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Articles 1 - 8 of 8
Full-Text Articles in Engineering
Geochemistry, Petrology, And Palynology Of The Princess No. 3 Coal, Greenup County, Kentucky, Madison M. Hood, Cortland F. Eble, James C. Hower, Shifeng Dai
Geochemistry, Petrology, And Palynology Of The Princess No. 3 Coal, Greenup County, Kentucky, Madison M. Hood, Cortland F. Eble, James C. Hower, Shifeng Dai
Center for Applied Energy Research Faculty and Staff Publications
The high volatile C bituminous-rank, Bolsovian-age Princess No. 3 coal, a correlative of the heavily-mined Hazard No. 7 coal and the Peach Orchard and Coalburg Lower Split coals, was investigated three sites at a mine in Greenup County, Kentucky. The coal exhibits a “dulling upwards” trend, with decreasing vitrinite and a greater tendency towards dull clarain and bone lithotypes towards the top of the coal. The relatively vitrinite-rich basal lithotype is marked by a dominance of lycopod tree spores. The palynology transitions upwards to a middle parting co-dominated by tree fern and small lycopod spores and an upper bench dominated …
The Use Of Green Pond Conglomerate As Building Stone In Morris County, New Jersey, Gregory A. Pope
The Use Of Green Pond Conglomerate As Building Stone In Morris County, New Jersey, Gregory A. Pope
Department of Earth and Environmental Studies Faculty Scholarship and Creative Works
Green Pond Conglomerate (GPC) is a maroon colored quartzite with white quartz pebbles, a classic “puddingstone”. GPC derives from a NW-SW-trending sliver of Paleozoic sediments, the “Green Pond Outlier”, surrounded by older metamorphic and igneous rocks of Morris and Passaic Counties. Buildings, retaining walls, field fences, and monuments incorporate the durable and attractive stone, in a distinct geographic area of Morris County. Several instances of structures completely constructed or faced with GPC occur in and around Morristown, limited to affluent houses and one prominent church. In these cases, GPC stones were dressed and faced, a labor-intensive effort. Elsewhere in the …
Rare Earth-Bearing Particles In Fly Ash Carbons: Examples From The Combustion Of Eastern Kentucky Coals, James C. Hower, John G. Groppo Jr.
Rare Earth-Bearing Particles In Fly Ash Carbons: Examples From The Combustion Of Eastern Kentucky Coals, James C. Hower, John G. Groppo Jr.
Center for Applied Energy Research Faculty and Staff Publications
Graphitic carbons from the combustion of bituminous coals and, perhaps, other coal ranks, tend to capture iron and a number of hazardous elements, including As, Hg, and Se. Rare earth elements in fly ashes occur in minerals, such as monazite, xenotime, and davidite. They also occur in sub-nm particles, probably in a mineral form, within the Al–Si glass on the investigated fly ashes. Just as graphitic carbons can capture Fe and hazardous elements, the carbons surrounding the fly ash glass and magnetic particles captures or encapsulates a broad suite of rare earth elements.
Traffic Impacts Of The Covid-19 Pandemic: Statewide Analysis Of Social Separation And Activity Restriction, Scott Parr, Brian Wolshon, John Renne, Pamela Murray-Tuite, Karl Kim
Traffic Impacts Of The Covid-19 Pandemic: Statewide Analysis Of Social Separation And Activity Restriction, Scott Parr, Brian Wolshon, John Renne, Pamela Murray-Tuite, Karl Kim
Faculty Publications
The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped …
Impact Of Compactive Effort On Soil Strength Of Glacial Lake Columbia Soils, Alexander M. Navarra, Dwight Hendrickson, Jaremy Shaw
Impact Of Compactive Effort On Soil Strength Of Glacial Lake Columbia Soils, Alexander M. Navarra, Dwight Hendrickson, Jaremy Shaw
2020 Symposium Posters
Glacial Lake Columbia (GLC) existed from 15,550 (+/- 450) to 13,050 (+/- 650) years ago (Atwater, 1986) as a result of the Okanagan Lobe of the Cordilleran Ice Sheet damming the Columbia River near present-day Grand Coulee Dam. The lake deposited a fine-grained basal layer that had interbeds of coarse Missoula Flood deposits and later lake deposits above. Because these GLC deposits are present around most of the Spokane area, they are important to civil engineering and development. We sampled the basal layer of GLC soils from the Peone Prairie, WA. We performed prerequisite testing before the main experiment, with …
Petrology, Physicochemical And Thermal Analyses Of Selected Cretaceous Coals From The Benue Trough Basin In Nigeria, S. A. Akinyemi, O. F. Adebayo, B. B. Nyakuma, A. K. Adegoke, O. A. Aturamu, O. A. Olaolorun, A. Adetunji, James C. Hower, Madison M. Hood, A. Jauro
Petrology, Physicochemical And Thermal Analyses Of Selected Cretaceous Coals From The Benue Trough Basin In Nigeria, S. A. Akinyemi, O. F. Adebayo, B. B. Nyakuma, A. K. Adegoke, O. A. Aturamu, O. A. Olaolorun, A. Adetunji, James C. Hower, Madison M. Hood, A. Jauro
Center for Applied Energy Research Faculty and Staff Publications
Abundant coal resources that were previously neglected due to a crude oil boom need revitalisation and integration into the national electricity mix to address the energy demands of the Nigerian population. Selected coal samples from the Benue Trough sedimentary basin in Nigeria were examined by various techniques, including proximate and ultimate analyses, organic petrography, Fourier transform infrared ray spectroscopy, and thermogravimetric analysis. Based on vitrinite reflectance, the Lafia-Obi (OLB), Garin Maiganga (GMG), Imiegba (IMG), and Okaba (OKB) coals are classified as subbituminous, while the Lamja1 (LMJ1), Lamja2 (LMJ2) and Chikila (CHK) coals are high volatile B bituminous. The Enugu (ENG) …
Geotechnical Engineering: Particle Size Distribution Of Layered Glacial Lake Columbia And Ice Age Flood Deposits In Latah Valley, Spokane, Wa, Aaron Cleveland, Kassie Allen
Geotechnical Engineering: Particle Size Distribution Of Layered Glacial Lake Columbia And Ice Age Flood Deposits In Latah Valley, Spokane, Wa, Aaron Cleveland, Kassie Allen
2020 Symposium Posters
We collected samples from the Latah Valley in Spokane, WA, of Missoula Flood deposits interbedded with Glacial Lake Columbia Sediments. We conducted tests on these soils according to ASTM standards. We performed Specific Gravity tests according to ASTM D854, and determined particle size distribution for these soils by conducting sieve and hydrometer analyses according to ASTM D422. We then plotted these data to create particle size distribution curves. Specific Gravities for the all of the samples collected range from 2.36 to 2.67. The flood deposits are dominated by coarse sand and gravel and the Glacial Lake Columbia deposits are dominated …
Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel
Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel
Electrical and Computer Engineering Faculty Publications
Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …