Engineering Commons^™

The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 36, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 37, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

The Winter Adverse Driving Dataset (Wads) - Sequence 76, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …

Open Source Software Toolchain For Automated Non‐Targeted Screening For Toxins In Alternative Foods, S. W. Breuer, L. Toppen, S. K. Schum, J. M. Pearce

Michigan Tech Publications, Part 1

Previous published methods for non-targeted screening of toxins in alternative foods such as leaf concentrate, agricultural residues or plastic fed to biological consortia are time consuming and expensive and thus present accessibility, as well as, time-constraint issues for scientists from under resourced settings to identify safe alternative foods. The novel methodology presented here, utilizes a completely free and open source software toolchain for automatically screening unknown alternative foods for toxicity using experimental data from ultra-high-pressure liquid chromatography and mass spectrometry. The process uses three distinct tools (mass spectrometry analysis with MZmine 2, formula assignment with MFAssignR, and data filtering with …

Me-Em 2020-21 Annual Report, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University

Department of Mechanical and Aerospace Engineering Annual Reports

Table of Contents

• Responsive Research
• Alumni Impact
• Innovative Enterprises
• Enrollment & Degrees
• Graduates
• Department
• Donors
• Contracts & Grants
• Patents & Publications

Me-Em Enewsbrief, September 2021, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Mechanical Properties And Characterization Of Epoxy Composites Containing Highly Entangled As-Received And Acid Treated Carbon Nanotubes, Aaron Krieg, Julia A. King, Gregory M. Odegard, Timothy Leftwich, Leif K. Odegard, Paul D. Fraley, Ibrahim Miskioglu, Claire Jolowsky, Matthew Lundblad, Jin Gyu Park, Richard Liang

Michigan Tech Publications, Part 1

Huntsman–Merrimack MIRALON® carbon nanotubes (CNTs) are a novel, highly entan-gled, commercially available, and scalable format of nanotubes. As-received and acid-treated CNTs were added to aerospace grade epoxy (CYCOM® 977-3), and the composites were characterized. The epoxy resin is expected to infiltrate the network of the CNTs and could improve mechanical properties. Epoxy composites were tested for flexural and viscoelastic properties and the as-re-ceived and acid treated CNTs were characterized using Field-Emission Scanning and Transmission Electron Microscopy, X-Ray Photoelectron Spectroscopy, and Thermogravimetric Analysis. Composites containing 0.4 wt% as-received CNTs showed an increase in flexural strength, from 136.9 MPa for neat epoxy …

A High Solids Field-To-Fuel Research Pipeline To Identify Interactions Between Feedstocks And Biofuel Production, Meenaa Chandrasekar, Leela Joshi, Karleigh M. Krieg, Sarvada Chipkar, Emily Burke, Derek J. Debrauske, Kurt D. Thelen, Trey K. Sato, Rebecca Ong

Michigan Tech Publications, Part 1

Background: Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of …

Editorial: Development And Application Of Bituminous Materials For Civil Infrastructures, Zhanping You, Jie Ji, Dawei Wang, Feng Li, Hui Yao, Yue Hou

Michigan Tech Publications, Part 1

No abstract provided.

Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue

Michigan Tech Publications, Part 1

Meteotsunamis pose a unique threat to coastal communities and often lead to damage of coastal infrastructure, deluge of nearby property, and loss of life and injury. The Great Lakes are a known hot-spot of meteotsunami activity and serve as an important region for investigation of essential hydrodynamic processes and model forecast requirements in meteotsunami-induced coastal flooding. For this work, we developed an advanced hydrodynamic model and evaluate key model attributes and dynamic processes, including: (1) coastal model grid resolution and wetting and drying process in low-lying zones, (2) coastal infrastructure, including breakwaters and associated submerging and overtopping processes, (3) annual/seasonal …

Sliding Mode Control Of A Nonlinear Wave Energy Converter Model, Tania Demonte Gonzalez, Gordon Parker, Enrico Anderlini, Wayne Weaver

Michigan Tech Publications, Part 1

The most accurate wave energy converter models for heaving point absorbers include nonlinearities, which increase as resonance is achieved to maximize the energy capture. Over the power production spectrum and within the physical limits of the devices, the efficiency of wave energy converters can be enhanced by employing a control scheme that accounts for these nonlinearities. This paper proposes a sliding mode control for a heaving point absorber that includes the nonlinear effects of the dynamic and static Froude‐Krylov forces. The sliding mode controller tracks a reference velocity that matches the phase of the excitation force to ensure higher energy …

Progressive Poling Of Large Area, High R33 Electro-Optic Polymer Seo100c, Michael Maurer, Evan Gawron, Christopher Middlebrook

Michigan Tech Publications, Part 1

SEO100c, an EO-polymer, has been reported of having an r33 in excess of 100 pm/V. Experimental poling research was performed on rib waveguide modulator for device design and development. Reported is the determination of the impact that temperature and voltage have on the poling of a SEO100c waveguide device in order to maximize the r33 while avoiding damage to the device structure ensuring high yield in manufacture. The poling process is shown to have a nonlinear relationship between r33 and poling field aiding in the selection of achievable poling voltages for required r33 values. Device thermal stability is quantified and …

Validation Of The Mathematics Motivation Questionnaire (Mmq) For Secondary School Students, Logan Fiorella, So Yoon Yoon, Kinnari Atit, Jason R. Power, Grace Panther, Sheryl Sorby, David H. Uttal, Norma Veurink

Michigan Tech Publications, Part 1

Background: Motivation is critical for supporting persistence and achievement in science, technology, engineering, and mathematics (STEM) disciplines. In this study, we focus on the assessment of mathematics motivation among secondary school students. We provide validity and reliability evidence for the Mathematics Motivation Questionnaire (MMQ)—adapted from the Science Motivation Questionnaire designed for college students—using data from 2551 secondary students from seven states across the United States. Results: Exploratory and confirmatory factor analyses confirmed five latent factors of the MMQ indicated by 19 items: intrinsic value, self-regulation, self-efficacy, utility value, and test anxiety. The nonlinear SEM reliability coefficients of the five constructs …

A Review Of Characteristics Of Bio-Oils And Their Utilization As Additives Of Asphalts, Ran Zhang, Zhanping You, Jie Ji, Qingwen Shi, Zhi Suo

Michigan Tech Publications, Part 1

Transforming waste biomass materials into bio-oils in order to partially substitute petroleum asphalt can reduce environmental pollution and fossil energy consumption and has economic benefits. The characteristics of bio-oils and their utilization as additives of asphalts are the focus of this review. First, physicochemical properties of various bio-oils are characterized. Then, conventional, rheological, and chemical properties of bio-oil modified asphalt binders are synthetically reviewed, as well as road performance of bio-oil modified asphalt mixtures. Finally, performance optimization is discussed for bio-asphalt binders and mixtures. This review indicates that bio-oils are highly complex materials that contain various compounds. Moreover, bio-oils are …

Application Of Epoxy-Asphalt Composite In Asphalt Paving Industry: A Review With Emphasis On Physicochemical Properties And Pavement Performances, Yu Chen, Nabil Hossiney, Xu Yang, Hainian Wang, Zhanping You

Michigan Tech Publications, Part 1

One of the failure mechanisms associated with asphalt paving layers, especially on steel deck bridges, is large permanent deformation, which adversely affects its long-term performance in service. Thus, epoxy resin was introduced in asphalt paving industry to tackle permanent deformation of asphalt mixtures due to its thermosetting nature. In this review, epoxy resin as a dominant component of the epoxy-asphalt composite system was first considered, followed by a discussion on its curing methods and curing mechanism. Furthermore, the physicochemical property and mechanical performance of epoxy asphalt and epoxy asphalt mixture were thoroughly examined. Crosslink density of epoxy asphalt dictates its …

A Xanes Study Of Lithium Polysulfide Solids: A First-Principles Study, Qing Guo, Kah Chun Lau, Ravindra Pandey

Michigan Tech Publications, Part 1

X-ray absorption spectroscopy (XAS) is used for capturing the reaction mechanisms at the molecular level via the determination of local electronic configurations inside Li-S batteries. In this paper, a comprehensive investigation of the S K-edge X-ray absorption near-edge structure (XANES) of a series of stoichiometric lithium polysulfide solids was performed, assuming that these polysulfide solids are formed during the battery cycling process. The results based on density functional theory show that the pre-edge peak in the S K-edge XANES spectra is not a common feature in the solid phase in contrast to the case of pristine polysulfide molecules where the …

Earth Imaging From The Surface Of The Moon With A Dscovr/Epic-Type Camera, Nick Gorkavyi, Simon Carn, Matt Deland, Yuri Knyazikhin, Nick Krotkov, Alexander Marshak, Et Al.

Michigan Tech Publications

The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) satellite observes the entire Sun-illuminated Earth from sunrise to sunset from the L1 Sun-Earth Lagrange point. The L1 location, however, confines the observed phase angles to ∼2°–12°, a nearly backscattering direction, precluding any information on the bidirectional surface reflectance factor (BRF) or cloud/aerosol phase function. Deploying an analog of EPIC on the Moon’s surface would offer a unique opportunity to image the full range of Earth phases, including observing ocean/cloud glint reflection for different phase angles; monitoring of transient volcanic clouds; detection of circum-polar mesospheric and stratospheric …

Elementary Reaction-Based Kinetic Model For The Fate Of: N -Nitrosodimethylamine Under Uv Oxidation, Benjamin Barrios, Divya Kamath, Erica Coscarelli, Daisuke Minakata

Michigan Tech Publications, Part 1

UV photolysis is an effective process to remove nitrosamines from contaminated water resources. Nitrosamines represent a class of compounds with high potential for carcinogenicity and, therefore, there are serious concerns regarding their threat to human health and their environmental toxicity. Although the photochemical parameters of parent nitrosamines and their initial reaction pathways are well understood, the fate of nitrogen-containing species and reactive nitrogen species generated from nitrosamine degradation has not yet been elucidated. In this study, we develop an elementary reaction-based kinetic model for the photolysis of N-nitrosodimethylamine (NDMA) and the photochemical transformation products. We use density functional theory quantum …

Extension Of A Gaseous Dry Deposition Algorithm To Oxidized Volatile Organic Compounds And Hydrogen Cyanide For Application In Chemistry Transport Models, Zhiyong Wu, Leiming Zhang, John T. Walker, Paul A. Makar, Judith Perlinger, Xuemei Wang

Michigan Tech Publications, Part 1

The dry deposition process refers to flux loss of an atmospheric pollutant due to uptake of the pollutant by the Earth's surfaces, including vegetation, underlying soil, and any other surface types. In chemistry transport models (CTMs), the dry deposition flux of a chemical species is typically calculated as the product of its surface layer concentration and its dry deposition velocity (Vd); the latter is a variable that needs to be highly empirically parameterized due to too many meteorological, biological, and chemical factors affecting this process. The gaseous dry deposition scheme of Zhang et al. (2003) parameterizes Vd for 31 inorganic …