469 research outputs found

    UMSL Bulletin 2022-2023

    Get PDF
    The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp

    Optimising the energy performance of the residential stock of the Kingdom of Saudi Arabia by retrofit measures

    Get PDF
    Building energy demands and green house gases are raising and a variety of energy efficiency frameworks, legislation, and housing approvals have evolved worldwide. The KSA is one of the largest energy producers and consumers internationally, with the residential sector using 52% of total energy generation. The KSA government has begun energy efficiency initiatives and policies that intend to reduce the residential energy demands via a series of regulations including Vision 2030 and the KSA building code. The regulations aim to assess the energy performance of residential buildings in order to lower the energy demands and greenhouse gas emissions to meet international carbon emissions requirements. The KSA targets to generate 9.5 GW from renewable energy by 2023, and 58.7 GW by 2030, which accounts for about 30% of the total energy generation capacity. Research has shown that in order to effectively reduce the energy demands and achieve worldwide carbon emissions targets, large-scale implementation interventions are required. The KSA housing stock consists of 3.6 million wide and varied residences due to various terrain. The diversity of the KSA dwellings encompasses housing type, age, amounts of rooms and bedrooms and flooring areas while common characteristics comprise construction materials and energy and cooking fuels. Therefore, this thesis develops housing archetypes that are representative of the KSA housing stock to be assessed and evaluated for the aim of reducing there energy demands and associated carbon emissions along with monthly running costs. The housing archetypes are used to quantify the housing energy performance and define the major sources of heat loss or gain. Two major reason for the high energy demands are solar radiation and heat gain due to infiltration. The infiltration occurs due to pressure differential across the thermal envelope. This is responsible for 40 TWh of lost energy from the housing stock, which accounts for 9.9 million MtCO2e. The research methodology applied an engineering bottom-up approach to quantify the energy performance of the KSA’s housing stock using EnergyPlus dynamic tool. EnergyPlus is a new generation modelling tool that incorporates the best features of two prior modelling tools: Building Load Analysis and System Thermodynamics (BLAST) and the Department of Energy (DOE–2). EnergyPlus is a free available tool and so allows data comparisons with international housing stocks. EnergyPlus was used to create the KSA’s housing energy baselines to predict the existing housing energy performance and to simulate various scenarios to reduce the total energy demands. The KSA housing energy demands can be optimised through a large-scale implementation of energy efficiency retrofitting schemes comprising 25 exterior thermal insulation types, eight exterior shading systems, and LED lighting systems and equipment, and the application of PV systems. This resulted in reducing the total KSA housing energy demands by 12.95 TWh/month, equivalent to 40% of the monthly housing energy use, and lowered associated carbon emissions by a total of 5.61 million MtCO2e/month, equivalent to 40% of monthly housing carbon emissions, and decreased the total housing stock cost about 72.39 million USD/month, equivalent to 50% of the total monthly cost

    2023-2024 academic bulletin & course catalog

    Get PDF
    University of South Carolina Aiken publishes a catalog with information about the university, student life, undergraduate and graduate academic programs, and faculty and staff listings

    24th Nordic Conference on Computational Linguistics (NoDaLiDa)

    Get PDF

    2022-2023 Xavier University Undergraduate and Graduate University Catalog

    Get PDF
    https://www.exhibit.xavier.edu/coursecatalog/1275/thumbnail.jp

    2023-2024 Graduate Catalog

    Get PDF
    2023-2024 graduate catalog for Morehead State University

    University of Maine Undergraduate Catalog, 2022-2023

    Get PDF
    The University of Maine undergraduate catalog for the 2022-2023 academic year includes an introduction, the academic calendars, general information about the university, and sections on attending, facilities and centers, and colleges and academic programs including the Colleges of Business, Public Policy and Health, Education and Development, Engineering, Liberal Arts and Sciences, and Natural Sciences, Forestry and Agriculture

    2023-2024 Lynn University Academic Catalog

    Get PDF
    The 2023-2024 Academic Catalog initially published as a web-only document. The Department of Marketing and Communication created a PDF version, which is available for download here.https://spiral.lynn.edu/accatalogs/1052/thumbnail.jp

    The Plankton Imager. a novel tool for the automated and continuous sampling of zooplankton.

    Get PDF
    Marine zooplankton have global ubiquitous distribution and are fundamental in the ocean carbon cycle, as prey for planktivores and use as indicators for ecosystem health. Recent impetus has been on developing cost effective methods to better sample the plankton. As a result, imaging devices are becoming synonymous with plankton sampling. This study contributes to the development, and demonstrates the ecological application, of a novel plankton imaging instrument: the Plankton Imager (PI). The PI is a continuous, automated instrument that uses water pumped onboard a ship and images all particles present. The images can be resolved to a moderate (family-level) taxonomic resolution by experts. This method revealed strong temporal changes in the zooplankton community of the Celtic Sea where interannual variation was greater than seasonal. In order to better harness the continuous nature of the PI, temporal subsampling (classifying 1 in 10 images) allowed for greater spatial coverage at finer resolution. This approach revealed that the choice of sampling resolution must be appropriate to the scale of the ecological process as decreasing spatial resolution had a considerable effect on the strength and significance of the relationship between zooplankton biomass and their phytoplankton prey. Concurrently with development of the instrument, machine learning classifiers, capable of classifying the millions of images the PI collects per day, have been developed. Application of a machine learning classifier to PI images resulted in zooplankton dataset with very fine spatiotemporal scales where data could be resolved to minutes or meters. These data were aligned with other continuous datasets to re-evaluate relationships with predatory commercial pelagic fish using finer scale data. This thesis demonstrates the PI, and similar instruments, are a cost effective method that can provide a similar description to existing methods as well as provide new insight into plankton ecology by yielding fine spatiotemporal data
    corecore