Search results for: W. A. Staples

Authors: O. S. Saulters, S. D. Goldberg, W. A. Staples, E. I. Martinez, L. M. Sanchez, D. E. Archuleta, D. L. Williams, S. D. Johnson, A. M. Baker

Abstract:

To address an important set of unverified field conditions, the Los Alamos National Laboratory Waste Compliance and Tracking System (WCATS) Wall-to-Wall Team performed an unprecedented and advanced inventory. This reconciliation involved confirmation analysis for approximately 5850 hazardous, low-level, mixed low-level, and transuranic waste containers located in more than 200 staging and storage areas across 33 Technical Areas. The interdisciplinary team scoped, planned, and developed the multidimensional assessments. Through coordination with cross-functional site hosts, they were able to verify and validate data while resolving discrepancies identified in WCATS. The results were extraordinary with an updated inventory, tailored outreach, more cohesive communications, and timely closed-loop feedbacks.

Keywords: Circular economy, environmental performance data, social-ecological-technological systems, waste management.

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Authors: Lucy Patricia Onundo, Wilfred Njoroge Mwema

Abstract:

The rapidly diminishing fossil fuel reserves, their exorbitant cost and the increasingly apparent negative effect of fossil fuels to climate changes is a wake-up call to explore renewable energy. Wind, bio-fuel and solar power have already become staples of Kenyan electricity mix. The potential of electric power generation from marine tidal currents is enormous, with oceans covering more than 70% of the earth. However, attempts to harness marine tidal energy in Kenya, has yet to be studied thoroughly due to its promising, cyclic, reliable and predictable nature and the vast energy contained within it. The high load factors resulting from the fluid properties and the predictable resource characteristics make marine currents particularly attractive for power generation and advantageous when compared to others. Global-level resource assessments and oceanographic literature and data have been compiled in an analysis of the technology-specific requirements for tidal energy technologies and the physical resources. Temporal variations in resource intensity as well as the differences between small-scale applications are considered.

Keywords: Energy data assessment, environmental legislation, renewable energy, tidal-in-stream turbines.

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Authors: Md Monir Hossain, Anne Staples, Kuya Takami, Tomonari Furukawa

Abstract:

Tire noise has a significant impact on ride quality and vehicle interior comfort, even at low frequency. Reduction of tire noise is especially important due to strict state and federal environmental regulations. The primary sources of tire noise are the low frequency structure-borne noise and the noise that originates from the release of trapped air between the tire tread and road surface during each revolution of the tire. The frequency response of the tire changes at low and high frequency. At low frequency, the tension and bending moment become dominant, while the internal structure and local deformation become dominant at higher frequencies. Here, we analyze tire response in terms of deformation and rolling velocity at low revolution frequency. An Abaqus FEA finite element model is used to calculate the static and dynamic response of a rolling tire under different rolling conditions. The natural frequencies and mode shapes of a deformed tire are calculated with the FEA package where the subspace-based steady state dynamic analysis calculates dynamic response of tire subjected to harmonic excitation. The analysis was conducted on the dynamic response at the road (contact point of tire and road surface) and side nodes of a static and rolling tire when the tire was excited with 200 N vertical load for a frequency ranging from 20 to 200 Hz. The results show that frequency has little effect on tire deformation up to 80 Hz. But between 80 and 200 Hz, the radial and lateral components of displacement of the road and side nodes exhibited significant oscillation. For the static analysis, the fluctuation was sharp and frequent and decreased with frequency. In contrast, the fluctuation was periodic in nature for the dynamic response of the rolling tire. In addition to the dynamic analysis, a steady state rolling analysis was also performed on the tire traveling at ground velocity with a constant angular motion. The purpose of the computation was to demonstrate the effect of rotating motion on deformation and rolling velocity with respect to a fixed Newtonian reference point. The analysis showed a significant variation in deformation and rolling velocity due to centrifugal and Coriolis acceleration with respect to a fixed Newtonian point on ground.

Keywords: Natural frequency, rotational motion, steady state rolling, subspace-based steady state dynamic analysis.

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

Abstract:

Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT.

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