Dissertations / Theses on the topic '120299 Building not elsewhere classified'
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Parr, Eric. "Performance of an air-to-air heat pump heating and recovery unit at high ventilation rates." Thesis, University of Central Lancashire, 2007. http://clok.uclan.ac.uk/20042/.
Full textOlaniyi, Olayinka Oluseyi. "Development of a facilities management framework for sustainable building practices in Nigeria." Thesis, University of Central Lancashire, 2017. http://clok.uclan.ac.uk/20755/.
Full textOliver, Christine. "Systemic reflexivity : building theory for organisational consultancy." Thesis, University of Bedfordshire, 2012. http://hdl.handle.net/10547/567099.
Full textWong, Kwok Wai Johnny. "Development of selection evaluation and system intelligence analytic models for the intelligent building control systems." Thesis, The Hong Kong Polytechnic University, 2007. https://eprints.qut.edu.au/20343/1/c20343.pdf.
Full textQunby, Rohan G. H. "Time, space, city and resistance : situating Negri's multitude in the contemporary metropolis : a thesis presented in partial fulfilment of the requirements for the degree of Masters in Public Policy at Massey University, Auckland, New Zealand." Massey University, 2009. http://hdl.handle.net/10179/923.
Full text(9750833), Zilong Yang. "Automated Building Extraction from Aerial Imagery with Mask R-CNN." Thesis, 2020.
Find full textBuildings are one of the fundamental sources of geospatial information for urban planning, population estimation, and infrastructure management. Although building extraction research has gained considerable progress through neural network methods, the labeling of training data still requires manual operations which are time-consuming and labor-intensive. Aiming to improve this process, this thesis developed an automated building extraction method based on the boundary following technique and the Mask Regional Convolutional Neural Network (Mask R-CNN) model. First, assisted by known building footprints, a boundary following method was used to automatically best label the training image datasets. In the next step, the Mask R-CNN model was trained with the labeling results and then applied to building extraction. Experiments with datasets of urban areas of Bloomington and Indianapolis with 2016 high resolution aerial images verified the effectiveness of the proposed approach. With the help of existing building footprints, the automatic labeling process took only five seconds for a 500*500 pixel image without human interaction. A 0.951 intersection over union (IoU) between the labeled mask and the ground truth was achieved due to the high quality of the automatic labeling step. In the training process, the Resnet50 network and the feature pyramid network (FPN) were adopted for feature extraction. The region proposal network (RPN) then was trained end-to-end to create region proposals. The performance of the proposed approach was evaluated in terms of building detection and mask segmentation in the two datasets. The building detection results of 40 test tiles respectively in Bloomington and Indianapolis showed that the Mask R-CNN model achieved 0.951 and 0.968 F1-scores. In addition, 84.2% of the newly built buildings in the Indianapolis dataset were successfully detected. According to the segmentation results on these two datasets, the Mask R-CNN model achieved the mean pixel accuracy (MPA) of 92% and 88%, respectively for Bloomington and Indianapolis. It was found that the performance of the mask segmentation and contour extraction became less satisfactory as the building shapes and roofs became more complex. It is expected that the method developed in this thesis can be adapted for large-scale use under varying urban setups.
(10692402), Jorge Alfredo Rojas Rondan. "A BIM-based tool for formwork management in building projects." Thesis, 2021.
Find full text(5930687), Jinglin Jiang. "Investigating How Energy Use Patterns Shape Indoor Nanoaerosol Dynamics in a Net-Zero Energy House." Thesis, 2019.
Find full textResearch on net-zero energy buildings (NZEBs) has been largely centered around improving building energy performance, while little attention has been given to indoor air quality. A critically important class of indoor air pollutants are nanoaerosols – airborne particulate matter smaller than 100 nm in size. Nanoaerosols penetrate deep into the human respiratory system and are associated with deleterious toxicological and human health outcomes. An important step towards improving indoor air quality in NZEBs is understanding how occupants, their activities, and building systems affect the emissions and fate of nanoaerosols. New developments in smart energy monitoring systems and smart thermostats offer a unique opportunity to track occupant activity patterns and the operational status of residential HVAC systems. In this study, we conducted a one-month field campaign in an occupied residential NZEB, the Purdue ReNEWW House, to explore how energy use profiles and smart thermostat data can be used to characterize indoor nanoaerosol dynamics. A Scanning Mobility Particle Sizer and Optical Particle Sizer were used to measure indoor aerosol concentrations and size distributions from 10 to 10,000 nm. AC current sensors were used to monitor electricity consumption of kitchen appliances (cooktop, oven, toaster, microwave, kitchen hood), the air handling unit (AHU), and the energy recovery ventilator (ERV). Two Ecobee smart thermostats informed the fractional amount of supply airflow directed to the basement and main floor. The nanoaerosol concentrations and energy use profiles were integrated with an aerosol physics-based material balance model to quantify nanoaerosol source and loss processes. Cooking activities were found to dominate the emissions of indoor nanoaerosols, often elevating indoor nanoaerosol concentrations beyond 104 cm-3. The emission rates for different cooking appliances varied from 1011 h-1 to 1014 h-1. Loss rates were found to be significantly different between AHU/ERV off and on conditions, with median loss rates of 1.43 h-1 to 3.68 h-1, respectively. Probability density functions of the source and loss rates for different scenarios will be used in Monte Carlo simulations to predict indoor nanoaerosol concentrations in NZEBs using only energy consumption and smart thermostat data.
(10292846), Zhipeng Deng. "RECOGNITION OF BUILDING OCCUPANT BEHAVIORS FROM INDOOR ENVIRONMENT PARAMETERS BY DATA MINING APPROACH." Thesis, 2021.
Find full text(11187477), Jin Wu. "Invariant Signatures for Supporting BIM Interoperability." Thesis, 2021.
Find full textBuilding Information Modeling (BIM) serves as an important media in supporting automation in the architecture, engineering, and construction (AEC) domain. However, with its fast development by different software companies in different applications, data exchange became labor-intensive, costly, and error-prone, which is known as the problem of interoperability. Industry foundation classes (IFC) are widely accepted to be the future of BIM in solving the challenge of BIM interoperability. However, there are practical limitations of the IFC standards, e.g., IFC’s flexibility creates space for misuses of IFC entities. This incorrect semantic information of an object can cause severe problems to downstream uses. To address this problem, the author proposed to use the concept of invariant signatures, which are a new set of features that capture the essence of an AEC object. Based on invariant signatures, the author proposed a rule-based method and a machine learning method for BIM-based AEC object classification, which can be used to detect potential misuses automatically. Detailed categories for beams were tested to have error-free performance. The best performing algorithm developed by the methods achieved 99.6% precision and 99.6% recall in the general building object classification. To promote automation and further improve the interoperability of BIM tasks, the author adopted invariant signature-based object classification in quantity takeoff (QTO), structural analysis, and model validation for automated building code compliance checking (ACC). Automation in such BIM tasks was enabled with high accuracy.
Piper, Christine. "The impact of certification on women-owned construction firms in the United States." 2007. http://arrow.unisa.edu.au:8081/1959.8/46352.
Full text(5929979), Yun-Jou Lin. "Point Cloud-Based Analysis and Modelling of Urban Environments and Transportation Corridors." Thesis, 2019.
Find full text(11199507), Christiane J. Ley. "Evaluating the Impacts of Sustainable Water Use Measures on Drinking Water Microbiology and Chemistry." Thesis, 2021.
Find full text(11191899), Jie Ma. "A SEQUENTIAL APPROACH FOR ACHIEVING SEPARATE SENSIBLE AND LATENT COOLING." Thesis, 2021.
Find full textCurrent air conditioning systems generally operate with a relatively fixed moisture removal capacity, and indoor humidity conditions are usually not actively controlled in most buildings. If we focus only on sensible heat removal, an air conditioning system could operate with a fairly high evaporating temperature, and consequently a high coefficient of performance (COP). However, to provide an acceptable level of dehumidification, air conditioners typically operate with a much lower evaporating temperature (and lower COP) to ensure that the air is cooled below its dew point to achieve dehumidification. The latent (moisture related) loads in a space typically only represent around 20-30% of the total load in many environments; however, the air conditioning system operates 100% of the time at a low COP to address this small fraction of the load. To address issues associated with inadequate dehumidification and high energy consumption of conventional air conditioning systems, the use of a separate sensible and latent cooling (SSLC) system can dramatically increase system COP and provide active humidity control. Most current SSLC approaches that are reported in the literature require the installation of multiple components or systems in addition to a conventional air conditioner to separately address the sensible and latent loads. This approach increases the overall system installation and maintenance costs and complicates the controller design.
A sequential SSLC system is proposed and described in this work takes full advantage of readily available variable speed technology and utilizes independent speed control of both the compressor and evaporator fan, so that a single direct expansion (DX) air-conditioning (A/C) system can be operated in such a way to separately address the sensible and latent loads in a highly efficient manner. In this work, a numerical model of DX A/C system is developed and validated through experiential testing to predict the performance under varied equipment speeds and then used to investigate the energy saving potential with the implementation of the proposed sequential SSLC system. To realize the sequential SSLC system approach, various corresponding control strategies are proposed and explained in this work that minimizes energy consumption while provides active control over both space temperature and relative humidity. At the end of this document, the benefits of applying the SSLC system in a prototype residential building under different typical climate characteristics are demonstrated.
(11181858), Yu-Wei Hung. "Simulation and Optimization of Desiccant-Based Wheel integrated HVAC Systems." Thesis, 2021.
Find full text(11176893), Toy W. Andrews. "Opportunities from Disaster: The Case for Using The Circular Economy in Debris Management." Thesis, 2021.
Find full text(9189365), Anthony A. Lowe. "The Theory of Applied Mind of Programming." Thesis, 2020.
Find full textThe Theory of Applied Mind of Programming (TAMP) provides a new model for describing how programmers think and learn. Historically, many students have struggled when learning to program. Programming as a discipline lives in logic and reason, but theory and science tell us that people do not always think rationally. TAMP builds upon the groundbreaking work of dual process theory and classical educational theorists (Piaget, Vygotsky, and Bruner) to rethink our assumptions about cognition and learning. Theory guides educators and researchers to improve their practice, not just their work but also their thinking. TAMP provides new theoretical constructs for describing the mental activities of programming, the challenges in learning to program, as well as a guidebook for creating and recognizing the value of theory.
This dissertation is highly nontraditional. It does not include a typical empirical study using a familiar research methodology to guide data collection and analysis. Instead, it leverages existing data, as accumulated over a half-century of computing education research and a century of research into cognition and learning. Since an applicable methodology of theory-building did not exist, this work also defines a new methodology for theory building. The methodology of this dissertation borrows notation from philosophy and methods from grounded theory to define a transparent and rigorous approach to creating applied theories. By revisiting past studies through the lens of new theoretical propositions, theorists can conceive, refine, and internally validate new constructs and propositions to revolutionize how we view technical education.
The takeaway from this dissertation is a set of new theoretical constructs and promising research and pedagogical approaches. TAMP proposes an applied model of Jerome Bruner's mental representations that describe the knowledge and cognitive processes of an experienced programmer. TAMP highlights implicit learning and the role of intuition in decision making across many aspects of programming. This work includes numerous examples of how to apply TAMP and its supporting theories in re-imagining teaching and research to offer alternative explanations for previously puzzling findings on student learning. TAMP may challenge conventional beliefs about applied reasoning and the extent of traditional pedagogy, but it also offers insights on how to promote creative problem-solving in students.
(8790986), Swaroop Ashok. "Construction Decision making using Virtual Reality." Thesis, 2020.
Find full textWe make decisions every day, some with the potential for a huge impact on our lives. This process of decision-making is crucial not only for individuals but for industries, including construction. Unlike the manufacturing industry, where one can make certain decisions regarding an actual product by looking at it in real time, the nature of construction is different. Here, decisions are to be made on a product which will be built somewhere in the near future. The complex and interim nature of construction projects, along with factors like time essence, increasing scale of projects and multitude of stakeholders, makes it even more difficult to reach consensus. Incorporating VR can aid in getting an insight on the final product at the very beginning of the project life cycle. With a visual representation, the stakeholders involved can collaborate on a single platform to assess the project, share common knowledge and make choices that would produce better results in all major aspects like cost, quality, time and safety. This study aims at assessing decision-making in the earlier stages of construction and then evaluating the performance of immersive and non-immersive VR platforms.
(5930906), Jacob J. Torres. "The Biowall Field Test Analysis and Optimization." Thesis, 2019.
Find full textA residential botanical
air filtration system (Biowall) to investigate the potential for using
phytoremediation to remove contaminants from indoor air was developed. A full scale and functioning prototype was
installed in a residence located in West Lafayette, Indiana. The prototype was integrated into the central
Heating, Ventilating, and Air Conditioning (HVAC) system of the home. This
research evaluated the Biowall operation to further its potential as an energy
efficient and sustainable residential air filtration system.
The main research effort began after the Biowall was installed in the residence. A field evaluation, which involved a series of measurements and data analysis, was conducted to identify treatments to improve Biowall performance. The study was conducted for approximately one year (Spring 2017-Spring 2018). Based on the initial data set, prioritization of systems in need of improvement was identified and changes were imposed. Following a post-treatment testing period, a comparison between the initial and final performances was completed with conclusions based on this comparison.
The engineering and analysis reported in this document focus on the air flow path through the Biowall, plant growth, and the irrigation system. The conclusions provide an extensive evaluation of the design, operation, and function of the Biowall subsystems under review.
(9669701), Robert Thomas Ryan. "EXAMINING THE RELATIONSHIP OF BID DIFFERENCE AND DISADVANTAGED BUSINESS ENTERPRISE PARTICIPATION GOALS IN HIGHWAY CONSTRUCTION PROJECTS." Thesis, 2020.
Find full text(9622742), Kelly A. McFall. "ADDRESSING CORPORATE KNOWLEDGE LOSS IN A UNIVERSITY UTILITY PLANT." Thesis, 2020.
Find full textThis research was a pilot study in a larger project that focused on how to retrieve knowledge from retiring long-term employees of a small university utility plant, incorporate that material into their existing training program, and during the process reduce the training time for current and future employees. Wade utility plant faced the retirement of eight employees with nearly 200 years of corporate knowledge within three years, but their current training program required seven to nine years to complete. The study utilized interviews, first-hand observation and partnership with current employees to explore how best to obtain the corporate knowledge that would be lost when the proletarian workers retired. The study revealed that the training program needed to be updated, and communication, trust and training evaluation continuity needed to be addressed. Due to these issues, trust was built through transparency by the researcher, and suggestions were made to management for moving forward. This study adds to the body of knowledge by utilizing knowledge capture techniques in a utility plant, highlighting effective knowledge capture techniques for proletarian workers, the importance of corporate planning for the effect of group retirements, and how incorporating proletarian workers into training creation can make a positive impact on company relationships.