2 resultados para Health Belief Model

em Digital Commons - Michigan Tech


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In Panama, one of the Environmental Health (EH) Sector’s primary goals is to improve the health of rural Panamanians by helping them to adopt behaviors and practices that improve access to and use of sanitation systems. In complying with this goal, the EH sector has used participatory development models to improve hygiene and increase access to latrines through volunteer managed latrine construction projects. Unfortunately, there is little understanding of the long term sustainability of these interventions after the volunteers have completed their service. With the Peace Corps adapting their Monitoring, Reporting, and Evaluation procedures, it is appropriate to evaluate the sustainability of sanitation interventions offering recommendations for the adaptions of the EH training program, project management, and evaluation procedures. Recognizing the need for evaluation of past latrine projects, the author performed a post project assessment of 19 pit latrine projects using participatory analysis methodologies. First, the author reviewed volunteers’ perspectives of pit latrine projects in a survey. Then, for comparison, the author performed a survey of latrine projects using a benchmarking scoring system to rate solid waste management, drainage, latrine siting, latrine condition, and hygiene. It was observed that the Sanitation WASH matrix created by the author was an effective tool for evaluating the efficacy of sanitation interventions. Overall more than 75%, of latrines constructed were in use. However, there were some areas where improvements could be made for both latrine construction and health and hygiene. The latrines scored poorly on the indicators related to the privacy structure and seat covers. Interestingly those are the two items least likely to be included in project subsidies. Furthermore, scores for hygiene-related indicators were low; particularly those related to hand washing and cleanliness of the kitchen, indicating potential for improvement in hygiene education. Based on these outcomes, the EH sector should consider including subsidies and standardized designs for privacy structures and seat covers for latrines. In addition, the universal adoption of contracts and/or deposits for project beneficiaries is expected to improve the completion of latrines. In order to address the low scores in the health and hygiene indicators, the EH sector should adapt volunteer training, in addition to standardizing health and hygiene intervention procedures. In doing so, the sector should mimic the Community Health Club model that has shown success in improving health and hygiene indicators, as well as use a training session plan format similar to those in the Water Committee Seminar manual. Finally, the sector should have an experienced volunteer dedicated to program oversight and post-project monitoring and evaluation.

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Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.