performed to identify the relationship between selected independent variables and the challenges and barriers of implementing SCM. The findings indicated a positive relationship between selected independent variables and the challenges and barriers of implementing SCM within the Sri Lankan retail industry. The study recommends effective actions to successfully implement SCM within the retail industry in Sri Lanka amidst the COVID-19 situation.
The Relationship Between Dividend Policy and Firm Financial Performance: Empirical Study of Non-Financial Listed Companies in Sri Lanka
Authors: Abeysinghe A. M. A. T. , Kariyawasam A. H. N.
Published: January 2024

The purpose of this paper is to examine the dividend policy and how it impacts the financial performance of non-financial listed companies in Sri Lanka. The study employs a quantitative approach to determine the association between dividend policy and firm financial performance. The population of this study is listed as manufacturing, food, beverage, and tobacco companies in Sri Lanka from 2016 to 2020. Dividend policy is the independent variable, which is measured using the dividend payout ratio (DPR) and earnings per share (EPS). Return on equity (ROE) and return on assets (ROA) are used to measure the firm financial performance which is the dependent variable. Firm size and revenue are used as control variables for the study. The secondary data were gathered from the annual reports of the selected companies by using the convenience sampling technique. Moreover, several statistical analyses were performed by using Stata. The results concluded that DPR does not significantly impact the firm financial performance. Further, the findings indicate that EPS and firm size significantly positively affect the firm financial performance. The study serves as an addition to knowledge that is useful for policymakers, potential investors, academics, and other stakeholders to policy making or study the above companies.
Assessing the Disclosure of Materiality Analysis in Integrated Reports: Evidence from Sri Lanka
Authors: Nusari A. , Henadirage A.
Published: January 2024

The disclosure of materiality analysis in integrated reports demonstrates the genuine intention of business organisations to fulfil stakeholders' information requirements through stakeholder needs and expectations analysis. This study assesses whether the Sri Lankan companies have taken the required initiatives to disclose the materiality analysis in their integrated reports. This research will assess the above concerns with the support of stakeholder and legitimacy theories. Integrated reporting (IR) has opened avenues for increasing the content validity and quality of reports published by companies by providing required guidelines and reporting Standards. Reporting on the materiality analysis is required by the Global Reporting Initiative (GRI) 3 Standard and the International Integrated Reporting Council (IIRC) Framework but remains voluntary. The revised Standard provides guidance on what information the companies are required to disclose, how they have prioritised material topics, and how they have decided the extent of related disclosures. Accordingly, this study will provide insights into the aspect of disclosure of materiality analysis in the annual reports of companies listed in the Colombo Stock Exchange (CSE) by analysing the annual reports of the selected listed companies in the years 2016/17, 2017/18, 2018/19, and 2019/20. A binary disclosure index has been developed to indicate whether the materiality-related disclosures have been mentioned and explained as required. The disclosure index will be quantified and statistically tested to arrive at conclusions regarding the analysis. The study has revealed that there is a growing trend in the disclosure of materiality analysis in the annual reports of the Sri Lankan listed companies. The companies have dedicated a few pages in their annual reports to discuss their materiality analysis process and the key stakeholders. Meanwhile, there is a lack of information on the methods used by the companies to identify their stakeholders. However, they have revealed information on the methods used to identify their material topics to some extent.
Feasibility of high-frequency percussions in people with severe acquired brain injury and tracheostomy: an observational study
Authors: Sciurello Salvatore Andrea , Graziano Francesca , Laganà Maria Marcella , Compalati Elena , Pappacoda Gabriele , Gambazza Simone , Navarro Jorge , Cecconi Pietro , Baglio Francesca , Banfi Paolo
Published: January 2024

People with severe acquired brain injury (pwSABI) frequently experience pulmonary complications. Among these, atelectasis can occur as a result of pneumonia, thus increasing the chance of developing acute respiratory failure. Respiratory physiotherapy contribution to the management of atelectasis in pwSABI is yet poorly understood. We conducted a retrospective analysis on 15 non-cooperative pwSABI with tracheostomy and spontaneously breathing, hospitalized and treated with high-frequency percussion physiotherapy between September 2018 and February 2021 at the Neurological Rehabilitation Unit of the IRCCS “S.Maria Nascente - Fondazione Don Gnocchi”, Milan. Our primary aim was to investigate the feasibility of such a physiotherapy intervention method. Then, we assessed changes in respiratory measures (arterial blood gas analysis and peripheral night-time oxygen saturation) and high-resolution computed tomography lung images, evaluated before and after the physiotherapy treatment. The radiological measures were a modified radiological atelectasis score (mRAS) assigned by two radiologists, and an opacity score automatically provided by the software CT Pneumonia Analysis® that identifies the regions of abnormal lung patterns. Treatment diaries showed that all treatments were completed, and no adverse events during treatment were registered. Among the 15 pwSABI analyzed, 8 were treated with IPV® and 7 with MetaNeb®. After a median of 14 (I-III quartile=12.5-14.5) days of treatment, we observed a statistical improvement in various arterial blood gas measures and peripheral night-time oxygen saturation measures. We also found radiological improvement or stability in more than 80% of pwSABI. In conclusion, our physiotherapy approach was feasible, and we observed respiratory parameters and radiological improvements. Using technology to assess abnormal tomographic patterns could be of interest to disentangle the short-term effects of respiratory physiotherapy on non-collaborating people.
Statistical process control in pulsed drip irrigation systems
Authors: Cossich Vinicius , Boas Marcio Antonio Vilas , Kepp Naila Cristina , Lopes Allan Remor , Júnior Dário Machado
Published: January 2024

Pulse drip application is a management option to prevent clogging and improve water-use efficiency. The measurement of distribution uniformity is opportune for pulse irrigation projects to ensure efficiency since the shorter the pulse time, the more negative influence the transition periods have. The objective of the present work was to monitor the quality of a drip irrigation system with different emitter models and different pulse times. The experiment was conducted under laboratory bench conditions, and 25 tests were performed for each pulse application (2, 3, 6 and 12 minutes) and emitter model (non-compensated and auto-compensated). Uniformity was determined using Christiansen's uniformity coefficient (CUC) and distribution uniformity coefficient (DUC) and monitored by Shewhart control charts and exponentially weighted moving average (EWMA). The decrease in pulse time caused a decrease in flow rate and uniformity only in drip irrigation systems with non auto-compensated emitters. However, this decrease is subtle, to the point that uniformity presented an excellent performance for all pulses tested. The use of the Shewhart and EWMA control charts were effective in monitoring the uniformity of the pulsed drip irrigation system. The Shewhart control chart was more robust in identifying isolated non-compensated uniformities, while the EWMA control chart was more sensitive in identifying unstable propensity. In the treatments with the non-compensated emitter, the statistical process control was able to identify that shorter pulse times resulted in greater application instability. As for the auto-compensated emitters, the statistical process control highlighted the concern with application uniformity after maintenance interference.

Keywords: anti-drain emitter, high-frequency irrigation, irrigation interval, statistical quality control.
Single Early Intravesical Instillation of Epirubicin for Preventing Bladder Recurrence after Nephroureterectomy in Upper Urinary Tract Urothelial Carcinoma
Authors: Lee Jong Hoon , Lee Chung Un , Chung Jae Hoon , Song Wan , Kang Minyong , Jeon Hwang Gyun , Jeong Byong Chang , Seo Seong Il , Jeon Seong Soo , Sung Hyun Hwan
Published: January 2024

Purpose We aimed to assess the effectiveness of early single intravesical administration of epirubicin in preventing intravesical recurrence after radical nephroureterectomy for upper tract urothelial carcinoma.Materials and Methods Patients with upper tract urothelial carcinoma who underwent radical nephroureterectomy between November 2018 and May 2022 were retrospectively reviewed. Intravesical epirubicin was administered within 48 hours if no evidence of leakage was observed. Epirubicin (50 mg) in 50 mL normal saline solution was introduced into the bladder via a catheter and maintained for 60 minutes. The severity of adverse events was graded using the Clavien-Dindo classification. We compared intravesical recurrence rate between the two groups. Multivariate analyses were performed to identify the independent predictors of bladder recurrence following radical nephroureterectomy.Results Epirubicin (n=55) and control (n=116) groups were included in the analysis. No grade 1 or higher bladder symptoms have been reported. A statistically significant difference in the intravesical recurrence rate was observed between the two groups (11.8% at 1 year in the epirubicin group vs. 28.4% at 1 year in the control group; log-rank p=0.039). In multivariate analysis, epirubicin instillation (hazard ratio [HR], 0.43; 95% confidence interval [CI], 0.20 to 0.93; p=0.033) and adjuvant chemotherapy (HR, 0.29; 95% CI, 0.13 to 0.65; p=0.003) were independently predictive of a reduced incidence of bladder recurrence.Conclusion This retrospective review revealed that a single immediate intravesical instillation of epirubicin is safe and can reduce the incidence of intravesical recurrence after radical nephroureterectomy. However, further prospective trials are required to confirm these findings.
Relations for quadratic Hodge integrals via stable maps
Authors: Politopoulos Georgios
Published: January 2024

Following Faber–Pandharipande, we use the virtual localization formula for the moduli space of stable maps to
$\mathbb {P}^{1}$
to compute relations between Hodge integrals. We prove that certain generating series of these integrals are polynomials.
On the pythagorean structure of the optimal transport for separable cost functions
Authors: Auricchio Gennaro
Published: January 2024

In this paper, we study the optimal transport problem induced by two measures supported over two polish spaces, namely,

X

and

Y

, which are the product of

n

smaller polish spaces, that is,

X={\Large{\times}}_{j=1}^n X_j

and

Y={\Large{\times}}_{j=1}^n Y_j

. In particular, we focus on problems induced by a cost function

c:X\times Y\to [0,+\infty)

that is separable; i.e.,

c

is such that

c=c_1+\dots+c_n

, where each

c_j

depends only on the couple

(x_j,y_j)

, and thus

c_j:X_j\times Y_j\to [0,+\infty)

. Noticeably, if

X=Y=\mathbb{R}^n

, this class of cost functions includes all the

l_p^p

costs. Our main result proves that the optimal transportation plan with respect to a separable cost function between two given measures can be expressed as the composition of

n

different lower-dimensional transports, one for each pair of coordinates

(x_i,y_i)

in

X\times Y

. This allows us to decompose the entire Wasserstein cost as the sum of

n

lower-dimensional Wasserstein costs and to prove that there always exists an optimal transportation plan whose random variable enjoys a conditional independence property with respect to its marginals. We then show that our formalism allows us to explicitly compute the optimal transportation plan between two probability measures when each measure has independent marginals. Finally, we focus on two specific frameworks. In the first one, the cost function is a separable distance, i.e.,

d=d_1+d_2

, where both

d_1

and

d_2

are distances themselves. In the second one, both measures are supported over

\mathbb{R}^n

and the cost function is of the form

c(x,y)=h(\vert x_1-y_1\vert)+h(\vert x_2-y_2\vert)

, where

h

is a convex function such that

h(0)=0

.
Representaciones del conflicto armado en el cine colombiano
Authors: Rivera Betancur Jerónimo , Ruiz Moreno Sandra
Published: January 2024

El cine es un acto de representación y se basa en la construcción de realidades inspiradas en la experiencia.  En Colombia, el cine no ha sido producto de una industria estructurada, si no más bien del esfuerzo de algunos realizadores que han encontrado diferentes maneras de contar historias sobre temas que hacen parte del acontecer nacional.  El conflicto armado en Colombia, entendido como confrontación entre fuerzas del Estado y grupos organizados al margen de la ley, tiene más de cincuenta años y ha estado presente en el arte desde entonces.  La investigación “Narrativas del conflicto armado en el cine colombiano” abordó una muestra de películas de la filmografía nacional para encontrar la forma como se ha representado el tema del conflicto armado en el cine colombiano.
Vehicle-Integrated Camera Based Rider Helmet Detection & Warning System
Authors: Kishor Kaushal , Tarte Malay , Joshi Umita
Published: January 2024

Non-usage of helmets does not cause accidents but is critical for averting fatal and grievous injuries in the event of road occurrence accidents. Currently, traffic police use the helmet detection solution on surveillance videos to identify the vehicle number plate of a person who is not wearing a helmet and issue challan. But on the vehicle side, it is not yet implemented. At present, vehicles are neither equipped to issue warnings nor there are any safety measures taken to minimize the risk when the rider is not wearing a helmet. This paper suggests a passive safety system for two-wheelers that uses an integrated camera to detect if the rider is wearing a helmet or not by utilizing image processing techniques. Based on the result, if a helmet is not detected, then the vehicle can send control frames to vehicle HMI for alerts. This paper suggests two approaches to implement the solution. One is Machine Learning Model deployment, and another is OpenCV-based helmet detection. Each approach comes with certain constraints, which are discussed in this paper.
The Effect of Different Air Path Based ATS Thermal Management Strategy on a Non- EGR Medium Duty Diesel Engine’s Performance and Emissions
Authors: Sharma Ajeet Kumar , Kreuzig Gerhard , Gupta Ayush , Goyal Dinesh , Garg Varun
Published: January 2024

The major objective of this paper is to develop thermal management strategy targeting optimum performance of Selective Catalytic Reduction (SCR) catalyst in a Medium Duty Diesel Engine performing in BS6 emission cycles.

In the current scenario, the Emissions Norms are becoming more stringent and with the introduction of Real Drive Emission Test (RDE) and WHTC test comprising of both cold and hot phase, there is a need to develop techniques and strategies which are quick to respond in real time to cope with emission limit especially NOx. SCR seems to be suitable solution in reducing NOx in real time. However, there are limitations to SCR operating conditions, the major being the dosing release conditions which defines the gas temperature at which DEF (Diesel Exhaust Fluid) can be injected as DEF injection at lower gas temperatures than dosing release will lead to Urea deposit formation and will significantly hamper the SCR performance. The second factor for optimum SCR operation is to maintain the catalyst temperature where high NOx conversion efficiency is obtained.

Dosing release temperature plays an important role to achieve high NOx conversion efficiency, specifically when the aftertreatment system is at ambient temperature. Therefore, thermal management strategy is employed to ensure quick heating of ATS to achieve the Dosing release temperature in the shortest possible time duration. Thermal management involves air path control where actuators are used to alter the exhaust temperature, and also the injection strategies that favors higher exhaust enthalpy at the cost of BSFC. Thermal Management is active until the ATS will reach the certain temperature threshold beyond which the thermal management will be deactivated as prolong activation of thermal management may result in fuel penalty. From the airpath point of view the focus of this paper is towards the utilization of intake throttling, engine brake and variable exhaust flap. Along with the airpath, the impact of combustion retardation is also covered.
Analytical Tool for Design & Optimization of Double Isolation Mounting System for Electric Powertrain
Authors: Verma Shemon , Jayachandran Suresh Kumar , Mane Yogiraj , Paua Ketan , Vellandi Vikraman
Published: January 2024

As the world rapidly moves from IC engine powered vehicles to the ‘more sustainable’ electrified vehicles, the Powertrain Mounting System needs to be re-engineered to meet refinement requirements of customer. Electric vehicles are quieter but due to lack of the “masking effect”, are sensitive to minor disturbances that are perceived to be objectionable by passengers. Also, E-powertrains are lighter, produce higher torque at low rpms & operate at higher rpms which calls for different countermeasures for mounting systems compared to conventional single isolation 3-point mounting system as used in IC engines. Double isolation mounting system, where powertrain is connected to an auxiliary mass (sub frame/cradle) via mounts, which is suspended to the vehicle body via subframe bushes results in 12 rigid body modes, 6 for each mass, is highly effective in lowering the transmission of vibration at high frequencies. This paper discusses 12 DOF analytical tool developed to rapidly analyze the powertrain double isolation mounting system rigid body modes as well as kinetic energy distribution and decoupling. Results are compared with actual measured values as well as with commercially available Simcenter Amesim simulation tool and good correlation is established. Based on the developed tool, parametric study on number of mountings, stiffness and location sensitivity is studied and optimum e-powertrain mounting system is designed meeting modal & system deflection targets which is validated in test measurement.
Modular Fuel Cell Control Software for Commercial Vehicle Applications
Authors: Srivastava Vivek , Wendler Artem , Schaub Joschka , Walters Marius , Thodupunoori Shravan , Mulukutla Kiran
Published: January 2024

Compliance with the future CO2 emission limits for the fleet of vehicles sold presents a major challenge for the automotive industry. To comply with these stringent limits, one solution is mobility using hydrogen as an energy carrier. In this context, the development of Proton Exchange Membrane (PEM) fuel cells for commercial vehicle applications, both on- and off-road, is of significant interest due to the non-existent CO2 emissions. However, performance of these devices is closely related to the control concepts that are used to ensure high efficiency, good transient performance, high reliability & durability as well as safe operation. To address these challenges, this paper presents a modular Fuel Cell Control Software which offers the potential to be used for different P&ID (Piping & Instrumentation Diagram) configurations of fuel cell systems. The presented software controls and monitors the stack and the Balance of Plant (BoP) components and communicates with the main vehicle controller. To realize this, the control software consists of a start-up and shut-down procedure that has been coordinated with various fuel cell stack manufacturers. It allows a wide range of diagnostics to check various sub-systems. The main control variables, namely temperature, pressure, humidity, and air stoichiometry, which directly affect the fuel cell performance, are identified. Depending on the system complexity, the modular software takes into account different approaches to mass flow, pressure and humidity control, e.g. using throttles and bypasses. Particular attention is paid to the optimization of the purge/drain strategy. Furthermore, the challenges due to component deviations or aging are considered in closed-loop power control. In addition to the functional correlations and the principle layout of the novel algorithms, the paper delivers also experimental results that demonstrate the merits for a reliable operation.
Countermeasures for Low Frequency Boom Noise Reduction in Electric Vehicle
Authors: S Nataraja Moorthy , Rao Manchi , Raghavendran Prasath , Selvam Ebinezer
Published: January 2024

Electric vehicles (EV) are much quieter than IC engine powered vehicles due to less mechanical components and absence of combustion. The lower cabin noise in electric vehicles make customers sensitive to even small noise disturbances in vehicle. Road boom noise is one of such major concerns to which the customers are sensitive in electric vehicles.

The test vehicle is a front wheel driven compact SUV powered by electric motor. On normal plain road, noise levels are acceptable but when the vehicle has been driven on coarse road, the boom noise is perceived, and the levels are objectionable. Multi reference Transfer Path Analysis (MTPA) is conducted to identify the path through which maximum forces are entering the body. Based on MTPA, modifications are proposed on the suspension bushes and the noise levels were assessed. Operational Deflection Shape (ODS) analysis is conducted on entire vehicle components like suspension links, sub frame, floor, roof, and doors to identify the deflection pattern of the components at frequencies where the noise levels are higher. Based on full vehicle ODS, the critical components with maximum deflection at problematic frequency is identified and modifications are proposed to increase the dynamic stiffness of the components to reduce the noise levels. Effect of increase in stiffness of each critical component on cabin noise has been discussed. Alternative solutions like tuned mass dampers at the anti-nodal point are also explored and the changes required on the parameters of the damper to improve its performance is also discussed. With all modifications, the low frequency booming noise is reduced by ~ 4 dB (A) and the levels are acceptable. Design criteria that should be considered for vehicle components in early phase of development to avoid this concern are elaborated.
Electric Vehicle Road Noise Analysis through Systematic Virtual Prototyping
Authors: Dom Steven , Van Genechten Bert , Sorber Eric , Minervini Domenico
Published: January 2024

Without the masking effect of a combustion engine, noise from the road is much more prominent in electric vehicles (EV) and has become the dominant source of noise for drivers and passengers.

Road noise however is a complex problem. Unlike engine noise, which comes from a single, well-defined source, road noise finds its origins in the road-to-tire contact. This means that there are typically 4 sources (assuming a 4-wheel vehicle) which are influenced by the roughness and profile of the road as well as the compliance of the tires. From an engineering point of view it’s easy to appreciate the added complexity compared to engine noise.

In addition to the engineering complexity, there is also a supplier-OEM relationship that comes into play. Most OEMs do not manufacture their own tires and may even have multiple tire suppliers for the same vehicle. This brings on another set of complications. Firstly, there are multiple types of tires for the same vehicle, each combination having its own noise characteristics. And secondly, there is a need to properly agree with the tire suppliers on what the target performances of the tire need to be and how to determine them.

The proposed solution to these problems is to use defined vehicle architectures and populate them with sub-system and component models based on test and/or simulation data. The sub-systems are both passive systems such as trimmed bodies and sub-frames, but also ‘active’ components that introduce loads into the vehicle. In this case where we consider road noise, these active components are the wheels and the road loads coming through them. The important aspect of these ‘active’ components is that they are defined independent from the actual vehicle application, i.e. they are universally applicable to any vehicle model.

This approach, called Virtual Prototype Assembly, allows for effective prediction of road noise throughout the vehicle development without needing a physical vehicle or prototype and hence can be applied from very early on in the process.

In this paper, this methodology is applied to predict the interior noise in a simulated vehicle, starting from road loads determined from testing on an existing vehicle, transforming them into an invariant load definition and finally applying them onto a simulated vehicle.
Nanotechnology in Transportation Vehicles
Authors: Khadake Nilesh , Yadav Prashant
Published: January 2024

Nanotechnology is gaining popularity and used in the realm of transportation vehicles. Nanomaterials, with their distinct physical and chemical properties, have the potential to improve the safety and durability of transportation vehicles. This study analyzes the most current advances and uses of nanotechnology in the transportation vehicle business, such as nano-coatings, nano filters, carbon black for tires, and nanoparticles for engine performance enhancement and fuel consumption reduction. It also discusses the major hurdles for larger applications, such as environmental, health, and safety problems. Because some nanomaterials have demonstrated outstanding performance as well as theoretically investigated, they may be viable candidates for use in future environmentally friendly transportation vehicles. Improve the global transportation business.
Energy Conservation and Protecting Global Health by Automated Corporate Transport Services Application/System
Authors: Thakare Ashish
Published: January 2024

In a world increasingly concerned with environmental sustainability and traffic congestion, the need for innovative solutions to address daily commuting challenges has become paramount. This paper presents an innovative concept for an application/system that seeks to revolutionize the way corporate employees commute to work. By harnessing the power of data and technology, this application aims to reduce pollution, traffic, and fuel consumption while promoting shared transportation solutions among employees. The paper discusses the key features and benefits of this proposed application and its potential to create a greener and more efficient corporate commuting ecosystem.
Dual-Motor-BEV Controls Optimization
Authors: Chopra Ujjwal
Published: January 2024

In this paper we will discuss different techniques of controls optimization for a dual motor BEV model and look at the most optimal solution with an objective to minimize motor losses or maximize efficiency. In a dual motor model, torque split ratio plays a vital role in deciding the operating points for each motor and hence the losses or inefficiency in the system. It is important to find the optimal torque split ratio to improve range and performance. Three techniques covered in this paper include ECMS (Equivalent Consumption Minimization Strategy, DOE (Design of Experiment) and Empirical relation-based approach. ECMS is a local optimization technique. A combined ECMS and DOE based approach was performed to analyze with an eventual goal of creating a map which relates TSR (Torque Split Ratio) to the operating points in the form of vehicle acceleration and vehicle speed. A quadratic empirical relation between vehicle acceleration, speed and torque split ratio was set up and coefficients were optimized using genetic algorithm with an objective to minimize motor losses and hence increase range. We will analyze and compare these three techniques on the basis of optimal solution, computational effectiveness and final vehicle range increment as compared to baseline model. In the end we will also briefly discuss how Machine Learning can help enhance the model for controls development and digital twin applications to improve runtime without compromising on the accuracy.
Electromechanical - Multiphysics Simulation of Motor
Authors: Karale Ajinkya Sujay
Published: January 2024

These days, the use of virtual Multiphysics simulations through finite element analysis methodology is increasing exponentially during the development phase of automotive products. Thereupon, the automotive industries are becoming competent enough to build an ingenious and creative design with optimal performance within the coherent time. A huge number of electromagnetic as well as mechanical forces are being generated inside the Motor, when it is undergoing extreme driving conditions of the application. Hence it becomes vital to reduce the risks, if any, during the development phase by providing an optimal factor of safety within the electromechanical system of the motor. The present study gives details about conducted finite element analysis on an automotive traction motor to determine its mechanical strength and behavior. This study also focuses on finding the structurally critical regions over the motor assembly through electromechanical (Multiphysics) simulations.
A Machine Learning Approach for Hydrogen Internal Combustion (H2ICE) Mixture Preparation
Authors: Jose Alen , Probst Daniel , Biware Mukul
Published: January 2024

The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction.

A Design of Experiments (DoE) was derived for the injection system parameters to train the ML model using Latin Hypercube Sampling (LHS). An ensemble ML emulator uses the results from different ML algorithms to emulate the CFD simulation model trained with DoE data. Considering the injection parameters, a merit function is derived to optimize injection parameters using stochastic models like Genetic Algorithm (GA) to get the best mixture preparation. A significant advantage to the DoE-ML approach is the CFD cases can be run concurrently, shortening the wall clock time dramatically. A sequential CFD optimization can take months to complete, while a DoE-ML optimization can be completed in days using high core count HPC resources.

The integration of CFD simulation and AI techniques can provide a powerful tool for the design and optimization of H2ICEs, enabling engineers to improve engine performance and reduce emissions while minimizing the need for expensive and time-consuming experimental testing. Furthermore, these techniques can help in the rapid and cost-effective evaluation of new H2ICE designs, accelerating the development and adoption of this promising technology.
Generation of Tire Digital Twin for Virtual MBD Simulation of Vehicles for Durability, NVH and Handling Evaluation
Authors: Bakal Nikhil , Joshi Omkar Prakash , Pawar Prashant R , Shinde Vikram V
Published: January 2024

With the recent development in virtual modelling and vehicle simulation technology, many OEM’s worldwide are using digital road profiles in virtual environment for vehicle durability load prediction and virtual design evaluation. For precise simulation results, it is important to have the tire digital twin which is the realistic representation of tire in the virtual environment.

The study comprises of discussion about different types of tire models such as empirical, solid model, rigid ring model and flexural ring models such as Pacejka, MF Swift, CD tire, F tire etc. and also the complexity involved in development of these tire models.

Generation of virtual tire model requires highly sophisticated test rigs as well as vehicle level testing with Wheel Force transducers and other vehicle dynamics sensors. The large number of data points generated with testing are converted in standard TYDEX format to be further processed in various software tool for virtual model generation. Thus, a robust test routine based on laboratory and vehicle level tests to achieve different tire models such as F Tire, MF Tire etc. has been developed. The research paper also discusses the challenges, complexity in data pre and post processing to arrive at the tire characterization for tire digital twinning.

In this paper various technical aspects related to passenger car tires, its functions, available tire models, parameterization have been discussed. Additionally, case study has been explained on experience on generation of the digital twin model of tire with Cosin – Ftire software tool. In continuation with process different applications of the Tire models has been elaborated in brief. Tire model developed can be used for vehicle durability, ride & handling simulation, Autonomous driving and ADAS feature development for various OEM’s and tier 1 suppliers. Virtual tire model will aid in reducing the time and physical track testing efforts required in the tire development cycle
A Predictive Approach to Estimate Tyre Wear Characteristics
Authors: Bedi Vinay Kumar , Rana Kashif , Mahata Pundarik , Ghosh Prasenjit , Mukhopadhyay Rabindra
Published: January 2024

Tyre wear is of significant concern for the automotive industry due to multiple reasons including vehicle performance, safety, economy, environmental (particulate matter emission) aspects, etc. Therefore, ensuring enhanced tyre tread wear resistance is one of the most important criteria while developing a new tyre. Tyre wear phenomenon is influenced by various factors, such as road conditions, driving habits, maintenance practices and tyre design parameters (construction, geometry and material). The wear assessment through the classical field-testing approach consumes significant time and resources. Therefore, digital predictive tools are very useful in predicting wear characteristics at the early stage of the tyre development process.

In this study, an attempt has been made to capture the impact of tread geometry, tread material, vehicle geometry, vehicle speed, test track geometry, etc. on tyre wear. A commercial finite element code, Abaqus was utilized for tyre structural simulation and the frictional energy has been considered as a key indicator to estimate the propensity of tyre wear. The vehicle modelling is done in a multibody dynamics software Adams. It has been found that tyre stiffness and tread block geometry have a direct influence on tyre wear potential. A correlation between cornering stiffness and wear potential has been also observed. Furthermore, from a vehicle perspective, the effect of the positioning of the tyre on corresponding axles and test track geometry has been analysed.