5 resultados para network models
em Digital Commons - Michigan Tech
Resumo:
Peru is a developing country with abundant fresh water resources, yet the lack of infrastructure leaves much of the population without access to safe water for domestic uses. The author of this report was a Peace Corps Volunteer in the sector of water & sanitation in the district of Independencia, Ica, Peru. Independencia is located in the arid coastal region of the country, receiving on average 15 mm of rain annually. The water source for this district comes from the Pisco River, originating in the Andean highlands and outflowing into the Pacific Ocean near the town of Pisco, Peru. The objectives of this report are to assess the water supply and sanitation practices, model the existing water distribution system, and make recommendations for future expansion of the distribution system in the district of Independencia, Peru. The assessment of water supply will be based on the results from community surveys done in the district of Independencia, water quality testing done by a detachment of the U.S. Navy, as well as on the results of a hydraulic model built in EPANET 2.0 to represent the distribution system. Sanitation practice assessments will be based on the surveys as well as observations from the author while living in Peru. Recommendations for system expansions will be made based on results from the EPANET model and the municipality’s technical report for the existing distribution system. Household water use and sanitation surveys were conducted with 84 families in the district revealing that upwards of 85% store their domestic water in regularly washed containers with lids. Over 80% of those surveyed are drinking water that is treated, mostly boiled. Of those surveyed, over 95% reported washing their hands and over 60% mentioned at least one critical time for hand washing when asked for specific instances. From the surveys, it was also discovered that over 80% of houses are properly disposing of excrement, in either latrines or septic tanks. There were 43 families interviewed with children five years of age or under, and just over 18% reported the child had a case of diarrhea within the last month at the time of the interview. Finally, from the surveys it was calculated that the average water use per person per day is about 22 liters. Water quality testing carried out by a detachment of the U.S. Navy revealed that the water intended for consumption in the houses surveyed was not suitable for consumption, with a median E. coli most probable number of 47/100 ml for the 61 houses sampled. The median total coliforms was 3,000 colony forming units per 100 ml. EPANET was used to simulate the water delivery system and evaluate its performance. EPANET is designed for continuous water delivery systems, assuming all pipes are always flowing full. To account for the intermittent nature of the system, multiple EPANET network models were created to simulate how water is routed to the different parts of the system throughout the day. The models were created from interviews with the water technicians and a map of the system created using handheld GPS units. The purpose is to analyze the performance of the water system that services approximately 13,276 people in the district of Independencia, Peru, as well as provide recommendations for future growth and improvement of the service level. Performance evaluation of the existing system is based on meeting 25 liters per person per day while maintaining positive pressure at all nodes in the network. The future performance is based on meeting a minimum pressure of 20 psi in the main line, as proposed by Chase (2000). The EPANET model results yield an average nodal pressure for all communities of 71 psi, with a range from 1.3 – 160 psi. Thus, if the current water delivery schedule obtained from the local municipality is followed, all communities should have sufficient pressure to deliver 25 l/p/d, with the exception of Los Rosales, which can only supply 3.25 l/p/d. However, if the line to Los Rosales were increased from one to four inches, the system could supply this community with 25 l/p/d. The district of Independencia could greatly benefit from increasing the service level to 24-hour water delivery and a minimum of 50 l/p/d, so that communities without reliable access due to insufficient pressure would become equal beneficiaries of this invaluable resource. To evaluate the feasibility of this, EPANET was used to model the system with a range of population growth rates, system lifetimes, and demands. In order to meet a minimum pressure of 20 psi in the main line, the 6-inch diameter main line must be increased and approximately two miles of trench must be excavated up to 30 feet deep. The sections of the main line that must be excavated are mile 0-1 and 1.5-2.5, and the first 3.4 miles of the main line must be increased from 6 to 16 inches, contracting to 10 inches for the remaining 5.8 miles. Doing this would allow 24-hour water delivery and provide 50 l/p/d for a range of population growth rates and system lifetimes. It is expected that improving the water delivery service would reduce the morbidity and mortality from diarrheal diseases by decreasing the recontamination of the water due to transport and household storage, as well as by maintaining continuous pressure in the system to prevent infiltration of contaminated groundwater. However, this expansion must be carefully planned so as not to affect aquatic ecosystems or other districts utilizing water from the Pisco River. It is recommended that stream gaging of the Pisco River and precipitation monitoring of the surrounding watershed is initiated in order to begin a hydrological study that would be integrated into the district’s water resource planning. It is also recommended that the district begin routine water quality testing, with the results available to the public.
Resumo:
A phenomenological transition film evaporation model was introduced to a pore network model with the consideration of pore radius, contact angle, non-isothermal interface temperature, microscale fluid flows and heat and mass transfers. This was achieved by modeling the transition film region of the menisci in each pore throughout the porous transport layer of a half-cell polymer electrolyte membrane (PEM) fuel cell. The model presented in this research is compared with the standard diffusive fuel cell modeling approach to evaporation and shown to surpass the conventional modeling approach in terms of predicting the evaporation rates in porous media. The current diffusive evaporation models used in many fuel cell transport models assumes a constant evaporation rate across the entire liquid-air interface. The transition film model was implemented into the pore network model to address this issue and create a pore size dependency on the evaporation rates. This is accomplished by evaluating the transition film evaporation rates determined by the kinetic model for every pore containing liquid water in the porous transport layer (PTL). The comparison of a transition film and diffusive evaporation model shows an increase in predicted evaporation rates for smaller pore sizes with the transition film model. This is an important parameter when considering the micro-scaled pore sizes seen in the PTL and becomes even more substantial when considering transport in fuel cells containing an MPL, or a large variance in pore size. Experimentation was performed to validate the transition film model by monitoring evaporation rates from a non-zero contact angle water droplet on a heated substrate. The substrate was a glass plate with a hydrophobic coating to reduce wettability. The tests were performed at a constant substrate temperature and relative humidity. The transition film model was able to accurately predict the drop volume as time elapsed. By implementing the transition film model to a pore network model the evaporation rates present in the PTL can be more accurately modeled. This improves the ability of a pore network model to predict the distribution of liquid water and ultimately the level of flooding exhibited in a PTL for various operating conditions.
Resumo:
Invasive exotic plants have altered natural ecosystems across much of North America. In the Midwest, the presence of invasive plants is increasing rapidly, causing changes in ecosystem patterns and processes. Early detection has become a key component in invasive plant management and in the detection of ecosystem change. Risk assessment through predictive modeling has been a useful resource for monitoring and assisting with treatment decisions for invasive plants. Predictive models were developed to assist with early detection of ten target invasive plants in the Great Lakes Network of the National Park Service and for garlic mustard throughout the Upper Peninsula of Michigan. These multi-criteria risk models utilize geographic information system (GIS) data to predict the areas at highest risk for three phases of invasion: introduction, establishment, and spread. An accuracy assessment of the models for the ten target plants in the Great Lakes Network showed an average overall accuracy of 86.3%. The model developed for garlic mustard in the Upper Peninsula resulted in an accuracy of 99.0%. Used as one of many resources, the risk maps created from the model outputs will assist with the detection of ecosystem change, the monitoring of plant invasions, and the management of invasive plants through prioritized control efforts.
Resumo:
Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.
Resumo:
In recent years, security of industrial control systems has been the main research focus due to the potential cyber-attacks that can impact the physical operations. As a result of these risks, there has been an urgent need to establish a stronger security protection against these threats. Conventional firewalls with stateful rules can be implemented in the critical cyberinfrastructure environment which might require constant updates. Despite the ongoing effort to maintain the rules, the protection mechanism does not restrict malicious data flows and it poses the greater risk of potential intrusion occurrence. The contributions of this thesis are motivated by the aforementioned issues which include a systematic investigation of attack-related scenarios within a substation network in a reliable sense. The proposed work is two-fold: (i) system architecture evaluation and (ii) construction of attack tree for a substation network. Cyber-system reliability remains one of the important factors in determining the system bottleneck for investment planning and maintenance. It determines the longevity of the system operational period with or without any disruption. First, a complete enumeration of existing implementation is exhaustively identified with existing communication architectures (bidirectional) and new ones with strictly unidirectional. A detailed modeling of the extended 10 system architectures has been evaluated. Next, attack tree modeling for potential substation threats is formulated. This quantifies the potential risks for possible attack scenarios within a network or from the external networks. The analytical models proposed in this thesis can serve as a fundamental development that can be further researched.