Mission profile based optimization of a wearable power system

A Wearable Power System (WPS) is a portable power source utilized primarily to power the modern soldier’s electronic equipment. Such a system has to satisfy output power demands in the range of 20 W...200 W, specified as a 4-day mission profile and has a weight limit of 4 kg. To meet these demands, an optimization of a WPS, comprising an internal combustion (IC) engine, permanent magnetic three-phase electrical motor/generator, inverter, Li-batteries, DC-DC converters, and controller, is performed in this paper. The mechanical energy extracted from the fuel by IC engine is transferred to the generator that is used to recharge the battery and provide the power to the electrical output load. The main objectives are to select the engine, fuel and battery type, to match the weight of fuel and the number of battery cells, to find the optimal working point of engine and to minimize the system weight. To provide the second output voltage level of 14 VDC, a separate DC-DC converter is connected between the battery and the load, and optimized for the specified mission profile. A prototype of the WPS based on the optimization presented in the paper results in a total system weight of 3.9 kg and fulfils the mission profile.

Oxide Semiconductors For Organic Opto-electronic Devices

Development of transparent oxide semiconductors (TOS) from Earth-abundant materials is of great interest for cost-effective thin film device applications, such as solar cells, light emitting diodes (LEDs), touch-sensitive displays, electronic paper, and transparent thin film transistors. The need of inexpensive or high performance electrode might be even greater for organic photovoltaic (OPV), with the goal to harvest renewable energy with inexpensive, lightweight, and cost competitive materials. The natural abundance of zinc and the wide bandgap ($sim$3.3 eV) of its oxide make it an ideal candidate. In this dissertation, I have introduced various concepts on the modulations of various surface, interface and bulk opto-electronic properties of ZnO based semiconductor for charge transport, charge selectivity and optimal device performance. I have categorized transparent semiconductors into two sub groups depending upon their role in a device. Electrodes, usually 200 to 500 nm thick, optimized for good transparency and transporting the charges to the external circuit. Here, the electrical conductivity in parallel direction to thin film, i.e bulk conductivity is important. And contacts, usually 5 to 50 nm thick, are optimized in case of solar cells for providing charge selectivity and asymmetry to manipulate the built in field inside the device for charge separation and collection. Whereas in Organic LEDs (OLEDs), contacts provide optimum energy level alignment at organic oxide interface for improved charge injections. For an optimal solar cell performance, transparent electrodes are designed with maximum transparency in the region of interest to maximize the light to pass through to the absorber layer for photo-generation, plus they are designed for minimum sheet resistance for efficient charge collection and transport. As such there is need for material with high conductivity and transparency. Doping ZnO with some common elements such as B, Al, Ga, In, Ge, Si, and F result in n-type doping with increase in carriers resulting in high conductivity electrode, with better or comparable opto-electronic properties compared to current industry-standard indium tin oxide (ITO). Furthermore, improvement in mobility due to improvement on crystallographic structure also provide alternative path for high conductivity ZnO TCOs. Implementing these two aspects, various studies were done on gallium doped zinc oxide (GZO) transparent electrode, a very promising indium free electrode. The dynamics of the superimposed RF and DC power sputtering was utilized to improve the microstructure during the thin films growth, resulting in GZO electrode with conductivity greater than 4000 S/cm and transparency greater than 90 %. Similarly, various studies on research and development of Indium Zinc Tin Oxide and Indium Zinc Oxide thin films which can be applied to flexible substrates for next generation solar cells application is presented. In these new TCO systems, understanding the role of crystallographic structure ranging from poly-crystalline to amorphous phase and the influence on the charge transport and optical transparency as well as important surface passivation and surface charge transport properties. Implementation of these electrode based on ZnO on opto-electronics devices such as OLED and OPV is complicated due to chemical interaction over time with the organic layer or with ambient. The problem of inefficient charge collection/injection due to poor understanding of interface and/or bulk property of oxide electrode exists at several oxide-organic interfaces. The surface conductivity, the work function, the formation of dipoles and the band-bending at the interfacial sites can positively or negatively impact the device performance. Detailed characterization of the surface composition both before and after various chemicals treatment of various oxide electrode can therefore provide insight into optimization of device performance. Some of the work related to controlling the interfacial chemistry associated with charge transport of transparent electrodes are discussed. Thus, the role of various pre-treatment on poly-crystalline GZO electrode and amorphous indium zinc oxide (IZO) electrode is compared and contrasted. From the study, we have found that removal of defects and self passivating defects caused by accumulation of hydroxides in the surface of both poly-crystalline GZO and amorphous IZO, are critical for improving the surface conductivity and charge transport. Further insight on how these insulating and self-passivating defects cause charge accumulation and recombination in an device is discussed. With recent rapid development of bulk-heterojunction organic photovoltaics active materials, devices employing ZnO and ZnO based electrode provide air stable and cost-competitive alternatives to traditional inorganic photovoltaics. The organic light emitting diodes (OLEDs) have already been commercialized, thus to follow in the footsteps of this technology, OPV devices need further improvement in power conversion efficiency and stable materials resulting in long device lifetimes. Use of low work function metals such as Ca/Al in standard geometry do provide good electrode for electron collection, but serious problems using low work-function metal electrodes originates from the formation of non-conductive metal oxide due to oxidation resulting in rapid device failure. Hence, using low work-function, air stable, conductive metal oxides such as ZnO as electrons collecting electrode and high work-function, air stable metals such as silver for harvesting holes, has been on the rise. Devices with degenerately doped ZnO functioning as transparent conductive electrode, or as charge selective layer in a polymer/fullerene based heterojunction, present useful device structures for investigating the functional mechanisms within OPV devices and a possible pathway towards improved air-stable high efficiency devices. Furthermore, analysis of the physical properties of the ZnO layers with varying thickness, crystallographic structure, surface chemistry and grain size deposited via various techniques such as atomic layer deposition, sputtering and solution-processed ZnO with their respective OPV device performance is discussed. We find similarity and differences in electrode property for good charge injection in OLEDs and good charge collection in OPV devices very insightful in understanding physics behind device failures and successes. In general, self-passivating surface of amorphous TCOs IZO, ZTO and IZTO forms insulating layer that hinders the charge collection. Similarly, we find modulation of the carrier concentration and the mobility in electron transport layer, namely zinc oxide thin films, very important for optimizing device performance.

Particle Swarm Optimization Based Reactive Power Dispatch for Power Networks with Distributed Generation

Reactive power is critical to the operation of the power networks on both safety aspects and economic aspects. Unreasonable distribution of the reactive power would severely affect the power quality of the power networks and increases the transmission loss. Currently, the most economical and practical approach to minimizing the real power loss remains using reactive power dispatch method. Reactive power dispatch problem is nonlinear and has both equality constraints and inequality constraints. In this thesis, PSO algorithm and MATPOWER 5.1 toolbox are applied to solve the reactive power dispatch problem. PSO is a global optimization technique that is equipped with excellent searching capability. The biggest advantage of PSO is that the efficiency of PSO is less sensitive to the complexity of the objective function. MATPOWER 5.1 is an open source MATLAB toolbox focusing on solving the power flow problems. The benefit of MATPOWER is that its code can be easily used and modified. The proposed method in this thesis minimizes the real power loss in a practical power system and determines the optimal placement of a new installed DG. IEEE 14 bus system is used to evaluate the performance. Test results show the effectiveness of the proposed method.

Optimization of traffic signal controls within equilibrium route choice models : final report to Illinois Department of Transpotation/

Cover title.

National signal timing optimization project : summary evaluation report /

"May 1982."

Optimization of pipeline transport for CO2 sequestration

Coal fired power generation will continue to provide energy to the world for the foreseeable future. However, this energy use is a significant contributor to increased atmospheric CO2 concentration and, hence, global warming. Capture and disposal Of CO2 has received increased R&D attention in the last decade as the technology promises to be the most cost effective for large scale reductions in CO2 emissions. This paper addresses CO2 transport via pipeline from capture site to disposal site, in terms of system optimization, energy efficiency and overall economics. Technically, CO2 can be transported through pipelines in the form of a gas, a supercritical. fluid or in the subcooled liquid state. Operationally, most CO2 pipelines used for enhanced oil recovery transport CO2 as a supercritical fluid. In this paper, supercritical fluid and subcooled liquid transport are examined and compared, including their impacts on energy efficiency and cost. Using a commercially available process simulator, ASPEN PLUS 10.1, the results show that subcooled liquid transport maximizes the energy efficiency and minimizes the Cost Of CO2 transport over long distances under both isothermal and adiabatic conditions. Pipeline transport of subcooled liquid CO2 can be ideally used in areas of cold climate or by burying and insulating the pipeline. In very warm climates, periodic refrigeration to cool the CO2 below its critical point of 31.1 degrees C, may prove economical. Simulations have been used to determine the maximum safe pipeline distances to subsequent booster stations as a function of inlet pressure, environmental temperature and ground level heat flux conditions. (c) 2005 Published by Elsevier Ltd.

Optimization of microcavity OLED by varying the thickness of multi-layered mirror

We optimized the emission efficiency from a microcavity OLEDs consisting of widely used organic materials, N,N'-di(naphthalene-1-yl)-N,N'-diphenylbenzidine (NPB) as a hole transport layer and tris (8-hydroxyquinoline) (Alq(3)) as emitting and electron transporting layer. LiF/Al was considered as a cathode, while metallic Ag anode was used. TiO2 and Al2O3 layers were stacked on top of the cathode to alter the properties of the top mirror. The electroluminescence emission spectra, electric field distribution inside the device, carrier density, recombination rate and exciton density were calculated as a function of the position of the emission layer. The results show that for certain TiO2 and Al2O3 layer thicknesses, light output is enhanced as a result of the increase in both the reflectance and transmittance of the top mirror. Once the optimum structure has been determined, the microcavity OLED devices can be fabricated and characterized, and comparisons between experiments and theory can be made.

Multiobjective design optimization of IGBT power modules considering power cycling and thermal cycling

Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.

Surrogate-based analysis and optimization for the design of heat sinks with jet impingement

Heat sinks are widely used for cooling electronic devices and systems. Their thermal performance is usually determined by the material, shape, and size of the heat sink. With the assistance of computational fluid dynamics (CFD) and surrogate-based optimization, heat sinks can be designed and optimized to achieve a high level of performance. In this paper, the design and optimization of a plate-fin-type heat sink cooled by impingement jet is presented. The flow and thermal fields are simulated using the CFD simulation; the thermal resistance of the heat sink is then estimated. A Kriging surrogate model is developed to approximate the objective function (thermal resistance) as a function of design variables. Surrogate-based optimization is implemented by adaptively adding infill points based on an integrated strategy of the minimum value, the maximum mean square error approach, and the expected improvement approaches. The results show the influence of design variables on the thermal resistance and give the optimal heat sink with lowest thermal resistance for given jet impingement conditions.

The construction and optimization of an ion mobility spectrometer for the analysis of explosives and drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs.^ In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug.^ Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). ^ The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.^

Design Optimization of Submerged Jet Nozzles for Enhanced Mixing

The purpose of this thesis was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using a Computational Fluid Dynamics (CFD) software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was created based on the shear stress values obtained from 112 simulated designs. A multi-objective optimization software utilized the response surface to generate designs with the best combination of parameters to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters achieved larger shear stress values over a commercially available design.

Modified continuous ant colony algorithm for function optimization

Many classical as well as modern optimization techniques exist. One such modern method belonging to the field of swarm intelligence is termed ant colony optimization. This relatively new concept in optimization involves the use of artificial ants and is based on real ant behavior inspired by the way ants search for food. In this thesis, a novel ant colony optimization technique for continuous domains was developed. The goal was to provide improvements in computing time and robustness when compared to other optimization algorithms. Optimization function spaces can have extreme topologies and are therefore difficult to optimize. The proposed method effectively searched the domain and solved difficult single-objective optimization problems. The developed algorithm was run for numerous classic test cases for both single and multi-objective problems. The results demonstrate that the method is robust, stable, and that the number of objective function evaluations is comparable to other optimization algorithms.

Optimization of waiting time at toll plazas

Toll plazas have several toll payment types such as manual, automatic coin machines, electronic and mixed lanes. In places with high traffic flow, the presence of toll plaza causes a lot of traffic congestion; this creates a bottleneck for the traffic flow, unless the correct mix of payment types is in operation. The objective of this research is to determine the optimal lane configuration for the mix of the methods of payment so that the waiting time in the queue at the toll plaza is minimized. A queuing model representing the toll plaza system and a nonlinear integer program have been developed to determine the optimal mix. The numerical results show that the waiting time can be decreased at the toll plaza by changing the lane configuration. For the case study developed an improvement in the waiting time as high as 96.37 percent was noticed during the morning peak hour.

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models.