Browsing by Subject "TSP"
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Item A science based emission factor for particulate matter emitted from cotton harvesting(2009-05-15) Wanjura, John DavidPoor regional air quality in some states across the US cotton belt has resulted in increased pressure on agricultural sources of particulate matter (PM) from air pollution regulators. Moreover, inaccurate emission factors used in the calculation of annual emissions inventories led to the identification of cotton harvesting as a significant source of PM10 in California and Arizona. As a result, cotton growers in these states are now required to obtain air quality permits and submit management practice plans detailing the actions taken by the producer to reduce fugitive PM emissions from field operations. The objective of this work was to develop accurate PM emission factors for cotton harvesting in terms of total suspended particulate (TSP), PM10, and PM2.5. Two protocols were developed and used to develop PM emission factors from cotton harvesting operations on three farms in Texas during 2006 and 2007. Protocol one utilized TSP concentrations measured downwind of harvesting operations with meteorological data measured onsite in a dispersion model to back-calculate TSP emission flux values. Flux values, determined with the regulatory dispersion models ISCST3 and AERMOD, were converted to emission factors and corrected with results from particle size distribution (PSD) analyses to report emission factors in terms of PM10 and PM2.5. Emission factors were developed for two-row (John Deere 9910) and sixrow (John Deere 9996) cotton pickers with protocol one. The uncertainty associated with the emission factors developed through protocol one resulted in no significant difference between the emission factors for the two machines. Under the second protocol, emission concentrations were measured onboard the six-row cotton picker as the machine harvested cotton. PM10 and PM2.5 emission factors were developed from TSP emission concentration measurements converted to emission rates using the results of PSD analysis. The total TSP, PM10, and PM2.5 emission factors resulting from the source measurement protocol are 1.64 ? 0.37, 0.55 ? 0.12, and 1.58E- 03 ? 4.5E-04 kg/ha, respectively. These emission factors contain the lowest uncertainty and highest level of precision of any cotton harvesting PM emission factors ever developed. Thus, the emission factors developed through the source sampling protocol are recommended for regulatory use.Item Approximation Algorithms and Heuristics for a Heterogeneous Traveling Salesman Problem(2011-08-08) Rangarajan, RahulUnmanned Vehicles (UVs) are developed for several civil and military applications. For these applications, there is a need for multiple vehicles with different capabilities to visit and monitor a set of given targets. In such scenarios, routing problems arise naturally where there is a need to plan paths in order to optimally use resources and time. The focus of this thesis is to address a basic optimization problem that arises in this setting. We consider a routing problem where some targets have to be visited by specific vehicles. We approach this problem by dividing the routing into two sub problems: partitioning the targets while satisfying vehicle target constraints and sequencing. We solve the partitioning problem with the help of a minimum spanning tree algorithm. We use 3 different approaches to solve the sequencing problem; namely, the 2 approximation algorithm, Christofide's algorithm and the Lin - Kernighan Heuristic (LKH). The approximation algorithms were implemented in MATLAB. We also developed an integer programming (IP) model and a relaxed linear programming (LP) model in C with the help of Concert Technology for CPLEX, to obtain lower bounds. We compare the performance of the developed approximation algorithms with both the IP and the LP model and found that the heuristic performed very well and provided the better quality solutions as compared to the approximation algorithms. It was also found that the approximation algorithms gave better solutions than the apriori guarantees.Item Engineering approaches to address erros in measured and predicted particulate matter concentrations(Texas A&M University, 2006-08-16) Wanjura, John DavidSome of the air pollution regulations in the United States are based on an application of the National Ambient Air Quality Standards at the property line. Agricultural operations such as cotton gins, feed mills, and cattle feed yards may be inappropriately regulated by such regulations if the current methods of measuring and predicting the concentrations of regulated pollutants are used. The regulated particulate matter pollutants are those with aerodynamic equivalent diameters less than or equal to a nominal 10 and 2.5 micrometers (PM10 and PM2.5) respectively. The current Federal Reference Method PM10 and PM2.5 samplers exhibit oversampling errors when sampling dusts with particle size distributions similar to those of agricultural sources. These errors are due to the interaction of the performance characteristics of the sampler with the particle size distribution of the dust being sampled. The results of this work demonstrate the development of a new sampler that may be used to accurately sample total suspended particulate (TSP) concentrations. The particle size distribution of TSP samples can be obtained and used to more accurately determine PM10 and PM2.5 concentrations. The results of this work indicate that accurate measures of TSP can be taken on a low volume basis. This work also shows that the low volume samplers provide advantages in maintaining more consistent sampling flow rates, and more robust measurements of TSP concentrations in high dust concentrations. The EPA approved dispersion model most commonly used to estimate concentrations downwind from a stationary source is the Industrial Source Complex Short Term version 3 (ISCST3). ISCST3 is known to over-predict downwind concentrations from low level point sources. The results of this research show that the magnitude of these errors could be as much as 250%. A new approach to correcting these errors using the power law with P values as a function of stability class and downwind distance is demonstrated. Correcting the results of ISCST3 using this new approach results in an average estimated concentration reduction factor of 2.3.Item Evaluation of PM10 and Total Suspended Particulate Sampler Performance Through Wind Tunnel Testing(2011-10-21) Thelen, Mary KatherineParticulate matter (PM) concentrations in ambient air can be monitored by gravimetric sampling near a source using Federal Reference Method (FRM) samplers. PM is regulated by size, with PM10, which is comprised of particles with aerodynamic equivalent diameters less than or equal to 10 ?m, being the main focus of this research. FRM PM10 samplers exhibit sampling errors when sampling dusts with mass median diameters (MMDs) that are larger than the 10 ?m sampler cutpoint. For industries to be regulated equitably, these sampler errors must be quantified and understood. This research evaluates the performance of FRM PM10 and low volume total suspended particulate (TSP) samplers under the controlled conditions of a wind tunnel. The performance evaluation was conducted by observing the sampler cutpoints, slopes, and measured concentrations. These measured values were compared to values obtained using a collocated isokinetic reference sampler. The results of this research indicate that PM10 samplers do not operate as intended under all conditions. The cutpoint of the PM10 inlets was significantly higher than the maximum FRM limit of 10.5 ?m when sampling dust with MMDs larger than the cutpoint of the sampler. The slope values for the PM10 inlets were significantly higher than the maximum FRM limit of 1.6. MMDs and geometric standard deviations of PM collected by TSP samplers were significantly different than those of PM collected using the collocated isokinetic sampler. The concentrations measured by the TSP samplers were significantly higher than the collocated isokinetic sampler. The results of this research provide a better understanding of the performance of TSP and PM10 samplers operating under different conditions and shows that these samplers are not operating as intended. Because of this, industries may be suffering the consequences of inequitable regulation.Item Heurisic approaches for no-depot k-traveling salesmen problem with a minmax objective(Texas A&M University, 2007-09-17) Na, ByungsooThis thesis deals with the no-depot minmax Multiple Traveling Salesmen Problem (MTSP), which can be formulated as follows. Given a set of n cities and k salesmen,find k disjoint tours (one for each salesmen) such that each city belongs to exactly one tour and the length of the longest of k tours is minimized. The no-depot assumption means that the salesmen do not start from and return to one fixed depot. The no-depot model can be applied in designing patrolling routes, as well as in business situations, especially where salesmen work from home or the company has no central office. This model can be also applied to the job scheduling problem with n jobs and k identical machines. Despite its potential applicability to a number of important situations, the research literature on the no-depot minmax k-TSP has been limited, with no reports on computational experiments. The previously published results included the proof of NP-hardness of the problem of interest, which motivates using heuristics for its solution. This thesis proposes several construction heuristic algorithms, including greedy algorithms, cluster first and route second algorithms, and route first and cluster second algorithms. As a local search method for a single tour, 2-opt search and Lin-Kernighan were used, and for a local search method between multiple tours, relocation and exchange (edge heuristics) were used. Furthermore, to prevent the drawback of trapping in the local minima, the simulated annealing method is used. Extensive computational experiments were carried out using TSPLIB instances. Among construction algorithms, route first and cluster second algorithms including removing two edges method performed best. In terms of running time, clustering first and routing second algorithms took shorter time on large-scale instances. The simulated annealing could produce better solutions than the descent method, but did not always perform well in terms of average solution. To evaluate the performance of the proposed heuristic methods, their solutions were compared with the optimal solutions obtained using a mixed-integer programming formulation of the problem. For small-scale problems, heuristic solutions were equal to the optimal solution output by CPLEX.Item Path Planning Algorithms for Multiple Heterogeneous Vehicles(2010-01-16) Oberlin, Paul V.Unmanned aerial vehicles (UAVs) are becoming increasingly popular for surveillance in civil and military applications. Vehicles built for this purpose vary in their sensing capabilities, speed and maneuverability. It is therefore natural to assume that a team of UAVs given the mission of visiting a set of targets would include vehicles with differing capabilities. This paper addresses the problem of assigning each vehicle a sequence of targets to visit such that the mission is completed with the least "cost" possible given that the team of vehicles is heterogeneous. In order to simplify the problem the capabilities of each vehicle are modeled as cost to travel from one target to another. In other words, if a vehicle is particularly suited to visit a certain target, the cost for that vehicle to visit that target is low compared to the other vehicles in the team. After applying this simplification, the problem can be posed as an instance of the combinatorial problem called the Heterogeneous Travelling Salesman Problem (HTSP). This paper presents a transformation of a Heterogenous, Multiple Depot, Multiple Traveling Salesman Problem (HMDMTSP) into a single, Asymmetric, Traveling Salesman Problem (ATSP). As a result, algorithms available for the single salesman problem can be used to solve the HMDMTSP. To show the effectiveness of the transformation, the well known Lin-Kernighan-Helsgaun heuristic was applied to the transformed ATSP. Computational results show that good quality solutions can be obtained for the HMDMTSP relatively fast. Additional complications to the sequencing problem come in the form of precedence constraints which prescribe a partial order in which nodes must be visited. In this context the sequencing problem was studied seperately using the Linear Program (LP) relaxation of a Mixed Integer Linear Program (MILP) formulation of the combinatorial problem known as the "Precedence Constrained Asymmetric Travelling Salesman Problem" (PCATSP).