Thesis (M.S.)--University of Arkansas, Fayetteville, 2005. / "May 2005." Includes bibliographical references (leaves 27-30). Also available online (PDF file) by a subscription to the set or by purchasing the individual file.

Thesis (M.S.)--University of Arkansas, Fayetteville, 2005. / "May 2005." Includes bibliographical references (leaves 27-30).

The safety of dams is crucial in ensuring the continual availability of water, safety of the surrounding communities and infrastructure. Surveillance systems are implemented to monitor the structural integrity of certain dams which have a safety risk. The components and extent of the surveillance systems adopted depends on many factors, which include the type of dam wall structure used to impound the reservoir, geotechnical and environmental conditions. The case study used for this thesis is Kouga Dam located in the Eastern Cape Province of South Africa. It is a double curvature, concrete arch dam which supplies water for domestic, irrigation and industrial use to the Gamtoos River Valley and Nelson Mandela Metropolitan. During construction the stability of the right flank was questioned and subsequently, remedial measures were taken in order to increase the shear resistance of this flank. Previous dam safety evaluations also noted the possibility of Alkali Silica Reaction (ASR) occurring within the structure which resulted in concrete swelling and loss of strength. Due to these factors and the large hazard potential rating associated with this dam an intensive surveillance system has been used to monitor the dam's behaviour during operation. In this thesis the results of the surveillance system is analysed. A strong linear relationship exists between the temperature loading and displacement response of the dam wall. Changes in temperature initiate the response of the structure almost instantaneously. A more complex relationship exists between hydrostatic loading and the displacement response of the structure. A phase lag of approximately one to three months is evident between these two variables. Since construction the displacement and strain rates in the upstream (y) and upward (z) directions are 0.3mm/annum and 8.6με/annum respectively. However, since 1989 there has been a reduction in the average displacement and strain rates in all directions by approximately 70%. This may suggest that the ASR has stabilized. The vertical construction joints, especially the central and upper joints, are relatively open during low water levels. The structure is found to transfer the imposed loading mainly to the central foundation via dominant cantilever action. As a result the reaction forces on the upper foundation have been found to be relatively low, lowering the risk of potential shear failure of the right foundation. Small foundation movements of less than 0.3mm have been observed within the foundation downstream of the dam wall on the right flank. These movements are between 10 and 40m within the foundations.

台灣四十多年來，隨著工業化及經濟快速的發展，國民所得逐年的增加與生活水準的日漸提高，已使得大眾對於住宅品質愈來愈加重視。所謂住宅品質，其內涵除了客觀上基本設施的完備外，尚應包括主觀滿意度的提高，而提高滿意度的方法，則可以藉著適當管理維護工作的執行，使住宅環境能維持在一定的居住品質之上。由於我國對於住宅管理維護工作之執行，除了國民住宅外，目前並無明確的管理規定，而民間對於住宅的管理維護，則分別有許多不同的管理組織或管理維護公司，採取不同的管理維護方式在進行管理維護的工作，對於不同的管理維護方式，其所獲得的住宅品質水準為何?則有待進一步加以研究。 因此，本文擬先建立住宅管理維護可提昇住宅品質之假設，首先蒐集住宅品質及住宅管理維護之相關文獻與調查報告，對目前之住宅品質情形及住宅管理維護狀況做初步的瞭解。其次，為了對住宅品質及住宅管理維護之關係做進一步的探討，本研究將依據一般民間住宅及國民住宅不同的管理維護方式，在台北都會區中選取七個研究個案，對個案不同的管理維護方式與住宅品質狀況做一調查，並藉著問卷抽樣調查的方法，瞭解住戶對目前住宅品質及住宅管理維護之滿意情形，然後根據調查資料來建立住宅管理維護影響住宅品質之迴歸分析模式，分析之模式主要有二，其一為建立住宅屬性、住戶屬性及管理維護屬性影響住宅品質之迴歸模式，其二為將住戶滿意度之問卷變項透過因子分析技術，選出主要之因子，做為迴歸分析模式之自變項。根據本論文之初步結果顯示，模式一以屋齡、費用繳交率、住宅安全措施等項目，對於住宅品質之滿意度影響較為顯著，模式二則以管制公約、公共設施、管理費等因子，對住宅品質滿意度之影響較為顯著。 最後，本文擬根據實證研究的結果，對目前國民住宅及一般民間住宅之管理維護法令與政策，未來之修正與研擬方向做一探討與建議，希望從法令之訂定與執行，落實到民間住宅管理之實際運作，使住宅管理維護制度得以建立，進而達到提昇住宅品質之目標。 / This paper is trying to answer whether housing management and maintenance could improve (or influence) housing quality or not? Are they any different housing quality satisfication among different types of housing management and maintenance? In order to answer these questions, we slect seven cases to survey their housing quality as well as management and maintenance situation. Two models are tested, one is housing quality regression analysis of housing management and maintenance factors; the other is household satisfication factor analysis of housing quality. Both results support that housing management and maintenance is important to housing quality. Some policy implications are also suggested, particular in housing management and maintenance regulation.

<p style="text-align: justify;">Vrednost objekata i njihova upotrebljivost opadaju vremenom usled neadekvatnog održavanja. Uobičajen model korektivnog održavanja postaje neprihvatljiv zbog toga što je ekonomski neodrživ. Reaktivno održavanje se zamenjuje proaktivnim održavanjem čijim se planiranjem nepredvidive intervencije svode na najmanju meru. To je moguće ostvariti uvođenjem savremene organizacije upravljanja održavanjem. Za kvalitetno održavanje neophodno je postojanje baze podataka koja omogućava planiranje i kontrolu aktivnosti na održavanju objekata.</p> / <p style="text-align: justify;">The value of buildings as well as their utilization declines over the time due to<br />inadequate maintenance. Usual method of corrective maintenance becomes<br />unacceptable due to its economic unsustainability. Reactive maintenance is<br />replaced by proactive maintenance the planning of which provides for<br />reduction of unpredictable interventions to the greatest possible extent. This<br />can be achieved by introducing modern organization of maintenance<br />management. With a view to establishing quality maintenance, it is<br />necessary to have the data base which enables planning and supervision of<br />building maintenance activities.</p>

No description available.

Highway clients are increasingly concerned with the environmental consequences and sustainability implications of their highway maintenance service. This is because the service consumes a significant amount of natural resources, is financial and energy-intensive and is a large Greenhouse gas (GHG) emitter responsible for global warming and climate change. This has placed the highway maintenance sector, including its supply chain under increasing pressure to deliver well-maintained low-carbon maintenance service, whilst addressing its climate change impacts. The highway stakeholders increasing focus on carbon footprinting is a direct response to the legal obligation presented by the enactment of the UK s Climate Change Act (2008) and the Carbon Reduction Commitments. Investment decisions on highway infrastructure must now account for carbon and financial costs in a balanced manner. Highway clients now require their supply chains to demonstrate the capacity to reduce both direct and indirect carbon, and provide carbon footprint information relating to the work done or being tendered for. This is driving the sector to re-think its business operations within environmental, economic and social limits, which inherently presents risks and opportunities poorly understood by the stakeholders. It requires an in-depth understanding of the business operations, inputs and outputs. These business requirements are compounded given the lack of an agreed industrial methodology standard focusing on carbon footprinting, the knowledge and skill gaps, system boundary definitions, credible industrial data and their collection approach. The aim of this study is to develop a project-focused and process-based carbon footprinting methodology that includes a decision-support and carbon management tool to assist carbon management decision-making in highway maintenance planning and operation. This study then explored how the PAS2050 protocol can enhance the highway maintenance service delivery carbon footprinting and identify opportunities for reduction. It briefly reviews carbon emissions performance and the UK s highway maintenance sector, and developed a methodological framework that includes a carbon evaluation tool (the sponsor s business focus tool) based on the PAS2050 protocol. The framework developed is specific to highway maintenance planning and operation. It offers a carbon Life Cycle Assessment (LCA) tool that can identify emission hotspots across the process value chain, and inform a carbon reduction hierarchy. The implementation of the PAS2050-compliant methodology framework and the carbon evaluation tool for core highway maintenance processes (for example, pavement resurfacing, pavement marking, bulk lamp replacement and grass cutting), in addition to carbon footprinting across different site locations (urban, semi-urban and rural) are presented. The results indicate that materials production and their delivery to site (embodied carbon) are areas of carbon hotspots. This represents an important decision point for highway designers, managers and maintainers in order to deliver low-carbon service. These carbon hotspots suggest a less energy-intensive or green materials manufacturing process, responsible sourcing, use of recycled and secondary materials sourced locally (closer to sites) and delivered in bulk. The step-by-step carbon footprinting approach presented in this study is unique. It can be used by other sectors within the built environment as a pragmatic means of identifying and prioritising areas of potential carbon reduction through informed decision-making.

Resumo: Neste trabalho se apresenta uma técnica de redução de dados para monitoração e diagnóstico automático de grupos geradores hidroelétricos com base na análise de vibrações, utilizando redes neurais artificiais. Os sinais de vibração são processados numericamente para se obter um espectro normalizado com no máximo doze freqüências, especialmente determinadas para cada máquina em particular, de tal forma a torná-lo representativo da condição da máquina. A definição das bandas de freqüência a serem usadas no processamento desse espectro especial é feita para cada equipamento a ser monitorado com auxílio de um ambiente computacional desenvolvido e apresentado neste trabalho. Um programa protótipo de monitoração baseado nestas técnicas foi desenvolvido e é apresentado com uso de exemplos de aplicação. / Abstract: In this work a data reduction technique based on vibration analysis that can be applied to both monitoring and automatic diagnosis of rotating machineries together with use of neural networks is presented. Vibration signals are processed to obtain a normalized spectrum with up to 12 frequency bands that should be defined for each particular machine. In this manner this special spectrum can become representative of the machine's working condition. The definition of the spectrum's bands that will be used in data processing is carried out for each machine by use of a computational environment that has been developed. This environment is also shown in this work. A prototype monitoring program based in this technique also has been developed and its application is highlighted with examples. / Orientador: João Antonio Pereira / Coorientador: Adyles Arato Júnior / Banca: Alberto Tamagna / Banca: Luiz de Paula do Nascimento / Mestre

Made available in DSpace on 2014-06-11T19:27:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-09-05Bitstream added on 2014-06-13T20:55:57Z : No. of bitstreams: 1 almeida_fcl_me_ilha.pdf: 3597520 bytes, checksum: 3503cdbcd54e460db80583534b7d06dd (MD5) / Neste trabalho se apresenta uma técnica de redução de dados para monitoração e diagnóstico automático de grupos geradores hidroelétricos com base na análise de vibrações, utilizando redes neurais artificiais. Os sinais de vibração são processados numericamente para se obter um espectro normalizado com no máximo doze freqüências, especialmente determinadas para cada máquina em particular, de tal forma a torná-lo representativo da condição da máquina. A definição das bandas de freqüência a serem usadas no processamento desse espectro especial é feita para cada equipamento a ser monitorado com auxílio de um ambiente computacional desenvolvido e apresentado neste trabalho. Um programa protótipo de monitoração baseado nestas técnicas foi desenvolvido e é apresentado com uso de exemplos de aplicação. / In this work a data reduction technique based on vibration analysis that can be applied to both monitoring and automatic diagnosis of rotating machineries together with use of neural networks is presented. Vibration signals are processed to obtain a normalized spectrum with up to 12 frequency bands that should be defined for each particular machine. In this manner this special spectrum can become representative of the machine’s working condition. The definition of the spectrum’s bands that will be used in data processing is carried out for each machine by use of a computational environment that has been developed. This environment is also shown in this work. A prototype monitoring program based in this technique also has been developed and its application is highlighted with examples.

Serienfertiger im Bereich der Innenhochdruck-Umformung stehen unter starkem Wettbewerbsdruck alternativer klassischer Fertigungen und deren Kostenkriterien. Wechselnde Produktionsanforderungen im globalisierten Marktumfeld erfordern flexibles Handeln bei höchster Qualität und niedrigen Kosten. Durch Reduzierung der Lager- und Umlaufbestände können Kosteneinsparungen erzielt werden. Störungsbedingte Ausfälle an IHU-Anlagen gilt es dabei auf ein Minimum zu reduzieren, um die vereinbarten Liefertermine fristgerecht zu erfüllen und Konventionalstrafen zu umgehen. Die erforderliche Produktivität und das angestrebte Qualitätsniveau lässt sich nur durch angepasste Instandhaltungsstrategien aufrechterhalten, weshalb ein Konzept für die vorausschauende Instandhaltung mit integriertem Qualitätsmanagement speziell für den Bereich der IHU erarbeitet wurde. Dynamische Prozess- und Instandhaltungsanpassungen sind zentraler Bestandteil der Entwicklungsarbeit.