bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Gas Inflow during the Onset of a Starburst in a Low-mass Galaxy at z = 2.45
Authors: Coleman Erin , G.C. Keerthi Vasan , Chen 陈 Yuguang 昱光 , Jones Tucker , Rhoades Sunny , Ellis Richard , Stark Dan , Leethochawalit Nicha , Sanders Ryan , Mortensen Kris , Glazebrook Karl , Kacprzak Glenn G.
Published: December 2024

The baryon cycle is crucial for understanding galaxy formation, as gas inflows and outflows vary throughout a galaxy’s lifetime and affect its star formation rate. Despite the necessity of accretion for galaxy growth at high redshifts, direct observations of inflowing gas have proven elusive, especially at z ≳ 2. We present a spectroscopic analysis of a galaxy at redshift z = 2.45, which exhibits signs of inflow in several ultraviolet interstellar absorption lines, with no clear outflow signatures. The absorption lines are redshifted by ∼250 km s−1 with respect to the systemic redshift, and C iv shows a prominent inverse P-Cygni profile. Simple stellar population models suggest that this galaxy has a low metallicity (∼5% solar), with a very young starburst of age ∼4 Myr dominating the ultraviolet luminosity. The gas inflow velocity and nebular velocity dispersion suggest an approximate halo mass of order ∼1011
M
⊙, a regime in which simulations predict that bursty star formation is common at this redshift. We conclude that this system is likely in the beginning of a cycle of bursty star formation, where inflow and star formation rates are high, but where supernovae and other feedback processes have not yet launched strong outflows. In this scenario, we expect the inflow-dominated phase to be observable (e.g., with net redshifted interstellar medium absorption) for only a short timescale after a starburst onset. This result represents a promising avenue for probing the full baryon cycle, including inflows, during the formative phases of low-mass galaxies at high redshifts.
A new spider species of the Pholcus yichengicus species group (Araneae, Pholcidae) from Hebei Province, northern China
Authors: Li Jinglin , Zhang Xiaoqing , Yao Zhiyuan
Published: December 2024

The Pholcus yichengicus species group currently contains 47 species. It is mainly distributed in central and southern China, as well as northern Thailand.

Pholcus changli Yao, sp. nov. is described as a new species of the P. yichengicus species group collected from northern China (Hebei Province).
Modelling the present and future distribution of Ambystoma altamirani in the Transmexican Volcanic Belt, Mexico
Authors: Sunny Armando , Martínez-Valerio Jaqueline Carolina , Bolom-Huet Rene , Heredia-Bobadilla Rosa Laura , Alvarez-Lopeztello Jonas , Gómez-Ortiz Yuriana , Guido-Patiño Juan Carlos , Manjarrez Javier , González-Pedroza María G. , Domínguez-Vega Hublester
Published: December 2024

Ambystoma altamirani is a critically endangered, microendemic amphibian species inhabiting the high-altitude rivers and streams of the Trans-Mexican Volcanic Belt (TMVB), a region experiencing severe ecological disturbances. This study aims to assess the current and future distribution of A. altamirani under different climate and land-use change scenarios using ecological niche modelling (ENM). We also evaluate the connectivity of suitable habitats and the overlap with existing natural protected areas (NPAs). Using occurrence records and environmental variables, we modelled the species’ potential distribution under two climate models (CN85 and MP85) for 2050. The results indicate a significant reduction in suitable habitat, particularly in areas such as the Sierra de las Cruces and the Chichinautzin Biological Corridor, with habitat losses projected to reach up to 13.95% by 2050 under the CN85 scenario. Forest cover loss between 2001 and 2023 further exacerbates this threat, especially in municipalities like Tlalpan and Ocuilan. Our analysis highlights the urgent need for targeted conservation efforts, including the preservation of mixed Abies-Pinus forests and the restoration of degraded ecosystems. The findings underscore the critical importance of integrated conservation strategies that address habitat degradation, climate resilience and ecological connectivity to ensure the long-term survival of A. altamirani.
Advanced Machine Learning Techniques for Enhancing Network Intrusion Detection and Classification Using DarkNet CIC2020
Authors: Kalidindi Archana , B. Raja Koti , CH. Srilakshmi , Buddaraju Krishna Mohan , Kandi Akash Reddy , Makutam Gopi Sai Srinivas
Published: December 2024

The increase of illegal endeavors and malware traffic inside the Darknet presents a detracting challenge to cybersecurity. This study deals with the problems by applying leading machine learning (ML) techniques to reduce the use of the Darknet misuse while still preserving the aura of mystery, anonymity, and privacy. Leveraging the Darknet CIC2020 dataset, the research performs binary and multiclass classification, which are based on modern algorithms, with autoencoder being one of them. Convolutional neural networks (CNN), long short-term memory (LSTM), and XGBoost were used to discriminate the complicated systems. Results indicate XGBoost performed better in cases of both binary and multi-class classifications showing tremendous reliability, accuracy, recall, and F1-score. Furthermore, the study extends its scope by introducing ensemble techniques such as voting classifier and stacking classifier, aiming to enhance predictive accuracy by joining diverse base estimators. Combining autoencoder and XGBoost, alongside investigating the CNN+LSTM architecture, enhances the model’s effectiveness. These hybrid approaches are implemented so that they can affect the components of various algorithms, creating more finely grained acting metrics on a per-order basis. This approach is to analyze Darknet traffic patterns that enable us to understand the importance of Internet security measures.
In-World NPC: Analysing Artificial Intelligence Precision in Virtual Reality Settings
Authors: Mochamad Bruri Triyono  , Rafiq Arif Ainur , Didik Hariyanto  , Dina Adinda  , Maria Denami
Published: December 2024

This study investigates the accuracy and performance of artificial intelligence (AI)-driven non-player characters (NPC) in a virtual classroom environment, focusing on an educational simulation scenario. By employing a mixed-methods approach that combines quantitative data from controlled experiments and qualitative insights from user feedback, the research aims to provide a comprehensive evaluation of NPC behavior. The findings indicate that NPC demonstrated a high decision-making accuracy rate of 87%, with solid behavioral consistency and generally fast response times averaging 1.2 seconds. However, challenges were noted in handling complex queries and maintaining consistency in dynamic scenarios. Factors influencing NPC performance included the complexity of user interactions, the environmental context, and the limitations of AI algorithms. Overall user satisfaction was high, with participants appreciating NPC realism, responsiveness, and engagement. A comparative analysis of AI techniques revealed that while rule-based systems were efficient and predictable, machine learning models offered superior adaptability and contextual understanding, albeit at the cost of higher computational demands. The study concludes that enhancing AI capabilities, optimising computational resources, and incorporating adaptive learning algorithms can improve NPC performance. These insights provide valuable guidance for future developments in AI-driven NPC, aiming to create more immersive and compelling virtual educational environments.
Open-ended Simulation 3D Game as a Tool for Speech Therapy Intervention
Authors: Hatzigiannakoglou Paul D. , Okalidou Areti , Georgopoulos Voula C.
Published: December 2024

Speech and communication disorders are widespread among preschool children. Various studies indicate that approximately 8% of children aged 317 years have some form of communication disorder. This paper presents a three-dimensional serious game, open-ended in nature, intended as a tool for speech therapy intervention to address these disorders. The software is suitable for supporting speech, language, and communication in preschool children and is primarily intended for speech therapists, but also for parents and educators involved in language development programs for children. The game simulates the toys and objects used by speech therapists during sessions with children and creates an engaging virtual environment. By promoting active listening, imitation, prompted speech and spontaneous language production, the game enhances children’s communication skills. The software is compatible with devices running on Windows, Mac, Android, and iOS and is also available as a web application, ensuring maximum accessibility for users.
A primeira Crónica Portuguesa
Authors: Mattoso José
Published: December 2024

A partir da datação da Crónica de los Veinte Reyes, estabelecida por Inéz Fernandez Ordoñez, F. Moreira faz recuar para antes de 1282/4 a redacção da uma Primeira Crónica Portuguesa, origem da IV Crónica Breve de Santa Cruz de Coimbra, até agora considerada com escrita c. 1340. Procura demonstrar a sua unidade redactorial, o seu testemunho em função da ideologia régia e a sua origem cortesã. Admitindo, embora, o interesse destes argumentos, defende-se a origem compósita das narrativas que a precedem e a necessidade de as enquadrar sociologicamente. O interesse ideológico da crónica é reduzido face à historiografia régia castelhana.
What is ontic vagueness?
Authors: Chibeni Silvio Seno
Published: December 2024

There is ample divergence among students of vagueness as to what exactly should be understood by a vague object, or by ontic, or metaphysical vagueness in general. In fact, the very intelligibility of the notion of a vague object has been called into question by important philosophers in the past, indicating that the task of finding a coherent, philosophically fertile characterization of the notion is not a simple one. This article aims to contribute to this undertaking, by identifying, examining and comparing some of the main proposals in the literature. It is suggested that we should try to characterize vague properties and relations independently of any particular view about vague objects, and then to formulate a criterion for vague objects in terms of indefinite instantiation of sharp properties. It is shown that this approach makes it easier to evaluate certain semantic-epistemic dismissive strategies concerning the possibility of there being vague objects. It is briefly indicated that if the objects are analysed with the theoretical and conceptual resources of quantum physics (and not of classical physics, as is ordinarily done), such dismissive strategies are seriously undermined.
Effects of Lanthanum on Structure of Sodium Borosilicate Glasses
Authors: Ben Zennou Meriem , Bachar Ahmed , Mabrouk Assia
Published: December 2024

Nuclear waste management poses a significant challenge in contemporary society, necessitating innovative approaches for confinement and characterization. This chapter addresses the synthesis and characterization of a model glass intended for nuclear waste encapsulation. Specifically focusing on the incorporation of lanthanum into the glass matrix, we detail the synthesis procedures and investigate its structural and mechanical implications. Utilizing advanced spectroscopic techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), Raman spectroscopy, and Brillouin scattering, we elucidate the intricate interactions between lanthanum ions and the glass structure. This contribution not only enhances our fundamental understanding of nuclear glass compositions but also provides insights into the development of robust strategies for nuclear waste containment.
Innovative GO Membranes
Authors: Maity Saurav Kumar , Tyagi Uplabdhi , Kumar Krishna , Kumar Gulshan
Published: December 2024

Traditional membrane technologies often suffer from limitations such as fouling, limited selectivity, and insufficient durability under harsh operating conditions. GO-based membranes, in this regard, offer a promising solution to these challenges due to their exceptional properties. This chapter provides a comprehensive exploration of GO membranes, emphasizing their transformative role in industrial wastewater treatment. The discussion extends to advanced fabrication techniques, innovations in scaling production, and the challenges encountered in the process. Strategies to enhance membrane performance and address issues like fouling are also examined, alongside the environmental and economic benefits of GO membranes, including their potential for carbon reduction and cost-effectiveness. Lastly, the chapter concludes with future perspectives, outlining emerging trends, interdisciplinary approaches, and recommendations for advancing GO membrane technology toward widespread industrial adoption, ultimately contributing to sustainable and efficient wastewater management.
Perovskite Progress
Authors: Kacimi-Naciri Hicham , Rguiti Mohamed , Mabrouk Assia , Ben Achour Mohamed Aymen , Lorgouilloux Yannick , Courtois Christian , Faska Nadia , Bachar Ahmed
Published: December 2024

The incorporation of strontium into Ba1-xSrxTiO3 compounds has a significant impact on their structural, electronic, optical, and mechanical properties. This study presents an analysis based on first principles calculations using density functional theory (DFT) to study the effects of strontium doping by varying Sr concentrations. The evolution of the structure, electronic band structures, optical and mechanical properties is examined to understand how Sr doping influences the fundamental characteristics of the material. The results highlight that Sr doping provides valuable information for tailored design of perovskite-type materials, thus optimizing their properties for various technological applications.
Trauma-Informed Gatekeeping
Authors: Munsey Beck A. , Holliman Ryan
Published: December 2024

It is important for counselor educators to focus on gatekeeping practices in a trauma-informed lens. Trauma-informed practices have been gaining popularity in mental health fields because of the number of people experiencing trauma in society and being mindful of inclusivity in the policies and procedures counselor educators create for their programs. This chapter focuses on a few concepts of leadership, gatekeeping, remediation strategies, and the challenges counselor educators/leaders face when gatekeeping. Leadership is broken down into counselor educators in leadership and leadership theory. Then, the gatekeeping section will include a focus on trauma informed practices. Next, remediation strategies of using faculty discussions, formal academic meetings, remediation plans, dismissal, behavioral assessment team(s), appeal process, and the challenges practicing trauma informed gatekeeping. The chapter will conclude with case studies to highlight information from the chapter in developing skills for practicing trauma informed gatekeeping through a leadership perspective.
Smart Water Management and Resource Conservation
Authors: Kumar Rajeev , Saxena Arti
Published: December 2024

Water is essential to every living being. Water management and resource conservation is very important to provide safe and clean water to all. Resources of water have been polluted and contaminated due to increasing population and urbanization. Irrigation and hydropower reservoir are other sources responsible for water stress on earth. The main aim of smart cities and urban development is to provide clean and safe water for everyone at low cost and in sustainable ways. Thus, it is necessary to conserve water resources and manage the water smartly. Use of non-conventional water resources for irrigation, aquaculture and aquifer recharge is one of the smart solutions to decrease the use of fresh water resources for these purposes. Machine learning is the smart solution for managing and conserving the water resources. Various machine learning models is applied for prediction tasks. However, deep learning is applied for categorization and regression task. The chapter objective is to provide the smart and sustainable solution for managing water resources and conservation in smart cities.
An Evolution of ASEAN Energy Policy on Renewable Energy Transition and Energy Sustainability for Carbon Neutrality
Authors: Bharti Mukesh Shankar
Published: December 2024

This study explores ASEAN energy policy for decarbonization in ASEAN countries. ASEAN is working as a regional organization in the Southeast Asia region and has proven to be a successful organization in the world. For many years ASEAN has been working on the installation of alternative energy sources in the region. The Renewable Energy Program was initiated by ASEAN to achieve carbon neutrality and promote renewable energy in its Member States. This paper delves into a critical area of energy policy and sustainability within Southeast Asia. The commitment of ASEAN nations to reduce greenhouse gas emissions and promote sustainable development, as outlined in the ASEAN Plan of Action for Energy Cooperation (APAEC) and the ASEAN Declaration on Renewable Energy, demonstrates a collective recognition of the importance of this issue. This paper qualitatively emphasizes the multifaceted nature of the challenge and the importance of a holistic approach to achieving decarbonization goals.
Circular Economy in the Construction Industry in India
Authors: Kazmi Rizwan , Chakraborty Manjari
Published: December 2024

The construction industry is highly resource intensive. The world is witnessing a situation where a major population, including India, will live in cities by 2050. The intensity of resource consumption will increase manifold in the construction industry across the globe and in India in the coming two decades. Consequently, nations worldwide have made a transitional shift in the development process from linear to circular models. The circular model aims at eliminating waste and regenerating the ecosystem. This article studies circular economy initiatives in the construction industry across the globe through a literature review that focuses on the understanding developed in the four broad areas of the circular built environment. The study further presents India's initiatives for circular construction. In conclusion, the article highlights the gap in circular construction practice in India based on the global state-of-the-art understanding. In the end, recommendations for circular construction in India are suggested, paving the way for a sustainable future of the built environment.
Parents: Do you think of safety when selecting toys for your children?
 
Authors: Perera Ruwanthi , Peiris Piyumaka , Perera Kavee , Guruge Malithi , Gunasekara Gihan
Published: December 2024

No abstract available
In memory of Vittorio Nobile (1940-2023), apidologist
Authors: Turrisi Giuseppe Fabrizio
Published: December 2024

The life and career of the Sicilian entomologist Dr. Vittorio Nobile (1940-2023), a specialist of Apoidea Anthophila and active at the University of Catania for more than forty years, are outlined. Brief biographic data and photographic references, along with essential information on his scientific contribution to the taxonomy and faunistics of Apoidea and other insects, are provided. Information on the type material of the 21 taxa described by Nobile (18 Apoidea, of which 15 species and 3 subspecies, plus 3 species of Aulacidae), a list of his forty-two publications, and a reference to the two patronymic taxa are also provided. The reference Italian bee collection realized by Vittorio Nobile includes more than 12,000 specimens in 126 entomological boxes, 124 medium-sized and 2 small-sized, representing more than 700 species (about 70% of the Italian bee fauna) and it has been donated to the University of Florence, Museum of Natural History “La Specola”, Section Entomology.
Towards evidence-informed action in promoting disability inclusion in Africa
Authors: Botha Michelle , Kahonde Callista K.
Published: December 2024

No abstract available.
Impact of Diverse Musical Genres on Blood-Feeding and Mating Behavior in Aedes aegypti Mosquitoes
Authors: Ni Chew Yan , Kassim Nur Faeza Abu , Ayub Noor Moukhni , Abuelmaali Sara Abdelrahman , Mashlawi Abadi M. , Dieng Hamady
Published: December 2024

Background & objectives:

Sound plays an important role in mosquito foraging and sexual interactions. Mosquitoes utilize acoustic signals for host location, sexual recognition, and mating, which is achieved through the rhythmic beating of their wings to generate distinct sounds characterized by specific flight tone frequencies.

Methods:

In this study, electronic music (Tremor by Dimitri Vegas, Martin Garrix and Like Mike) and country music (Country Road by John Denver) were played in high and low volumes to investigate the influence of different genres of music on the blood feeding and mating responses of Ae. aegypti. The observations encompassed monitoring the landing attempts, blood-feeding endeavors, and mating behavior of Ae. aegypti.

Results:

High-volume electronic and country music with elevated pitch and amplitude significantly reduced host attacks and blood-feeding attempts by female mosquitoes compared to low-volume or music-off conditions.

Interpretation & conclusion:

However, the significant reduction of successful copula was only observed in Ae. aegypti mosquitoes exposed under electronic music with high volume. As transmission of dengue is through blood feeding and mating, this discovery may open new possibilities for developing music-based control strategies against mosquito-borne diseases.
Prevalence and seasonal patterns of vector borne diseases in patients presenting with acute febrile illness in a tertiary care hospital in Puducherry- a prospective observational study
Authors: Chowdhury Sushmita Sana , Vinod R , Sabaritha B , Anand K
Published: December 2024

Background & objectives:

Vector-borne diseases (VBD) are a major public health concern. Globalization, urbanization & climate change are reasons for the emergence and re-emergence of VBDs. In our study, we looked into the prevalence of VBD infections around our tertiary care hospital in South India. The objective was to determine the prevalence of common VBDs like Malaria, Dengue, Japanese encephalitis (JE), Chikungunya and Scrub typhus in patients with acute febrile illness (AFI).

Methods:

This was a prospective laboratory based observational study. Blood samples from patients with AFI were tested for Dengue NS1 Antigen, IgM and IgG; and IgM antibodies for JE, Chikungunya and Scrub typhus using ELISA tests. Peripheral blood smear examination was performed for malarial parasite detection.

Results:

Total 802 samples were analysed. The sample positivity rate for VBD was 63.6% (510/802 samples) On diving the positive results across seasons in the study period, the VBD positivity rates were 66.3%, 49.1%, 61.2% and 67.3% for the first post-monsoon, summer, monsoon and the second post-monsoon seasons respectively- a trend of increased rates noted during the post-monsoon seasons. 192 samples (23.9%) were positive for scrub typhus alone, 189 samples (23.6%) were positive for dengue infection alone, six samples (0.7%) were positive for chikungunya infection alone, 121 samples (15.1%) were positive for dengue plus scrub typhus co-infection, two samples (0.2%) were positive for dengue plus chikungunya co-infection, while 292 samples (36.4%) showed negative results. None of the samples were positive for malaria and Japanese encephalitis.

Interpretation & conclusion:

Scrub typhus and dengue were the most prevalent VBDs in concordance with the prevalence pattern noted in other studies in South India. Increasing awareness and surveillance of the VBDs, developing stringent control policies, easy access to testing and initiating early appropriate therapy can help reduce the incidence of VBDs.
Coverage Probability of EH-enabled LoRa networks - A Deep Learning Approach
Authors: Nguyen Thi-Tuyet-Hai , Cong-Hung Tran , Hong-Son Nguyen , Hanh Tan , Trung Duy Tran , Tu Lam-Thanh
Published: December 2024

The performance of energy harvesting (EH)-enabled long-range (LoRa) networks is analyzed in this work. Specifically, we employ deep learning (DL) to estimate the coverage probability (Pcov) of the considered networks. Our study incorporates a general fading distribution, specifically the Nakagami-m distribution, and utilizes tools from stochastic geometry (SG) to model the spatial distributions of all nodes and end-devices (EDs) with EH capability. The DL approach is employed to overcome the limitations of model-based methods that can only evaluate the Pcov under simplified network conditions. Therefore, we propose a deep neural network (DNN) that estimates the Pcov with high accuracy compared to the ground truth values. Additionally, we demonstrate that DL significantly outperforms the Monte Carlo simulation approach in terms of resource consumption, including time and memory.
On the free boundary for thin obstacle problems with Sobolev variable coefficients
Authors: Andreucci Giovanna , Focardi Matteo , Spadaro Emanuele
Published: December 2024

We establish a quasi-monotonicity formula for an intrinsic frequency function related to solutions to thin obstacle problems with zero obstacle driven by quadratic energies with Sobolev

W^{1,p}

coefficients, where

p

is bigger than the space dimension. From this, we deduce several regularity and structural properties of the corresponding free boundaries at those distinguished points with finite order of contact with the obstacle. In particular, we prove the rectifiability and the local finiteness of the Minkowski content of the whole free boundary in the case of Lipschitz coefficients.
Applying deep learning to detect abnormal event log traces: a non-rule-based framework
Authors:   Montclair State University, Wang Yunsen , Chiu Tiffany ,   The State University of New York at New Paltz, Vasarhelyi Miklos A. ,   Rutgers, the State University of New jersey
Published: December 2024

Process mining is an efficient method that can analyze the full population of transactions using the event log of business processes. Conventional rule-based process mining techniques can detect anomalies; however, it tends to trigger a large number of false alarms. To improve the efficiency of anomaly detection using process mining, this study adopts a deep learning-based classification approach to detect anomalies in the traces of event logs. This approach contributes to the literature by proposing a non-rule-based process mining technique based on deep learning. Results demonstrate that the proposed non-rule-based process mining method can help auditors focus on transactional anomalies.

Keywords: Process mining, deep learning, anomaly detection, fraudulent activities.
Automotive Cybersecurity: Defend the Future of Connected Vehicles
Authors: Mahendrakar Shrinidhi , Madarla Manoj , Gangapuram Siva , Dadoo Vishal
Published: December 2024

Cybersecurity, particularly in the automotive sector, is of paramount importance in today’s digital age. With the advent of connected commercial vehicles, which leverage telematics for efficient fleet management, the landscape of automotive cybersecurity is rapidly evolving. These vehicles, integral to logistics and transportation businesses, are becoming increasingly connected, thereby escalating the risks associated with cybersecurity threats.

These commercial vehicles are becoming prime targets for cyber-attacks due to their connectivity and the valuable data they hold. The potential consequences of these cyber-attacks can range from data breaches to disruptions in fleet operations, and even safety risks. This paper analyses the unique challenges faced by the commercial vehicle sector, such as the need for robust telematics systems, secure communication channels, and stringent data protection measures.

Case studies of notable cybersecurity incidents involving commercial vehicles are presented, providing valuable insights into the modus operandi of cybercriminals. Strategies and best practices to mitigate these risks are proposed, emphasizing the need for secure vehicle architecture and design, intrusion detection systems, and regular OTA updates.

The role of employee training programs in enhancing cybersecurity awareness is also highlighted. Emerging trends like AI and machine learning in threat detection, blockchain technology for secure data transmission, and collaborations with ethical hackers for vulnerability assessment are discussed.

The paper reviews the current regulatory landscape, stressing the need for international standards specifically for connected commercial vehicles. It concludes with an outlook on anticipated developments in automotive cybersecurity, recommendations for industry stakeholders, and the assertion that prioritizing cybersecurity is crucial for the future of the commercial vehicle industry.
A Review of Hydrogen Storage System (HSS) and Hydrogen Internal Combustion Engine (H2-ICE) for the Potential H2-ICE Vehicle
Authors: Biswas Sanjoy , Naik Amit Kumar , Kashyap Krishna
Published: December 2024

The different energy policies and legislations across the globe, unions, or country wise are the key influencer for evaluation of Transport Industry in both advancement of Technologies and Ecosystem development. Accordingly, European Climate law is focusing to achieve net zero greenhouse (or carbon neutral) gas emissions for EU (European Union) countries by 2050. Similarly in India, National Green Hydrogen Mission (NGHM) by Ministry of New and Renewable Energy (MNRE) is aiming for significant decarbonization and to become market leader in Green Hydrogen Transition. Hydrogen is potential fuel for H2-FCEV (Hydrogen Fuel Cell Electric vehicle) and H2-ICE (Hydrogen -Internal combustion Engine) due to its carbon free molecule and other properties. This review paper is focusing on comprehensive study of different aspects of H2- ICE vehicle. Key study areas are mainly Hydrogen (H2) as fuel, Hydrogen Storage System (HSS), H2-ICEs, Hydrogen storge pressure and H2-ICE vehicle architecture. The advantages, challenges and gaps in present technology are discussed. This paper aims to provide an overview and potential of carbon neutral emission technology solution namely H2-ICEs based on scientific literature survey and try to conclude considering current knowledge and Technological maturity. Further, this paper covers the comparison of H2-ICE vehicle architecture among the HPDI and SI Engine. This consists of optimization of HSS within the vehicle Architecture. The study indicates that High-Pressure Direct Injection (HPDI) Engine type H2-ICE vehicle is potentially more favorable than Spark Ignition (SI) type H2-ICE in terms of Vehicle Performance, Applicability (operation / use-case), engine efficiency and safety. Same time, Engine (HPDI - H2-ICE) and vehicle complexity level is at higher side for HPDI-H2-ICE vehicle.
The Ranking of Major Noise Sources of a Multi Cylinder Diesel Engine
Authors: Goel Arunkumar , Meena Avadhesh Kumar
Published: December 2024

In the present problem, we have studied mechanical & aero dynamic induced noise. Mechanical noise refers to noise generated by the vibrating surface of the engine structure, engine components and engine accessories after excitation by reciprocating or rotary components. Aero dynamic noises are due to air intake and exhaust of the gases. In the present study, the identification of the engine sources such as Engine Structural Noise, Fuel Pump Noise, Oil Pan Noise, Air Suction Noise and Exhaust Noise has been performed.

These four noise sources like Fuel pump, oil pan, Suction noise and Exhaust noise were isolated through wooden/plastic/steel ducts by acoustical duct method for a 80.85 kW diesel engine coupled with a hydraulic dynamo meter at different speeds and load conditions. The results were compared with the overall/structural Sound Pressure Level (SPL). The SPL of engine sources like oil Pan, fuel pump & Air intake are also plotted to show the ranking of all sources and also checked the impact of speed and load on noise ranking of the components/systems of the engine.
Novel UWS Injection Technique for SCR Performance Improvement
Authors: Venkatachalam Palaniappan , Shiva Shashidhar , Govindarajan Vaishali , Soni Prerna , Patidar Sachin
Published: December 2024

The present study aims to meet the Euro-VII compliance applicable for internal combustion engines (diesel and hydrogen) by improving the performance of selective catalytic reduction (SCR) system using a novel urea water solution (UWS) mist injection technique. In SCR system, the interaction of exhaust gas and UWS resulted into ammonia (NH3) species, which is mixed with harmful NOx emission and converted into harmless by-products. Despite the proven technology, there are several challenges presented in the existing system which restricts the ideal performance of SCR system especially during cold starting condition: (i) incomplete droplet evaporation (ii) solid deposit formation (iii) non uniformity of NH3 distribution at the catalyst entrance. The past studies shows that the droplet size plays a major role in this context. Further, it is noted that the smaller size droplets are desirable to overcome the impediments and enhance the efficiency of SCR application. Therefore, it is decided to investigate the effect of mist (contains very fine size droplets) injection on the important factors of SCR system such as formation and spatial uniformity of NH3 species, and urea solid deposition on the mixing chamber wall. For this purpose, the study is carried out using the numerical simulation where the Reynolds Average Navier Stoke (RANS) and discrete phase model (DPM) is used to simulate the exhaust gas and mist, respectively. The results highlight that using the mist injection is a promising solution as it not only promotes the droplet evaporation rate but also enhances the NH3 distribution which leads to a homogeneous mixture of NH3/NOx. Further, it is noted that the amount of urea solid deposition is significantly smaller on the mixing chamber wall.
Safe Phase Current Measurement for Motor Control Applications
Authors: Birari Ashwini Anil
Published: December 2024

As the automotive industry progresses towards electrification, driven by need for sustainability and reduced emissions, the traction inverter emerges as pivotal component of electric vehicles (EVs). Serving as the interface between the vehicle’s control systems, motor and battery. The traction inverter’s performance directly impacts the efficiency, sustainability and overall functionality of electric drive systems. A critical function of the traction inverter is measurement of phase currents in each motor phase, enabling precise control of the motor’s torque and rational speed. This capability is essential for optimizing efficiency, enhancing performance and ensuring safety key aspects of modern electric vehicle technology. This paper introduces method for measuring phase currents in Permanent Magnet Synchronous Motors (PMSM) utilizing the Enhanced Versitile Analog-Digital-Converter (EVADC) integrated within Infineon’s Aurix Tricore. This technology preferred for its rapid conversion speed and advanced features for synchronization and parallel sampling. This approach facilitates synchronous three phase motor current measurement at the midpoint of the Pulse Width Modulation (PWM) trigger signal. By capturing data at this critical point, we effectively eliminate current ripples, which is crucial for accurate motor control technique such as Field Oriented Control (FOC), thereby enhancing the management of torque and rotational speed. Moreover, this work adheres to redundancy principles aimed at preventing single point failures. By implementing critical safety metrics and confirmations measures (SPFM and LFM) necessary for compliance with ISO26262 standards. Redeundnacy checks on measured phase currents support error mitigation, fault detection and overall system safety. This comprehensive approach contributes to advancement of electric vehicle technology but also emphasizes the importance of robust phase current measurement techniques achieving greater reliability and efficiency in electric vehicle operation.
Electric Battery Cell, Module, and Battery Pack FE Modeling for Multiphysics Simulation
Authors: Jain Tripti , Bonala Sastry , Dangare Anand
Published: December 2024

Electrified powertrain is the essential need to meet the C02 and NOX emissions compliance. Thereby focus of automotive industry is shifting towards to Electric Vehicle (EV). Thermal Runaway (TR) is still a big challenge to the safety of the EV. The major cause of TR is internal short-circuit of batteries under external mechanical abuse. When Anode and cathode of the battery comes in contact and short circuit happens. Internal short circuit is causing high amount of current flow and energy generation which leads to high increase in temperature. The approach that is used till date by OEMs is to protect the battery pack from structural damage during crash resulting into overdesigning of the vehicle.

In this paper, detailed FE modeling of the battery system is considered for evaluating internal short circuit and TR. Solid Randle circuit is used for Multiphysics coupling simulation in Ls-dyna. Solid Randle circuits solves this Multiphysics and derives these electrical and thermal parameters which makes this methodology simple and effective. By integrating thermal, electrical, and mechanical behaviors within a comprehensive simulation framework, we aim to accurately predict the onset and progression of TR during crash event.

The approach is to analyze the electrical & thermal parameters on the cell level and then adapt the same modeling methodology to battery module and battery pack level which is further used for full vehicle study.

The results provide insights into the failure mechanisms and propagation pathways, facilitating the optimization of battery design and safety features. And help OEMs to evaluate battery performance for internal and external short circuit during crash events helps in optimal way and evaluate critical TR of the battery system.
Microstructural Characterization of Aluminium Alloys Used in Automotive Body Parts
Authors: Deshmukh Mansi , Jain Vikas , Misal Swapnali , Paliwal Lokesh
Published: December 2024

To meet light-weighting and safety target of automotive vehicles, different Aluminium alloys are used in various body parts. Apart from conventional manufacturing process of gravity die casting (GDC), advanced manufacturing process such as low pressure die casting (LPDC), high pressure die casting (HPDC) and extrusion processes are also used to form complex automotive body parts. Steel parts are majorly used in automotive applications across world. However, steel has limitations with respect to light-weighting. To achieve light-weighting, now a days, there is trend to use these complex Aluminium parts in automotive industry to replace steel and integrate multiple parts into a single one. Aluminium has emerged as great potential for light-weighting and reducing complexity of handling multiple parts at an automotive plant. There is a challenge to identify suitable etchant for microstructural characterization of Aluminium alloy parts that can be made through various manufacturing processes. This paper discusses Aluminium alloy’s microstructural characterization, suitable etchant selection, identification of alloy and its manufacturing process.
Aerodynamic Analysis of Electric Cargo Scooter with Unified Modelling and Simulation
Authors: Balachandran Karthik , Das Alok , Shinde Pranav
Published: December 2024

Aerodynamic analysis is a primary requirement in the development of electric scooters to predict the impact of air flow around the vehicle on critical performance parameters including the overall range, vehicle stability due to wind loads, air cooling of electric motor and battery. Any new design of vehicle requires an aerodynamic evaluation to estimate the variations in drag forces with speed. It is prohibitively expensive and time consuming to perform full-scale model wind tunnel tests on each variant of the vehicle configuration for wide range of driving scenarios. Physics-based 3D simulation is the preferred approach in the present context and the use of Computational Fluid Dynamics (CFD) for such cases has been well understood and established. Although only the external shape changes make a difference to external aerodynamics, sometimes even a small variation in shape could trigger unwanted flow behavior leading to large drag forces, or enhance the vehicle performance by reducing the drag, with less aggressive design changes. In the present work, we study aerodynamics of world’s first Compact Logistics Vehicle (CLV) – a purpose-built electric cargo scooter that can accommodate a rider and a pillion along with a significant amount of dedicated cargo space. We already established the methodology and best practice for a variant of the present vehicle which could accommodate only the rider and have implemented the same in the current study. A total of 15 different scenarios including three different vehicle and rider combinations across a range of velocities (6 m/s or 21.6 km/h, 8 m/s or 28.8 km/h, 11 m/s or 39.6 km/h, 16 m/s or 57.6 km/h and 22 m/s or 79.2 km/h), have been studied, by placing the vehicle in a virtual wind tunnel and simulating the velocity and pressure distribution, and most importantly total drag force for each scenario. The three cases comprise the stand-alone vehicle, vehicle with the rider, and vehicle including the rider and the passenger (pillion). The result of this study indicates only a slight variation in the drag due to the presence of a rider along with the passenger (pillion). We are able to capture the aerodynamic characteristics of the recirculation zones in all of these cases. In addition to the variations in the inlet velocities, we also studied the effect of the turbulence intensities (5%, 10%, and 20%) on the over-all drag coefficient.
Characterization of Cut and Chip Damage in Ultra Low Rolling Resistance Tire for Electric Vehicles
Authors: Mishra Nitish , Singh Ram Krishnan
Published: December 2024

Since the inception of battery driven electric vehicles in the automotive world, there has been a constant challenge in maximizing the range of an electric vehicles through various means including battery technology, vehicle weight optimization, low drag coefficients etc. The tires being a viscoelastic composite material have now become a vital to the range performance of an EV. The rolling resistance of a tire is now become a hotter topic than ever. The rolling resistance coefficient (RRC) is the measure of energy loss during rolling due to viscoelastic dissipation in the tire. The viscous dissipation in tire arises due to hysteresis in the various components of a tire including tread, sidewall, inner liner, apex etc rubber compounds. The internal friction between layers of body ply, steel belts and tread crown ply also contribute to the internal heat generation. Therefore, the development of ultra-low RRC tires is a serious challenge for tire engineers. Nevertheless, the recent advances in the tire technology, which include introduction of new generation reinforcing fillers in rubber compounds, tread pattern design and construction matrix optimization, allow the tire experts to carefully select the suitable material and design parameters to meet the performance characteristics and durability of an EV tire.

This paper demonstrates the scientific way of analysing cut and chip failure in tires which is one of the most frequent and troublesome challenges in the development cycle of low RRC tires. The various material characterization techniques which include viscoelastic behaviour of tread rubber compound, polymer-filler interaction and filler dispersion in tread rubber compound were studied along with the tire footprint characteristics. Eventually a better comprehensive understanding was drawn on the impact of material behaviour and tire characteristics on the cut and chip damage of ultra-low RRC tires for Electric Vehicle (EV) vehicles.
A Parametric Analysis of Relationship between Tyre and Braking Performances in Electric Vehicle
Authors: V Padmasri , Vellandi Vikraman , Sundaram Raghupathi , Singh Ram Krishnan , P Praveen , Chittibabu Santhosh
Published: December 2024

Sports Utility Vehicles (SUVs) Braking performance is a critical parameter, and it is described by the measure of stopping distance & stability of the vehicle at a specified speed. When it comes to electric vehicles, balancing tyre performance parameters like RRc, traction, wear, ride and handling, weight and NVH is challenging due to higher axle weights, higher moment of inertia and high instant torque delivery. This study presents the braking performances of EV-intended tyres at various contact surfaces in both dry & wet conditions. Impact of tyre design attributes like tyre tread pattern, contact patch, tread compound, tyre carcass construction & characteristics studied on 3 different tyres including ultra-high-performance tyres on braking performances. This paper contains the study & analysis of 1) Footprint analysis concerning the shape of the contact patch, pressure distribution, land-sea ratio, and contact area 2)Tyre tread design such as NSD, grooves, ribs & sipes design and pitch length 3) Compound property studies like hardness, modulus, tensile strength, tear strength & elongation at break 4)Materials like polymer blend, filler ratio & new-gen materials 5)Tyre performance characteristics which are contributing to vehicle stability like lateral stiffness, longitudinal stiffness, dynamic stiffness & mu slip curves and 6) Longitudinal & lateral forces at various speed conditions with CAE Simulations.

BEV requires low rolling resistance for improving vehicle range and which calls for reducing the hysteresis of tyre tread compound which affect vehicle barking performance at wet surface and it should be compensated by adjusting other design parameters.

Mu slip curve very important characteristics for designing brakes system to get peak mu and programming software for ABS system.
A Simulation Based Methodology for Optimizing Correlation of Brake Disc Temperature
Authors: Negi Ayush Singh , Kochhar Raman
Published: December 2024

Brake disc temperature is a critical factor influencing the performance and wear characteristics of braking systems in automobiles. Hence it is very important to optimize the correlation of brake disc temperature prediction with test. In this study critical parameters of Brake Disc temperature evaluation are identified, and algorithm is used to optimize the critical parameters to achieve the correlation of prediction with experiment data. Through a series of controlled experiments and simulations, disc temperatures are monitored under different braking conditions and simultaneously input parameters for prediction are optimized to achieve the correlation. Statistical methods were applied to evaluate the observed correlations and to model the predictive behavior of brake disc temperatures.

Finally, A front-loading tool is developed to optimize the brake disc keeping target thermal capacity via algorithm. The findings of this study are expected to contribute to the enhancement of brake system design by providing insights into thermal dynamics during braking. This can lead to the development of more efficient cooling strategies and materials that are better suited to dissipate heat, thereby improving safety and performance.