46033 research outputs found
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Dixiana
No full textBand members of Dixianahttps://commons.und.edu/performing-arts-photos/1138/thumbnail.jp
Cirque Le Masque
No full textCast of Cirque Le Masquehttps://commons.und.edu/performing-arts-photos/1137/thumbnail.jp
Spaceflight Safety Regulations: The Case For Implementing Safety Management Systems In The Developing U.S. Commercial Human Spaceflight Industry
No full textAccidents have historically accompanied the development of new transportation systems, often due to technical failures; but human factors – such as organizational culture and management decisions – are increasingly recognized as significant contributors. A strong safety culture, prioritizing safety at all organizational levels, effective management procedures, and open reporting of violations, is believed to improve outcomes by proactively reducing risk in highly technical organizations. These elements form the basis of Safety Management Systems (SMS), which include safety policy, risk management, assurance, and promotion. As commercial spaceflight expands public access to space, US regulators must develop flexible safety regulations that protect the public while supporting industry growth. This research draws on lessons from commercial aviation, NASA’s human spaceflight experience, and recent aerospace accidents, applying SMS principles to identify common causes and support best practices. Findings emphasize the importance of non-prescriptive, non-punitive SMS frameworks for industry acceptance and long-term viability of commercial human spaceflight
Technology Demonstration
No full textFact sheet about the Energy & Environmental Research Center’s technology demonstration abilities. Includes information on combustion systems, gasification and gas cleanup systems, and chemical and liquid processing.https://commons.und.edu/eerc-brochures/1167/thumbnail.jp
Beaded Moccasins
No full textBright green beaded women\u27s leather moccasins, with yellow orange and red beaded diamonds against the green background.
Featured in the exhibition, Plain of Stars: An exhibition to uplift, acknowledge, and celebrate Indigenous students.https://commons.und.edu/native-art/1098/thumbnail.jp
Untitled
No full textA black miniature chair decorated with flowers and silver geometric designs.
Featured in the exhibition, Plain of Stars: An exhibition to uplift, acknowledge, and celebrate Indigenous students.https://commons.und.edu/native-art/1097/thumbnail.jp
And Girls
No full textUnidentified man and two unidentified girls sit beside each other on a bench near the beach. Title taken from photographer\u27s original album.https://commons.und.edu/infantry-photos/1160/thumbnail.jp
Enhancing Green Hydrogen Integration In Distributed Energy Systems
Get PDFThis study investigates strategic integration of green hydrogen into Distributed Energy Systems (DES) as a means of addressing three closely related challenges: first, uncertainties in hydrogen supply due to renewables intermittency; second, non-existence of practical, scalable modeling solutions for early-phase DES planning involving Alkaline Water Electrolyzers; and third, a lack of sufficient policy frameworks facilitating mass deployment. Existing hydrogen production models are often too complex for effective use in DES and do not relate stack number, input power, and renewable resource fluctuation. To address this limitation, the paper introduces a new probabilistic electrolyzer sizing method based on cumulative distribution function (CDF) percentiles (P50–P90) and formulates a reduced-form hydrogen output model with electrolyzer stack number (N) and input power (P). The model accounts for varying performance between systems with N ≤ 6 and N \u3e 6, elucidating economies of scale and scaling behavior in the non-linear sense within \u3c5% error. Empirical confirmation confirms that hydrogen output increases linearly with system size, and P60–P70 system sizing cases offer optimal trade-offs among output, curtailment, and cost. Simulation-based operational modeling using HOMER Pro reveals that the operation of hybrid battery-hydrogen systems decreases curtailment by 60% and REU by 30%, whereas load-following electrolyzers reduce Levelized Cost of Hydrogen (LCOH) by 8–15%. Policy simulations show that layered incentives—20–30% CAPEX subsidies, 40–83/ton carbon pricing—can raise project Net Present Value (NPV) by 300–900%. Monte Carlo simulations also determine a 70% probability of achieving positive NPV under best-case policy conditions. Grid-connected hydrogen systems are less policy-sensitive, whereas synthetic gas, ammonia, hydrogen natural gas blending, and underground storage channels require sector-focused intervention, such as subsidies, tax credits, and R&D investment.This combined strategy—combining empirical modeling, operational improvement, and multi-layer policy design—gives a realistic, end-to-end blueprint for hydrogen deployment in DES. Some of the most important recommendations are: one, the use of open-access sizing tools and LCOH calculators to facilitate local investors and planners; two, the use of modular, hybrid battery-hydrogen system designs to maximize flexibility and minimize curtailment; and three, sequenced policy support through the blending of CAPEX subsidies, production credits, and carbon pricing to promote equitable, climate-aligned hydrogen uptake. These findings support SDG 7, SDG 9, SDG 11, and SDG 13 attainment and Paris Agreement objectives and render hydrogen technically viable and socioeconomically justifiable as a pillar of the global energy transition. Subsequent research ought to integrate high-frequency solar, wind, and demand data; investigate geothermal and bioenergy integration; and simulate investor reaction to regulation risk by means of Bayesian and game-theoretic analysis
Photometric Analysis Of Four Near-Earth Asteroids With A Convex Shape Model Of (25330) 1999 KV4
Get PDFAstrometric and photometric observations of asteroids provide information regarding their positions, rotation rates, axis of rotation, and shapes. Lightcurve inversion utilizes an asteroid’s change in brightness with respect to phase angle change, which maximizes ground-based observational data. This study investigated the rotational properties of four near-Earth asteroids (NEAs) with a single pole solution and convex shape model of (25330) 1999 KV4 using the lightcurve inversion method. Photometric observations were remotely obtained using the Skynet Robotic Telescope Network, andNOIRLAB’s Cerro-Tololo Inter-American Observatory’s (CTIO) 24” Ritchey-Chretien Prompt 3 Telescope. The data were calibrated using AstroImageJ software, and lightcurve analyses were performed using MPO Canopus to find the rotational periods and amplitudes of each target. The results show NEA (219071) 1997 US9’s rotational period as 3.331 ± 0.001 hours with an amplitude of 0.19 ± 0.07 magnitude, agreeing with previously published results. The rotational period for NEAs (152787) 1999 TB10 and (187026) 2005 EK70 were calculated at 2.876 ± 0.001 hours and amplitude of 0.29 ± 0.05 magnitudes, and 6.966 ± 0.001 hours and amplitude of 0.20 ± 0.02 magnitudes, respectively. Lightcurve Inversion was performed using MPO LCInvert on NEA (25330) 1999 KV4 using compiled data from CTIO, Ondrejov Observatory, Modra Observatory, and Sopot Astronomical Observatory. The results indicate the pole solution at ? = 145 ± 19°, ? = −80 ± 16° with the period of 4.912 ± 0.001 hours and ?2 = 0.352230. The period and pole solution were applied to the Minkowski/triangles conversion, where the area of each polygonal facet is converted into triangles onto a 3D convex shape representing the asteroid. The shape model exhibits an equatorial ridge about the axis of rotation and produces a simulated photometric lightcurve, which agrees with the shape created using observational data
The Relationship Between Weather Variablity And Agricultural Land Cover Change In North Dakota (1997-2023) And Its Implication For Future Change
Get PDFClimate variability and weather patterns play a critical role in shaping agricultural land use and land cover (LULC), particularly in states like North Dakota, where agriculture dominates the landscape. This study explores the impacts of climatic factors—specifically rainfall, temperature, and Growing Degree Days (GDD)—on agricultural land cover (ALC) changes in North Dakota from 1997 to 2023, with projections for 2033. By combining historical analysis and predictive modeling, the research examines how climate variability has influenced crop dynamics and provides insights into future scenarios. The research uses advanced geospatial tools, including Google Earth Engine, and machine learning techniques such as Random Forest (RF), Autoregressive Integrated Moving Average and Long Short-Term Memory networks. Data mainly from the U.S. Department of Agriculture Cropland Data Layer and the North Dakota Agricultural Weather Network form the foundation for this analysis, linking climate variables such as rainfall, air temperature, GDD and bare soil temperature to ALC patterns. The findings reveal a significant shift toward monoculture practices, particularly the increasing dominance of spring wheat and corn, at the expense of sunflower, soybeans and other. While this shift enhances short-term agricultural productivity, it poses challenges to crop diversity, soil fertility, and long-term ecological resilience. Spatial analyses highlight strong clustering in the distributions of spring wheat and corn, whereas sunflower demonstrates fluctuating spatial dynamics and a declining trend. Projections for 2033 also indicate intensified hotspots of crop cultivation in southeastern and northeastern regions, driven by rising GDD and temperature. These trends underscore the potential risks to food security and the vulnerability of monoculture systems to climatic stressors. Using RF for ALC predictions, the study achieved an overall accuracy of 97 percent and a Kappa coefficient of 0.95 for crop prediction model, demonstrating the robustness of machine learning techniques in agricultural modeling. These findings underscore the need for adaptive management strategies to mitigate risks associated with climate variability and offer valuable contributions to sustainable agricultural planning and resilience