Characteristics of Water-in-Diesel Emulsions in a Single Cylinder Compression Ignition Engine

The objective of this project was to develop both engine performance and emission profiles for two test fuels — a 6% water-in-diesel oil emulsion (DOE-6) fuel and a neat diesel (D100) fuel. The testing was performed on a single cylinder, direct-injection, water-cooled diesel engine coupled to an eddy current dynamometer. Output parameters of the engine were used to calculate Brake Specific Fuel Consumption (BSFC) and Engine Efficiency (η) for each test fuel. DOE-6 fuels generated a 24% reduction in NOX and a 42% reduction in Carbon Monoxide emissions over the tested operating conditions. DOE-6 fuels presented higher ignition delays — between 1°-4°, yielded 1%–12% lower peak cylinder pressures and produced up to 5.5% lower exhaust temperatures. Brake Specific Fuel consumption increased by 6.6% for the DOE-6 fuels as compared to the D100 fuels. This project is the first research done by a New Zealand academic institution on water-in-diesel emulsion fuels.

A Web-Accessible Robotics Monitoring System Powered by a Thermoelectric Generator Connected to a Battery

In small source power generation scenarios in industrial or remote settings a viable small electrical supply for security and monitoring systems is often problematic due to the variability of the energy sources and the stability of the power generated. These small scale systems lack the advantages of a larger power grid. Therefore peak power requirements can be beyond the power generator necessitating energy storage such as batteries. The authors have developed and documented a reliable thermoelectric generator and a test bed. The generator was combined with a battery in order to meet peak power requirements beyond the unassisted range of the generator. This paper presents a test case result with the thermoelectric generator powering a complete web accessible mobile robot system. The robot system can be used for monitoring, physical manipulation of the environment, routine maintenance and in emergencies.

Representing the Water-Energy Nexus With Decision Matrices

The global water nexus is still in the formative stages as a area of study. The needs are mostly clear: people need adequate water for drinking, for growing food, for cooling steam-based power plants, and for sustaining the natural habitats that keep the carbon and hydrologic cycles functioning properly. What has emerged is a growing awareness of how finite the earth’s water resources are and how this creates a complex set of interconnected challenges in both developed and developing nations. What has also emerged are predictions with increasing urgency for water and energy crises in the next 20–50 years, especially if these concerns are left unaddressed. The Water-Nexus is not new, but its emerging importance now is driven primarily by population growth, climate change, and our growing awareness of societal impact on ecosystems. Providing energy for buildings, homes, and transportation is an increasingly difficult task for the growing population and aging infrastructure. Most individual issues within the Water-Energy Nexus are fairly well known with quantifiable water impacts. What is lacking is a clear representation of the Nexus relationships that show how changes in one sector impact another. What is needed is a compact way to represent the interrelationships that provide both insight and perspective on how much influence one proposed change has compared to another. Such an understanding should surface the most strategic, viable methods for simultaneously meeting water and energy needs while being a good steward of finances and natural resources. We propose the use of decision matrices from engineering design to represent the interconnected relationships that form the Water-Energy Nexus. The customers in this case are water-centric stakeholders such as government and corporate decision makers, educators, and water-oriented development agencies. Both quantitative and qualitative research methods are used to integrate the nexus topics into the decision matrix. Both positive and negative correlations in water impacts are indicated with their relative level of influence. Common units are used when possible to quantify water consumption or savings. Decision matrices are presented for transportation fuels and utility power generation. The transportation fuels matrix includes evaluation criteria for water impact, sustainability, convenience, emissions, public opinion, and geographic considerations. The utility power decision matrix has similar evaluation criteria except capacity factor is considered instead of convenience. These criteria are intended to aid policy makers in strategically navigating the legislative and policy generation process to emphasize or reduce emphasis on different fuel types. Recommendations are provided for strategic, viable methods to mitigate future effects of the Water-Energy crisis.

A Multilevel Optimization Method for the Design and Operation of Stand-Alone Hybrid Renewable Energy Systems for Multiple Remote Communities

Recently, there has been increased interest in designing stand-alone Hybrid Renewable Energy Systems (HRES) for remote communities. Several methodologies have been proposed to tackle the design optimization problem, to develop strategies for optimal operation/dispatch, or to address both problems concurrently. So far, however, these methods have been developed only for specific communities or system configurations (e.g., wind-diesel; PV-diesel). In this study, we propose a multilevel design optimization method that considers both optimal component selection and dispatch strategy that can be applied to any community regardless of the available renewable resources, thus overcoming the limitations of previous studies. The new approach considers a wide range of renewable and non-renewable energy technologies, a database of commercially available components, and leverages state-of-the-art methods for solving each optimization subproblem. The novel algorithm was evaluated with a set of meteorological conditions that emulate different remote communities. In addition, two pricing scenarios for diesel are studied to explore how the HRES design is influenced by this parameter.

Comparing High-Performance Computing Techniques for Modeling Structural Impact on Battery Cells

In this study, we have investigated feasibility of using commercial explicit finite element code LS-DYNA on massively parallel super-computing cluster for accurate modeling of structural impact on battery cells. Physical and numerical lateral impact tests have been conducted on cylindrical cells using a flat rigid drop cart in a custom-built drop test apparatus. The main component of cylindrical cell, jellyroll, is a layered spiral structure which consists of thin layers of electrodes and separator. Two numerical approaches were considered: (1) homogenized model of the cell and (2) heterogeneous (full) 3-D cell model. In the first approach, the jellyroll was considered as a homogeneous material with an effective stress-strain curve obtained through experiments. In the second model, individual layers of anode, cathode and separator were accounted for in the model, leading to extremely complex and computationally expensive finite element model. To overcome limitations of desktop computers, high-performance computing (HPC) techniques on a HPC cluster were needed in order to get the results of transient simulations in a reasonable solution time. We have compared two HPC methods used for this model is shared memory parallel processing (SMP) and massively parallel processing (MPP). Both the homogeneous and the heterogeneous models were considered for parallel simulations utilizing different number of computational nodes and cores and the performance of these models was compared. This work brings us one step closer to accurate modeling of structural impact on the entire battery pack that consists of thousands of cells.

Optimal Design of IC Engine Cooling Fins by Using Genetic Algorithm

The analysis for optimal design of an air-cooled internal combustion engine cooling fin array by using genetic algorithms (GA) is presented in this study. Genetic Algorithms are robust, stochastic search techniques which are also used for optimizing highly complex problems. In this study, the fin array is of the traditional circular fin type, which is subject to ambient convective heat transfer. The parameters (degrees of freedom) selected for the analysis include the cylinder wall thickness-to-radius ratio, fin thickness, fin length, the number of fins, and the local heat transfer coefficient. By using a single objective GA procedure, the heat transfer through the fin arrays is set as the objective function to be optimized with each parameter varied within the physical ranges. Proper population size is selected and the mutations, cross-over and selection are conducted in the GA procedure to arrive at the optimal set of parameters after a certain number of generations. The GA proves to be an effective optimization method in the thermal system component designs when the number of independent variables is large.

Mass Engine Cycle

A new thermodynamic cycle is proposed named mass engine cycle. In the proposed cycle, mass is transferred from a high mass concentration reservoir to the cycle, mass is rejected to a low mass concentration reservoir, and a net positive work is generated. This is similar to heat engine cycles where heat is transferred from a high temperature thermal reservoir (heat source) to the cycle; heat is rejected to a low temperature thermal reservoir (heat sink), and a net positive work is generated. The heat engine cycle uses heat exchangers to transfer heat between the cycle and the thermal reservoirs, while the mass engine cycle uses membrane mass exchangers which transfer mass between the cycle and the mass reservoir. These membrane mass exchangers transfer water through a semi-permeable membrane and reject other substances. The driving force for the mass transfer is the hydrostatic and osmotic pressure differences. Similar to Carnot limit of the thermal efficiency of the heat engine cycle, a theoretical limit is obtained for the proposed mass engine cycle under reversible thermodynamic conditions.

Thermodynamic Analysis and Working Fluid Optimization of a Combined ORC-VCC System Using Waste Heat From a Marine Diesel Engine

This paper examines through a thermodynamic analysis the feasibility of using waste heat from marine Diesel engines to drive a vapor compression refrigeration system. Several working fluids including propane, butane, isobutane and propylene are considered. Results showed that isobutane and Butane yield the highest performance, whereas propane and propylene yield negligible improvement compared to R134a for operating conditions considered.

Lake Michigan Water Resources Study

This paper contains an analysis of withdrawal data for North West Indiana to compute consumptive-use coefficients and to describe monthly variability of withdrawals and consumptive use. Concurrent data were available for most water-use categories from 1990 through 2008. Average monthly water withdrawals are discussed for a variety of water-use categories, and average water use per month is depicted graphically. Water quality analysis is presented and historic water quality data of Northwest Indiana, (Lake, Porter and LaPort Counties) were downloaded from USEPA website and they were examined for the trends in different water quality constituents. Individual station based analysis and regional analysis were conducted using MK Test. Water quality data indicated an improvement trend. Water withdrawals data were analyzed using regression and Artificial Neural Network (ANN) models. The ANN model performed a better forecasting while compared to a linear regression model. For most water-use categories, the summer months were those of highest withdrawal and highest consumptive use. For public supply, average monthly withdrawals ranged from 2,193 million gallons per day (Mgal/d) (February) to 3,092 Mgal/d (July). North West Indiana energy production had large increases in average monthly withdrawals in the summer months (17,551 Mgal/d in February to 26,236 Mgal/d in July, possibly because of increased electricity production in the summer, a need for additional cooling-water withdrawals when intake-water temperature is high, or use of different types of cooling methods during different times of the year. Average industrial withdrawals ranged from 31,553 Mgal/d (February) to 36,934 Mgal/d (August). The North West Indiana irrigation data showed that most withdrawals were in May through October for golf courses, nurseries, and crop irrigation. Miscellaneous water withdrawals ranged from 12.2 Mgal/d (January) to 416.3 Mgal/d (October), commercial facilities that have high water demand in Indiana are medical facilities, schools, amusement facilities, wildlife facilities, large stores, colleges, correctional institutions, and national security facilities. Consumptive use and consumptive-use coefficients were computed by two principal methods in this study: the return-flow and withdrawal method and the winter-base-rate method (WBR). The WBR method was not suitable for the industrial and miscellaneous water-use categories. The RW method was not used for public-supply facilities. The public-supply annual average consumptive-use coefficient derived by use of the WBR methods is 8 percent from 1990 to 2008 for North West Indiana; the summer average consumptive-use coefficient was considerably higher with the amount of 20 percent. The energy production annual consumptive-use coefficient was 13 percent by the WBR method, which increased to 28 percent for summer. In terms of maximum accuracy and minimal uncertainty, use of available withdrawal, return-flow, and consumptive-use data reported by facilities and data estimated from similar facilities are preferable over estimates based on data for a particular water-use category or groups of water-use categories. If monthly withdrawal, return flow, and consumptive use data are few and limited, monthly patterns described in this report may be used as a basis of estimation, but the level of uncertainty may be a greater than for the other estimation methods.

Finite Time Thermodynamics Model of an Absorption Chiller

A finite time thermodynamic model of an absorption chiller was developed. The effects of irreversibilities due to finite rate heat transfer in the heat exchangers are modeled by using the standard UA formulation with the absorber and condenser lumped as one heat exchanger. In order to match experimental data within 20%, the UA of the generator was modeled as a linear function of the heating fluid flow rate. A constant entropy production due to internal processes was included to model reduction in performance at off design conditions. The UA parameters and internal entropy production constant form a set of five fitting parameters with physical meaning. This is fewer parameters than the non-physical curve fit used in the industry standard Energy Plus model. The model was validated within 20% against data sets from two different systems.