UNDERSTANDING CHASSIS INPUTS FROM THE REAR SUSPENSION OF A SNOWMOBILE

Today’s snowmobile industry faces great challenges in the field of noise & vibration. The area of main concern is the pass-by noise restriction defined by the Society of Automotive Engineers (SAE) test standard J192, with a maximum sound pressure level of 78 dB(A) being required by many states and national parks. To continue meet or beat this requirement without effecting machine performance, a deeper understanding of the sound transfer paths is required. This thesis examines the transfer paths created by the tunnel, rear suspension, drive shaft, and rubber composite track, with the primary source being suspension input through the ground. Using a combination of field experiments and analytical modeling, perspective was gained on which suspension and drive elements create the primary transfer paths. With further understanding of these paths, industry can tailor and fine-tune the approaches taken in to control overall noise output.

Modeling contaminant behavior in Lake Superior : a comparison of PCBs, PBDEs, and mercury

A mass‐balance model for Lake Superior was applied to polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and mercury to determine the major routes of entry and the major mechanisms of loss from this ecosystem as well as the time required for each contaminant class to approach steady state. A two‐box model (water column, surface sediments) incorporating seasonally adjusted environmental parameters was used. Both numerical (forward Euler) and analytical solutions were employed and compared. For validation, the model was compared with current and historical concentrations and fluxes in the lake and sediments. Results for PCBs were similar to prior work showing that air‐water exchange is the most rapid input and loss process. The model indicates that mercury behaves similarly to a moderately‐chlorinated PCB, with air‐water exchange being a relatively rapid input and loss process. Modeled accumulation fluxes of PBDEs in sediments agreed with measured values reported in the literature. Wet deposition rates were about three times greater than dry particulate deposition rates for PBDEs. Gas deposition was an important process for tri‐ and tetra‐BDEs (BDEs 28 and 47), but not for higher‐brominated BDEs. Sediment burial was the dominant loss mechanism for most of the PBDE congeners while volatilization was still significant for tri‐ and tetra‐BDEs. Because volatilization is a relatively rapid loss process for both mercury and the most abundant PCBs (tri‐ through penta‐), the model predicts that similar times (from 2 ‐ 10 yr) are required for the compounds to approach steady state in the lake. The model predicts that if inputs of Hg(II) to the lake decrease in the future then concentrations of mercury in the lake will decrease at a rate similar to the historical decline in PCB concentrations following the ban on production and most uses in the U.S. In contrast, PBDEs are likely to respond more slowly if atmospheric concentrations are reduced in the future because loss by volatilization is a much slower process for PBDEs, leading to lesser overall loss rates for PBDEs in comparison to PCBs and mercury. Uncertainties in the chemical degradation rates and partitioning constants of PBDEs are the largest source of uncertainty in the modeled times to steady‐state for this class of chemicals. The modeled organic PBT loading rates are sensitive to uncertainties in scavenging efficiencies by rain and snow, dry deposition velocity, watershed runoff concentrations, and uncertainties in air‐water exchange such as the effect of atmospheric stability.

Parametric combustion modeling for ethanol-gasoline fuelled spark ignition engines

Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.

Transformer modeling ATP : internal faults & high-frequency discretization

Power transformers are key components of the power grid and are also one of the most subjected to a variety of power system transients. The failure of a large transformer can cause severe monetary losses to a utility, thus adequate protection schemes are of great importance to avoid transformer damage and maximize the continuity of service. Computer modeling can be used as an efficient tool to improve the reliability of a transformer protective relay application. Unfortunately, transformer models presently available in commercial software lack completeness in the representation of several aspects such as internal winding faults, which is a common cause of transformer failure. It is also important to adequately represent the transformer at frequencies higher than the power frequency for a more accurate simulation of switching transients since these are a well known cause for the unwanted tripping of protective relays. This work develops new capabilities for the Hybrid Transformer Model (XFMR) implemented in ATPDraw to allow the representation of internal winding faults and slow-front transients up to 10 kHz. The new model can be developed using any of two sources of information: 1) test report data and 2) design data. When only test-report data is available, a higher-order leakage inductance matrix is created from standard measurements. If design information is available, a Finite Element Model is created to calculate the leakage parameters for the higher-order model. An analytical model is also implemented as an alternative to FEM modeling. Measurements on 15-kVA 240?/208Y V and 500-kVA 11430Y/235Y V distribution transformers were performed to validate the model. A transformer model that is valid for simulations for frequencies above the power frequency was developed after continuing the division of windings into multiple sections and including a higher-order capacitance matrix. Frequency-scan laboratory measurements were used to benchmark the simulations. Finally, a stability analysis of the higher-order model was made by analyzing the trapezoidal rule for numerical integration as used in ATP. Numerical damping was also added to suppress oscillations locally when discontinuities occurred in the solution. A maximum error magnitude of 7.84% was encountered in the simulated currents for different turn-to-ground and turn-to-turn faults. The FEM approach provided the most accurate means to determine the leakage parameters for the ATP model. The higher-order model was found to reproduce the short-circuit impedance acceptably up to about 10 kHz and the behavior at the first anti-resonant frequency was better matched with the measurements.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

COMBUSTION INITIATION BY ELECTRICAL-DISCHARGE-INDUCED PLASMA IN LEAN AND DILUTE METHANE-AIR MIXTURE: EXPERIMENTAL AND MODELING INVESTIGATION

This dissertation represents experimental and numerical investigations of combustion initiation trigged by electrical-discharge-induced plasma within lean and dilute methane air mixture. This research topic is of interest due to its potential to further promote the understanding and prediction of spark ignition quality in high efficiency gasoline engines, which operate with lean and dilute fuel-air mixture. It is specified in this dissertation that the plasma to flame transition is the key process during the spark ignition event, yet it is also the most complicated and least understood procedure. Therefore the investigation is focused on the overlapped periods when plasma and flame both exists in the system. Experimental study is divided into two parts. Experiments in Part I focuses on the flame kernel resulting from the electrical discharge. A number of external factors are found to affect the growth of the flame kernel, resulting in complex correlations between discharge and flame kernel. Heat loss from the flame kernel to code ambient is found to be a dominant factor that quenches the flame kernel. Another experimental focus is on the plasma channel. Electrical discharges into gases induce intense and highly transient plasma. Detailed observation of the size and contents of the discharge-induced plasma channel is performed. Given the complex correlation and the multi-discipline physical/chemical processes involved in the plasma-flame transition, the modeling principle is taken to reproduce detailed transitions numerically with minimum analytical assumptions. Detailed measurement obtained from experimental work facilitates the more accurate description of initial reaction conditions. The novel and unique spark source considering both energy and species deposition is defined in a justified manner, which is the key feature of this Ignition by Plasma (IBP) model. The results of numerical simulation are intuitive and the potential of numerical simulation to better resolve the complex spark ignition mechanism is presented. Meanwhile, imperfections of the IBP model and numerical simulation have been specified and will address future attentions.

Development of measurement and modeling techniques to quantify atmospheric deposition of persistent, bioaccumulative and toxic chemicals in the Great Lakes

Measurement and modeling techniques were developed to improve over-water gaseous air-water exchange measurements for persistent bioaccumulative and toxic chemicals (PBTs). Analytical methods were applied to atmospheric measurements of hexachlorobenzene (HCB), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). Additionally, the sampling and analytical methods are well suited to study semivolatile organic compounds (SOCs) in air with applications related to secondary organic aerosol formation, urban, and indoor air quality. A novel gas-phase cleanup method is described for use with thermal desorption methods for analysis of atmospheric SOCs using multicapillary denuders. The cleanup selectively removed hydrogen-bonding chemicals from samples, including much of the background matrix of oxidized organic compounds in ambient air, and thereby improved precision and method detection limits for nonpolar analytes. A model is presented that predicts gas collection efficiency and particle collection artifact for SOCs in multicapillary denuders using polydimethylsiloxane (PDMS) sorbent. An approach is presented to estimate the equilibrium PDMS-gas partition coefficient (Kpdms) from an Abraham solvation parameter model for any SOC. A high flow rate (300 L min-1) multicapillary denuder was designed for measurement of trace atmospheric SOCs. Overall method precision and detection limits were determined using field duplicates and compared to the conventional high-volume sampler method. The high-flow denuder is an alternative to high-volume or passive samplers when separation of gas and particle-associated SOCs upstream of a filter and short sample collection time are advantageous. A Lagrangian internal boundary layer transport exchange (IBLTE) Model is described. The model predicts the near-surface variation in several quantities with fetch in coastal, offshore flow: 1) modification in potential temperature and gas mixing ratio, 2) surface fluxes of sensible heat, water vapor, and trace gases using the NOAA COARE Bulk Algorithm and Gas Transfer Model, 3) vertical gradients in potential temperature and mixing ratio. The model was applied to interpret micrometeorological measurements of air-water exchange flux of HCB and several PCB congeners in Lake Superior. The IBLTE Model can be applied to any scalar, including water vapor, carbon dioxide, dimethyl sulfide, and other scalar quantities of interest with respect to hydrology, climate, and ecosystem science.