bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Strong Gravity and the Nuclear Equation of State on Neutron-star Common-envelope Accretion
Authors: Holgado A. Miguel , Silva Hector O. , Ricker Paul M. , Yunes Nicolás
Published: April 2021

Common-envelope evolution is important in the formation of neutron star binaries within the isolated binary formation channel. As a neutron star inspirals within the envelope of a primary massive star, it accretes and spins up. Because neutron stars are in the strong-gravity regime, they have a substantial relativistic mass deficit, i.e., their gravitational mass is less than their baryonic mass. This effect causes some fraction of the accreted baryonic mass to convert into neutron star binding energy. The relativistic mass deficit also depends on the nuclear equation of state, since more compact neutron stars will have larger binding energies. We model the mass growth and spin-up of neutron stars inspiraling within common-envelope environments and quantify how different initial binary conditions and hadronic equations of state affect the post-common-envelope neutron star’s mass and spin. From these models, we find that neutron star mass growth is suppressed by ≈15%–30%. We also find that for a given amount of accreted baryonic mass, more compact neutron stars will spin-up faster while gaining less gravitational mass, and vice versa. This work demonstrates that a neutron star’s strong gravity and nuclear microphysics plays a role in neutron-star-common-envelope evolution, in addition to the macroscopic astrophysics of the envelope. Strong gravity and the nuclear equation of state may thus affect both the population properties of neutron star binaries and the cosmic double neutron star merger rate.
Ina Lunar Irregular Mare Patch Mission Concepts: Distinguishing between Ancient and Modern Volcanism Models
Authors: Qiao Le , Head James W. , Wilson Lionel , Ling Zongcheng
Published: April 2021

The Ina irregular mare patch, an ∼2 × 3 km summit depression on an ancient ∼22 km diameter shield volcano, displays two very enigmatic units: (1) dozens of dark convex-upward mounds and (2) a very rough, optically immature floor unit with very sharp morphologic contacts between the two. Controversy surrounds the age interpretation of Ina; superposed impact crater size–frequency distributions (CSFDs) suggest an age of ∼33 Ma, consistent with the presence of sharp contacts between the units and indicating that mare volcanism continues to today. Models of the terminal stages of volcano summit pit crater activity suggest an age coincident with the building of the shield, ∼3.5 Ga; these models interpret the CSFD age and sharp contacts to be due to an extremely porous lava lake floor and extrusion and solidification of magmatic foams. We present robotic–human exploration mission concepts designed to resolve this critical issue for lunar thermal evolution.
Comparative osteology of three endemic cichlids (Iranocichla spp.) (Actinopterygii, Perciformes, Cichlidae) from southern Iran
Authors: Dastanpoor Neda , Keivany Yazdan , Ebrahimi Eisa
Published: April 2021

Iranian cichlids are isolated disjunct populations of the African cichlids group, restricted to the Hormuz Strait region in the Hormuz basin, and are a very important group from both zoogeographic and phylogenetic points of view. Thus, the osteological structures, as one of the most reliable structures, of the three nominal species of Iranian cichlid fishes,Iranocichla hormuzensisCoad, 1982, from the Mehran River,Iranocichla persaEsmaeili, Sayyadzadeh et Seehausen, 2016, from Khorgo hot spring, andIranocichlasp., from the Kol River were described and compared. Ten specimens of each species were cleared and stained with Alcian blue and Alizarin red. A digital camera was used for taking pictures and CorelDraw X6 software for preparing drawings. The three species have some differences in the caudal fin skeleton, shape of the urostyle, neural spine of preural 2, hypural spines 2, and 3, anterior part of parhypural and hypurapophysis, the size of neural spines of preural 2 and 3, hypural 3 and 4, and epurals. Although there are some differences among the species, osteology of these species is very conservative and other traits like behavioral and molecular should be used.
First records of the bandfin scorpionfish, Scorpaenopsis vittapinna (Actinopterygii, Scorpaeniformes, Scorpaenidae), from Australia
Authors: Wibowo Kunto , Motomura Hiroyuki
Published: April 2021

Seven specimens (15.6–43.5 mm standard length) of Scorpaenopsis vittapinna Randall et Eschmeyer, 2002 (Scorpaenidae), a widely distributed Indo-West Pacific species, are recorded from Australian waters for the first time. A full description of the specimens is given, and intraspecific variations in comparison with the type specimens are noted.
Redescription of a rare cusk eel, Pycnocraspedum squamipinne (Actinopterygii, Ophidiiformes, Ophidiidae), from Bay of Bengal
Authors: Teena Jayakumar T. K. , Murugan A. , Kumar Ajith T. T. , Lal Kuldeep K.
Published: April 2021

Pycnocraspedum squamipinne Alcock, 1889 is a rare species of pelagic cusk eel described from specimens collected off the Bay of Bengal. The descriptive literature on P. squamipinne is limited to the original description owing to the rarity in collections. The genus and the species need a thorough revision to identify specific characters of taxonomic importance as the descriptive information regarding the species in the genus Pycnocraspedum is limited to the holotypes and syntypes. Fifteen fresh specimens of P. squamipinne were collected from the Chennai coast, Tamil Nadu, Bay of Bengal region. The syntypes of P. squamipinne (ZSI F 11700 and ZSI F 11703) available at the Zoological Survey of India, Kolkata were examined. The morphometric and meristic characters of P. squamipinne were compared with those of syntypes and other species of the genus. Molecular analysis was carried out using partial mtDNA cytochrome oxidase subunit I gene (COI). The specimen is deposited in the national fish repository of the ICAR, National Bureau of Fish Genetic Resources, Lucknow, India. A detailed redescription of P. squamipinne based on the syntypes and fifteen recently collected specimens are provided. A detailed comparison with other species of the genus is also provided which helps in establishing the taxonomic identity of P. squamipinne. Molecular information was generated which would help in the species identification of this rare deep-sea species. This study provides morphological and molecular information of the rare cusk eel, P. squamipinne, which would help in the precise identification of the species. However, due to paucity, the majority of species of the genus are still only known from single specimens and comprehensive examination of holotypes and intensive sampling is needed to better understand the species identity and distribution.
Beginning the quest: phylogenetic hypothesis and identification of evolutionary lineages in bats of the genus Micronycteris (Chiroptera, Phyllostomidae)
Authors: Morales-Martínez Darwin M. , López-Arévalo Hugo F. , Vargas-Ramírez Mario
Published: April 2021

Thirteen species of Neotropical bats of the genus Micronycteris are currently recognized and are allocated to four subgenera Leuconycteris, Micronycteris, Schizonycteris, and Xenonectes. Despite that, the presence of polyphyletic clades in molecular phylogenies suggests that its diversity is underestimated. Additionally, the incorrect identification of some genetic sequences, the incorrect assignation of available valid names, and restricted geographic sampling have biased the identification of independently evolutionary lineages within Micronycteris. In this study, several unknown genealogical lineages in the genus are identified and an updated phylogenetic hypothesis is proposed using mitochondrial and nuclear DNA fragments. The phylogenetic analyses congruently showed all individuals in four well-supported subgenera, but M. schmidtorum was revealed as the sister taxon of M. brosseti in the subgenus Leuconycteris. Twenty-seven different genealogical lineages were identified. These included eight confirmed species: M. brosseti, M. buriri, M. giovanniae, M. matses, M. schmidtorum, M. simmonsae, M. tresamici, and M. yatesi. Nineteen either allopatric or parapatric candidate species were also confirmed, two within the M. hirsuta complex, nine within the M. megalotis complex, seven within the M. minuta complex, and one corresponding to “M. sp.”. These results revealed an extensive undescribed diversity within each subgenus of Micronycteris. Nevertheless, the evolutionary processes associated with the specific radiations are poorly understood. This is just the beginning of the assessment of the taxonomy and systematics of Micronycteris, which requires additional integrative taxonomical approaches for its advance.
Corrigenda: Three new and one little-known species of Hypogastruridae (Collembola) from Russia’s northeast. ZooKeys 1005: 1–20. https://doi.org/10.3897/zookeys.1005.54882
Authors: Babenko Anatoly , Efeykin Boris , Bizin Mikhail
Published: April 2021

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A novel collocation approach to solve a nonlinear stochastic differential equation of fractional order involving a constant delay
Authors: Banihashemi Seddigheh , Jafaria Hossein , Babaei Afshin
Published: April 2021

In present work, a step-by-step Legendre collocation method is employed to solve a class of nonlinear fractional stochastic delay differential equations (FSDDEs). The step-by-step method converts the nonlinear FSDDE into a non-delay nonlinear fractional stochastic differential equation (FSDE). Then, a Legendre collocation approach is considered to obtain the numerical solution in each step. By using a collocation scheme, the non-delay nonlinear FSDE is reduced to a nonlinear system. Moreover, the error analysis of this numerical approach is investigated and convergence rate is examined. The accuracy and reliability of this method is shown on three test examples and the effect of different noise measures is investigated. Finally, as an useful application, the proposed scheme is applied to obtain the numerical solution of a stochastic SIRS model.
Evaluación del estado de elementos estructurales del Mercado de Legazpi: Ataque por sulfatos al hormigón y corrosión de las armaduras
Authors: Chinchón-Payá Servando , Torres Julio , Rebolledo Nuria , Sánchez Javier
Published: April 2021

El presente trabajo describe la metodología empleada para el estudio del estado del hormigón de zapatas, soportes, así como del terreno en varias zonas del edificio del Mercado de Legazpi en Madrid (España). Se han analizado los pilares, los arranques de pilar, las zapatas y los terrenos donde estos últimos están enterrados. Se ha realizado una inspección visual y una caracterización por ultrasonidos, lo cual ha permitido la selección de muestras para el posterior análisis en laboratorio mediante difracción de rayos X y microscopía electrónica de barrido, así como cuantificación de cloruros y sulfatos. Se han encontrado afecciones de corrosión de las armaduras en zonas puntuales, que son debidas tanto al anterior uso de la estructura como al envejecimiento de la misma. También existe una importante cantidad de sulfatos en los terrenos, de origen antrópico, que explicarían la formación de productos de ataque sulfático en las zapatas. El ataque por sulfatos, aunque presente, no parece suponer una merma importante en la integridad de la estructura.
Satisfacción con la vida según la contribución a la esfera pública y privada en las parejas españolas adultas
Authors: Gumà Jordi , Arpino Bruno
Published: April 2021

El objetivo del trabajo es, tomando como referencia la revolución de género, explorar si la desigual participación relativa en la provisión de recursos económicos y la realización de las tareas domésticas en el hogar se asocia con diferencias en los niveles de satisfacción con la vida para las mujeres y hombres adultos que conviven en pareja en España. Para ello, se analizan mediante modelos de regresión lineal las muestras españolas para la Encuesta Social Europea de 2004 y 2010 conjuntamente. En España se observan dos situaciones diferentes definidas por la distinta capacidad económica del hogar: en los hogares sin dificultades económicas, los comportamientos de género tienen una menor influencia sobre los niveles de satisfacción con la vida; sin embargo, en aquellos con dificultades económicas los perfiles de género más tradicionales se asocian con una mayor satisfacción masculina, al contrario que en el caso femenino.
Calibration of Metal Oxide Semiconductor Gas Sensors by High School Students
Authors: Höfner Sebastian , Schütze Andreas , Hirth Michael , Kuhn Jochen , Brück Benjamin
Published: April 2021

A wide range of pollutants cannot be perceived with human senses, which is why the use of gas sensors is indispensable for an objective assessment of air quality. Since many pollutants are both odorless and colorless, there is a lack of awareness, in particular among students. The project SUSmobil (funded by DBU – Deutsche Bundesstiftung Umwelt) aims to change this. In three modules on the topic of gas sensors and air quality, the students (a) learn the functionality of a metal oxide semiconductor (MOS) gas sensor, (b) perform a calibration process and (c) carry out environmental measurements with calibrated sensors. Based on these introductory experiments, the students are encouraged to develop their own environmental questions. In this paper, the student experiment for the calibration of a MOS gas sensor for ethanol is discussed. The experiment, designed as an HTML-based learning, addresses both theoretical and practical aspects of a typical sensor calibration process, consisting of data acquisition, feature extraction and model generation. In this example, machine learning is used for generating the evaluation model as existing physical models are not sufficiently exact.
Synthesis of Chitosan-Chitosan Composite Silica by Gamma Irradiation and Multi-Stage Deacetylation
Authors: Rohyami Yuli , Puspasari Ifa , Kundari Noor Anis
Published: April 2021

The Study on synthesis of chitosan prepared by gamma irradiation and multi-stage deacetylation as chitosan-silica membrane has been carried out. Synthesis of chitosan is carried out by deproteination with papain, demineralization, and deacetylation. Deacetylation of chitosan using gamma irradiation with 0, 5, 10, 15, 20, and 25 kGy and two and multi-stage deacetyllation. The synthesis of chitosan silica composite using sol gel method with the ratio of 1:1; 1:2; and 1:3. Based on the study, gamma irradiation increase deacetylation degree of chitosan and minimize the sodium hydroxide needed for deacetylation chitosan. The multi stage deacetylation increase the efficiency procedure for increase deacetylation degree of chitosan. Chitosan-silica composite has been synthesized by sol gel method. The gamma radiation doses have significantly influence on the deacetylation degree of chitosan. Gamma irradiation and multi stage deacetylation increase the efficiency procedure for preparation chitosan and chitosan-silica composite.
Bioanalytical Method Validation for the Determination of Warfarin in Spiked-Saliva Using Fluorometric HPLC for TDM Application
Authors: Wibowo Ari , Nurbaiti Shabrina , Ningrum Vitarani Dwi Ananda
Published: April 2021

Saliva becomes an alternative biological matrix for therapeutic drug monitoring (TDM) application since there is a strong correlation between warfarin plasma concentration and saliva; further, the sampling is non-invasive and more comply with pediatric and geriatric patients. This study aims to validate the parameters of the warfarin bioanalytical method in spiked-saliva according to the criteria from the Food and Drug Administration (FDA) in the Guidance for Industry Bioanalytical Method Validation. The method used is Fluorometric HPLC with an excitation wavelength of 310 nm and an emission wavelength of 390 nm. The mobile phase involved is phosphate buffer-methanol, and the stationary phase is C18. The LoD and LoQ obtained are 0.71 ng/mL and 2.16 ng/mL, respectively. The coefficient of variation and %diff in the selectivity, accuracy, and precision parameters have met the criteria of the bioanalytical method of less than 20%. Meanwhile, the average %recovery is 101.30%. To conclude, the developed warfarin bioanalytical method has fulfilled the established criteria. It can, therefore, be used to determine warfarin concentration in saliva as an alternative method for TDM services in the clinical domain.
Solid State Mixing Preparation of CaO/Bentonite Nanocomposite and its Application to Improve the Quality of Patchouli Oil
Authors: Wijaya Karna , Utami Maisari , Syoufian Akhmad , Murifal Ahmad Iskandar
Published: April 2021

A novel, highly active and effective adsorbent has been developed using solid state mixing method of natural bentonite and CaO. The so called CaO/bentonite nanocomposite was determined the optimum heating temperature and bentonite-to-CaO ratio to enhance the quality of patchouli oil by purification process technology. The adsorbents were characterized by XRD, FTIR, SEM, GSA and TG/DTA. The total acid value of patchouli oil was determined by using KOH. The test method to determine physical and chemical properties of patchouli oil in Indonesia has been set nationally through SNI 06-2385-2006. A significant decrease in acid value of patchouli oil (from 5.42 to 0.34 mg KOH/g oil) was observed after purification of patchouli oil over CaO/bentonite-300 (20:80) nanocomposite. After patchouli oil purification over CaO/bentonite-300 (20:80), the concentration of patchouli alcohol (PA) was increased from 33.08 to 34.82%, while Fe content was decreased from 4.25 to 1.56 ppm.
Unsteady Magnetohydrodynamic Mixed Convective Flow of a Reactive Casson Fluid in a Vertical Channel Filled with a Porous Medium
Authors: Rundora Lazarus
Published: April 2021

This article analyses the thermal decomposition in an unsteady MHD mixed convection flow of a reactive, electrically conducting Casson fluid within a vertical channel filled with a saturated porous medium and the influence of the temperature dependent properties on the flow. The fluid is assumed to be incompressible with the viscosity coefficient varying exponentially with temperature. The flow is subjected to an externally applied uniform magnetic field. The exothermic chemical kinetics inherent in the flow system give rise to heat dissipation. A technique based on a semi-discretization finite difference scheme and the shooting method is applied to solve the dimensionless governing equations. The effects of the temperature dependent viscosity, the magnetic field and other important parameters on the velocity and temperature profiles, the wall shear stress and the wall heat transfer rate are presented graphically and discussed quantitatively and qualitatively. The fluid flow model revealed flow characteristics that have profound ramifications including the increased heat transfer enhancement attributes of the reactive temperature dependent viscosity Casson fluid flow.
Synthesis of Ammonia Directly from Air and Water via a Single-Chamber Reactor Using Lanthanum Chromite-Based Composite as an Electrocatalyst
Authors: Amar Ibrahim A. , Ahwidi Mohammed M.
Published: April 2021

Carbon-free electrosynthesis of ammonia using water (H2source) and air (N2source) is promising technology to reduce the global CO2emission resulting from the industrial ammonia production process (Haber-Bosch). In this study, electrocatalysis activity of non-noble metal perovskite-based catalyst (La0.75Sr0.25Cr0.5Fe0.5O3-δ-Ce0.8Gd0.18Ca0.02O2-δ, LSCrF-CGDC) for ammonia synthesis directly from air and water was explored. Ammonia was successfully from wet air (3%H2O) synthesized in a single-chamber type reactor. The highest ammonia formation rate and Faradaic efficiency of about 1.94×10-11mol s-1cm-2and 2.01% were achieved at 375 oC and 1.2 V, respectively. The observed ammonia formation rate is higher than reported for an expensive noble metal-based catalyst (Ru/MgO). The obtained results indicated that the direct synthesis of ammonia from air and water is a promising technology for green and sustainable ammonia synthesis.
Physico-Mechanical Properties of Treated Chicken Feather–Reinforced Unsaturated Polyester Resin Based Composites
Authors: Ali Md. Farhad , Hossain Md. Sahadat , Moin Tanvir Siddike , Ahmed Samina , Chowdhury A.M. Sarwaruddin
Published: April 2021

The influence of chemical treatment on the mechanical properties of treated chicken feather fibre-reinforced unsaturated polyester resin (TCFF-UPR) composites was studied in this research. Redundant portions of chicken from poultry farms are comprehensively contaminating the environment. To minimize environmental pollution, these redundant portions need to use for the production of other materials. In this study, we used chicken feather for the preparation of useful composites combining with unsaturated polyester resin (UPR) to reduce environmental pollution. The composites were prepared successfully by conventional hand lay up technique using modified chicken feather as the reinforcing phase of composites. For preparing composites different percentages (2, 5, 7, 10, 12 and 15% by weight) of fibre were used. Attained tensile test results expressed significant enhancement in the tensile properties of composites, with the optimum combination of tensile strength presented by 5 wt% , tensile modulus presented by 10 wt% untreated chicken feather bio-fibre reinforcement and bending strength by 5 wt% chicken feather bio-fibre reinforcement.
A Real-Time Curb Detection Method for Vehicle by Using a 3D-LiDAR Sensor
Authors: Du Zhiqiang , Wu Jian , He Rui , Wang Guojun , Li Shuai , Zhang Jinghua , Chen Guosheng
Published: April 2021

Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning and environmental understanding. To precisely extract the road boundaries from the 3D-LiDAR data, a dedicated algorithm consisting of four steps is proposed in this paper. The steps are as follows: Firstly, the 3D-LiDAR data is pre-processed by employing the RANSAC method, the ground points are quickly separated from the original 3D-LiDAR point cloud to reduce the disturbance from the obstacles on the road, this greatly decreases the size of the point cloud to be processed. Secondly, based on the principle of 3D-LiDAR scanning, the ground points are divided into scan layers. And the road boundary points of each scan layer are detected by using three spatial features based on sliding window. Thirdly, based on the improved beam model, the road type (straight road or curved road) where the vehicle is located is predicted, and then the edge points are subdivided into different areas by the road type. Finally, we use the distance filtering and RANSAC filtering to filter out false road boundary points caused by obstacles and obtain accurate road boundaries. Compared to other methods, we can effectively reduce the wrong classification of road edge points caused by obstacles by using the improved beam model. And the false points caused by obstacles are effectively reduced by using distance filtering and RANSAC filtering. The performance of the proposed method is verified through experiments with a vehicle driving on campus roads and extensive tests with the KITTI data set the experimental results demonstrate the accuracy and robustness of the proposed method.
Control and Validation of an Autonomous Drag Racing Vehicle
Authors: Donikian Vatche , Bell Joseph , Khairallah Nadim , Washington Gregory
Published: April 2021

This paper studies the implementation and validation of control algorithms for an autonomous drag racing vehicle. The previously developed modeling equations are first implemented with control in a realistic simulation environment complete with synthetic sensor data and decision-making algorithms. The controller is then transformed into an embedded on-board processing unit for on-vehicle testing. Camera, lidar, and radar sensor data are investigated and algorithms are created to provide information from physical sensors rather than synthetic data. The control related to actuation of the steering, brake, throttle, and shifting systems are further discussed, along with human-vehicle interaction in terms of handoff and emergency takeovers. The control algorithms are then validated on the research vehicle. This is demonstrated by completing a fully autonomous quarter-mile drag race, complete with camera detection for the staging sequence and MPC trajectory following. Two additional safety scenarios are presented and controlled: starting the race off center and fishtailing.
Implementation Methodologies for Simulation as a Service (SaaS) to Develop ADAS Applications
Authors: Kagalwala Huzefa , Srivastava Siddhant , Venkatesan Manikanda Balaji , Srinivasan Srivatsan , Krovi Venkat N
Published: April 2021

Over the years, the complexity of autonomous vehicle development (and concurrently the verification and validation) has grown tremendously in terms of component-, subsystem- and system-level interactions between autonomy and the human users. Simulation-based testing holds significant promise in helping to identify both problematic interactions between component-, subsystem-, and system-levels as well as overcoming delays typically introduced by the default full-scale on-road testing. Software in Loop (SiL) simulation is utilized as an intermediate step towards software deployment for autonomous vehicles (AV) to make them reliable. SiL efforts can help reduce the resources required for successful deployment by helping to validate the software for millions of road miles. A key enabler for accelerating SiL processes is the ability to use Simulation as a Service (SaaS) rather than just isolated instances of software. The primary benefits ensue from the in-parallel processing of multiple scenarios or tests using cloud or multiple cores especially to more systematically create “what-if analyses” thereby reducing both development time and cost. Here, we present the workflow of our utilization of SaaS methods (provisioned by Metamoto) and our explorations in this domain using exemplar ADAS scenarios. Additionally, we highlight our ability to perform parametric sweeps over variables such as environmental conditions, actors in the scene, etc. hence performing tests over a variety of scenarios including edge cases. The goal of our efforts is to examine viability and ease-of-use of SaaS (Metamoto in a co-simulation mode) to support Software-in-the-Loop co-development and functional reliability within MATLAB, ROS and Python frameworks.
Modeling Radio Frequency Interference (RFI) Between Co-Located RF Systems
Authors: Burnham Karen
Published: April 2021

Today's vehicles are outfitted with more radio frequency (RF) systems operating in more frequency ranges than could have been imagined a generation ago. With the move to autonomous vehicles and increased driver assistance capability, the number of RF systems on any single vehicle is set to increase even more in the coming years. Further, passengers carry many devices into the vehicle and those devices often contain multiple RF systems in them. This paper will introduce a procedure and combined analysis/measurement method for proactively predicting the RF environment on a given vehicle for early identification of potential in-band or out-of-band interference. It will take into account main passbands, but also harmonics, spurious emissions, mixer products and other considerations. It will detail an iterative approach to modeling that starts with information available early in product development and becomes more refined as the development lifecycle progresses towards launch. This same approach can incorporate the impact of RF systems on neighboring vehicles as well as in the surrounding infrastructure environment (e.g., 5G, V2X, etc.).
Experimental Investigation of the Pressure Drop during Water Condensation inside Charge Air Coolers
Authors: Basler Irina , Reister Heinrich , Rossmann Rainer , Weigand Bernhard
Published: April 2021

This paper investigates the pressure drop with and without condensation inside a charge air cooler. The background to this investigation is the fact that the stored condensate in charge air coolers can be torn into the combustion chamber during different driving states. This may result in misfiring or in the worst-case lead to an engine failure. In order to prevent or reduce the accumulated condensate inside charge air coolers, a better understanding of the detailed physics of this process is required. To this end, one single channel of the charge air side is investigated in detail by using an experimental setup that was built to reproduce the operating conditions leading to condensation. First, measurements of the pressure drop without condensation are conducted and a good agreement with experimental data of a comparable heat exchanger reported in Kays and London [1] is shown. In case of condensation it is observed that the accumulated condensate leads to an increase in pressure drop. An equilibrium state is established between the condensate formed and the one discharged from the charge air cooler, which leads to pressure fluctuations. Furthermore, the amount of the accumulated condensate in the charge air cooler is considered when determining the Fanning friction factor. It is shown that with this consideration the two-phase pressure drop can be described by the single-phase Blasius approach in the investigated operating range of the charge air cooler. The mean deviation of the measured data from the correlation amounts to about 3.8%.
Connected Vehicle Data Time Series Dependence for Machine Learning Model Selection and Specification
Authors: Meroux Dominique , Telenko Cassandra , Jiang Zhen
Published: April 2021

Connected vehicle data unlock compelling solutions for vehicle owners and fleet managers. In selecting machine learning algorithms for use in predicting a connected vehicle signal value, time series dependency is critical to understand. With little to no time series dependency, conventional machine learning models may be used with a feature set that has few or no lag variables. If there is a lot of time series dependency including long-term dependencies, deep learning architectures like variants of recurrent neural networks (RNN) may be a better approach. Further, at any time step, RNN features may be specified to use some number of past time steps to predict the latest value. This paper seeks to identify time series dependency of connected vehicle signals, and selection of the number of time steps to look back in the features set to minimize error.
Unstructured with a Point: Validation and Robustness Evaluation of Point-Cloud Based Path Planning
Authors: Kysar Sam , Bos Jeremy , Kurup Akhil , Jeffries Zach , Carter Jake , Majhor Casey , Jayakumar Paramsothy , Smith William
Published: April 2021

Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.
An Innovative Service Load-Agnostic Structural Light-Weighting Design Optimization Methodology
Authors: Kulkarni Kumar B. , Hodges Scott E. , Thyagarajan Ravi
Published: April 2021

A myriad of topology optimization tools exist today in the market that use automated under-the-hood structural simulations. All the user needs is to provide is the current shape of the part, or the maximum space that the part is allowed to occupy, and the maximum loads that it will experience. Though this technology has existed for over 25 years, recent advances in Additive Manufacturing (AM) have now enabled fabrication of hitherto-infeasible parts, both quickly and inexpensively.

A quick cursory literature search on successful implementation of topology optimization reveals that a majority of the attention has been focused on structural components and assemblies subjected to known service load(s) [1,2,3]. Therein lies one of the disadvantages experienced in the state-of-the-art today, especially for the military industry. The magnitudes of these loads are unknown a priori during design development, but rather only after vehicles are physically available, which is in much later design stages, and often too late to reap the benefits of optimization. In addition, enormous resources are required to measure loads in key components in physical tests, simply for performing topology optimization. In this study, a modeling and simulation (M&S) approach to optimization of structures in the absence of knowledge of service loads is described to determine the best weight save while simultaneously maintaining a similar or better “performance”.

Since the targets are with respect to zero or minimal performance gradation with respect to the baseline design, the premise of this research is that the optimization exercise can be carried out with relative loads, and knowledge of the absolute values are not necessary. This hypothesis has been successfully borne out in this paper, and the two design spaces explored meet all the set performance criteria compared to the baseline, and are able to achieve a weight save of up to 20%.
Developing Prediction Based Algorithms for Energy and Exergy Flow
Authors: Jane Robert , Kim CDT Tae , James LTC Corey
Published: April 2021

The future battlefield will include multiple dissimilar manned and unmanned aerial, ground, sea, and space vehicles working in concert with each other to support fires, logistics, maneuvers, communication, and coordination-based missions. Mission effectiveness and efficiency are often at odds, and due to the distributed and dissimilar energy flows inherent in Multi-Domain Operations (MDO) there is a need to understand, identify, and characterize the energy flows. The ability to analyze the energy flows and effectively maintain adequate energy reserves could provide strategic capabilities to the warfighters, permitting energy informed operations to maximize mission effectiveness and efficiency, while mitigating vulnerabilities. This research focuses on developing energy and exergy characterization through development of Artificial Intelligence (AI), Machine Learning (ML), and Artificial Neural Networks (ANNs) for assessing and analyzing performance of a platform. These types of tools were developed for a Mobile Ground Vehicle (MGV) for two primary reasons: (1) reconcile past state information not directly observable from the available sensor measurements, and (2) to characterize the aggregate energy flow behavior, such that Model Predictive Control (MPC) could be applied to customize the performance of the vehicle. Preliminary results indicate that provided a reference drive cycle and an estimation of the tractive force requirements, either a set of ANNs or Long Short-Term Memory (LSTM) recurrent neural networks can be used to reconcile past sensor measurements and extended to estimate energy flow characterizations of the drivetrain and other ancillary components within the vehicular platform that could affect efficiency and mission effectiveness.
Method for Estimation of Time at Temperature Histogram of Vehicle Interior Parts Exposed to Meteorological Environments around the World (Third Report)
Authors: Fukuda Takeru , Abe Jun
Published: April 2021

In order to help guarantee the durability and reliability of vehicle interior parts, it is necessary to use time at temperature histogram data for the parts when they are exposed to actual meteorological environments as criteria for judgment. In order to do so, it would be necessary to conduct actual vehicle exposure tests in the regions throughout the world in which the vehicles will be sold, which is unrealistic. The research discussed in this paper proposes a method of estimating the time at temperature histogram for vehicle interior parts when exposure tests are conducted at locations throughout the world using vehicle-specific constants obtained from actual vehicle exposure tests conducted in a single location and publicly available annual meteorological data.

Using the same vehicle, exposure tests were conducted sequentially in three locations: Yomitan Village in Okinawa Prefecture (2016); a Honda parking lot in Haga, Tochigi Prefecture (2017); and a vacant lot belonging to a partner company in Takasu, Hokkaido Prefecture (2018). An analysis performed using hourly temperature measurement data and meteorological data found that air temperature is the basic temperature for the interior parts, and increases in their temperature above the air temperature were proportional to the total solar radiation or the amount of radiant heat from the instrument panel. It was also found that the degree of change in the temperatures of interior parts in relation to the amount of radiant heat, in other words the constants of proportionality, were constants specific to the vehicle used in the exposure test and not dependent on the location of the exposure test, or the season or weather in which it was conducted. It was possible to express the temperatures of the interior parts by means of these vehicle-specific constants and a linear model of the variables of air temperature and total solar radiation. Calculated values accorded well with measured values. Using this model, it has become possible to calculate time at temperature histogram data for vehicle interior parts when exposure tests are conducted at locations throughout the world.
Use of Digital Olfaction to Standardize Cabin Odor Testing in Automotive Interiors
Authors: Bultel Etienne , Franchy Mike , Klein John , Brun Lucie , Decorps Johanna , Facteau Elizabeth , Shereda Laura , Pasqualon Aurélie , Rousselle Tristan
Published: April 2021

Subjectivity in testing for automotive validation processes is typically a sticking point for many suppliers and OEMs. For vehicle interiors, in addition to the laboratory testing, human panels of “trained noses” are used to judge the different components and the completed vehicle.

In the automotive industry, there is no standardization as each OEM has their own testing specifications, rating scale and methods. In addition to the variation in OEM specification, there are also global specifications issued by SAE, VDA, and ISO. This lack of unified quantitative norms leads to increased costs and timing for suppliers, lab-to-lab variations in results and ultimately longer development times for the OEMs.

With the advances in sensors, biochemistry and machine learning, odor detection and classification can be achieved with the use of a digital olfaction device, or “electronic nose”. We will demonstrate the ability to identify different types of plastics, the ability to differentiate between compound variants of the same material and a proof of concept for detection of odors in the automotive domain based on the ISO 12219-7 and VDA270 standards. We will also propose a quantifiable rating of odor which mimics the human panel established norms, in a way which is reproducible and independent of variation between individual testers. Ultimately, standardization of odor testing with consistent, repeatable and cost-effective digital olfaction methods can bring traceability and credibility to Tier 1 suppliers that translate to end-product quality for OEMs.
Machine Learning Based Parameter Calibration for Multi-Scale Material Modeling of Laser Powder Bed Fusion (L-PBF) AlSi10Mg
Authors: Li Yang , Li Ziang , Lai Wei-Jen , Xu Hongyi , Xue Zhendan , Su Xuming , Gao Zhenyan
Published: April 2021

Rapid development of Laser Powder Bed Fusion (L-PBF) technology enables almost unconstrained design freedom for metallic parts and components in automotive industry. However, the mechanical properties of L-PBF alloys, AlSi10Mg for example, have shown significant differences when compared with their counterparts via conventional manufacturing process, due to the unique microstructure induced by extremely high heating and cooling rate. Therefore, microstructure informed material modeling approach is critical to fully unveil the process-structure-property correlation for such materials and enable the consideration of the effect of manufacturing during part design. Multi-scale material modeling approach, in which crystal plasticity finite element (CPFE) models were employed at the microscale, has been previously developed for L-PBF AlSi10Mg. However, calibration of parameters for CPFE based on macroscale mechanical testing was found to be challenging due to the complexity and the high computational cost of the models. In the present study, the authors developed a machine learning based approach to tackle this challenge. With the training set data collected from preliminary runs of the multi-scale material models, surrogate models with different machine learning algorithms were constructed. It was found that the surrogate models using Gradient Boosting Machine (GBM) algorithm can well capture the response of the complex finite element based multi-scale material models. In the meantime, the study also showed that performing feature engineering can greatly enhance the efficiency and robustness of machine learning models. Specifically, the surrogate models are trained to predict the explicit physical descriptors instead of the summed error between stress-strain curves from testing and prediction. The obtained surrogate models were then utilized to find the optimal values of the parameters in microscale CPFE. Validation runs of multi-scale models using the optimal parameters found through surrogate modeling showed minimized differences between prediction and macroscale mechanical testing and thus proved the effectiveness of the developed approach.
Automotive Hood Panel Design Utilizing Anisotropic Multi-Material Topology Optimization
Authors: Munroe Evan , Roper Stephen , Bohrer Rubens , Kashanian Kiarash , Pamwar Manish , Sangha Balbir , Kim Il Yong
Published: April 2021

Topology optimization (TO) represents an invaluable instrument for the structural design of components, with extensive use in numerous industries including automotive and aerospace. TO allows designers to generate lightweight, non-intuitive solutions that often improve overall system performance. Utilization of multiple materials within TO expands its range of applications, granting additional freedom and structural performance to designers. Often, use of multiple materials in TO results in material placement that may not have been previously identified as optimal, providing designers with the ability to produce novel high performance systems. As numerous modern engineering materials possess anisotropic properties, a logical extension of multi-material TO is to include provisions for anisotropic materials. Herein lies the focus of this work.

A TO algorithm capable of considering anisotropic material properties is used to investigate a case study on the design of an automotive hood panel. A baseline aluminum hood panel is used to generate stiffness targets for optimization, followed by the generation of a design space model to allow the algorithm to determine optimal material placement. Optimization is undertaken with two types of AS4 continuous carbon fiber reinforced epoxy, each in two orientations. Optimal hood panel solutions that maintain stiffness levels of the conventional baseline are achieved. The mass of the design space is minimized, and constrained through the baseline displacement values. The effect of hood panel thickness and offset distance between panel layers is also investigated.

The optimal topologies indicated an overall mass savings of up to 44.5% in relation to the baseline, while maintaining hood panel stiffness. Comparative mass savings decreased as hood panel thickness increased and offset distance decreased. The allocation of stiffer materials was observed near locations of applied loads and constraints, with highly anisotropic materials placed along hood panel extremities. The practicality of anisotropic multi-material TO in lightweight design was thus demonstrated.
Validation of a LES Spark-Ignition Model (GLIM) for Highly-Diluted Mixtures in a Closed Volume Combustion Vessel
Authors: Iacovano Clara , Zeng Yangbing , Anbarasu Muniappan , Fontanesi Stefano , D'Adamo Alessandro
Published: April 2021

The establishment of highly-diluted combustion strategies is one of the major challenges that the next generation of sustainable internal combustion engines must face. The desirable use of high EGR rates and of lean mixtures clashes with the tolerable combustion stability. To this aim, the development of numerical models able to reproduce the degree of combustion variability is crucial to allow the virtual exploration and optimization of a wide number of innovative combustion strategies.

In this study ignition experiments using a conventional coil system are carried out in a closed volume combustion vessel with side-oriented flow generated by a speed-controlled fan. Acquisitions for four combinations of premixed propane/air mixture quality (Φ=0.9,1.2), dilution rate (20%-30%) and lateral flow velocity (1-5 m/s) are used to assess the modelling capabilities of a newly developed spark-ignition model for large-eddy simulation (GLIM, GruMo-UniMORE LES Ignition Model). The model accounts for all the main physical phenomena governing flame kernel growth, including electric circuit and over-adiabatic thermal expansion, which are included in the LES formalism of ECFM-LES combustion model. In the first part of the study the agreement of the simulation results against measurements is carried out to assess a validated non-reacting condition and converged flow statistics. Then, combustion simulations are carried out, and ignition events are repeated at random timings to replicate flow variability at ignition. Finally, optical comparison is carried out for simulated enflamed volume against high-frequency Schlieren images for all the cases, and measurements of flame radius growth are presented. The agreement of the quantitative flame measurements, as well as the qualitative resemblance of flame development, indicate the use of the presented GLIM ignition model as a valuable model for multi-cycle engine simulations, with particular relevance on unstable and CCV-affected conditions