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A relatively simple subset of nanotechnology - nanofluids - can be obtained by adding nanoparticles to conventional base fluids. The promise of these fluids stems from the fact that relatively low particle loadings (typically <1% volume fractions) can significantly change the properties of the base fluid. This research

A relatively simple subset of nanotechnology - nanofluids - can be obtained by adding nanoparticles to conventional base fluids. The promise of these fluids stems from the fact that relatively low particle loadings (typically <1% volume fractions) can significantly change the properties of the base fluid. This research explores how low volume fraction nanofluids, composed of common base-fluids, interact with light energy. Comparative experimentation and modeling reveals that absorbing light volumetrically (i.e. in the depth of the fluid) is fundamentally different from surface-based absorption. Depending on the particle material, size, shape, and volume fraction, a fluid can be changed from being mostly transparent to sunlight (in the case of water, alcohols, oils, and glycols) to being a very efficient volumetric absorber of sunlight. This research also visualizes, under high levels of irradiation, how nanofluids undergo interesting, localized phase change phenomena. For this, images were taken of bubble formation and boiling in aqueous nanofluids heated by a hot wire and by a laser. Infrared thermography was also used to quantify this phenomenon. Overall, though, this research reveals the possibility for novel solar collectors in which the working fluid directly absorbs light energy and undergoes phase change in a single step. Modeling results indicate that these improvements can increase a solar thermal receiver's efficiency by up to 10%.
ContributorsTaylor, Robert (Author) / Phelan, Patrick E (Thesis advisor) / Adrian, Ronald (Committee member) / Trimble, Steve (Committee member) / Posner, Jonathan (Committee member) / Maracas, George (Committee member) / Arizona State University (Publisher)
Created2011
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Description
A good production schedule in a semiconductor back-end facility is critical for the on time delivery of customer orders. Compared to the front-end process that is dominated by re-entrant product flows, the back-end process is linear and therefore more suitable for scheduling. However, the production scheduling of the back-end process

A good production schedule in a semiconductor back-end facility is critical for the on time delivery of customer orders. Compared to the front-end process that is dominated by re-entrant product flows, the back-end process is linear and therefore more suitable for scheduling. However, the production scheduling of the back-end process is still very difficult due to the wide product mix, large number of parallel machines, product family related setups, machine-product qualification, and weekly demand consisting of thousands of lots. In this research, a novel mixed-integer-linear-programming (MILP) model is proposed for the batch production scheduling of a semiconductor back-end facility. In the MILP formulation, the manufacturing process is modeled as a flexible flow line with bottleneck stages, unrelated parallel machines, product family related sequence-independent setups, and product-machine qualification considerations. However, this MILP formulation is difficult to solve for real size problem instances. In a semiconductor back-end facility, production scheduling usually needs to be done every day while considering updated demand forecast for a medium term planning horizon. Due to the limitation on the solvable size of the MILP model, a deterministic scheduling system (DSS), consisting of an optimizer and a scheduler, is proposed to provide sub-optimal solutions in a short time for real size problem instances. The optimizer generates a tentative production plan. Then the scheduler sequences each lot on each individual machine according to the tentative production plan and scheduling rules. Customized factory rules and additional resource constraints are included in the DSS, such as preventive maintenance schedule, setup crew availability, and carrier limitations. Small problem instances are randomly generated to compare the performances of the MILP model and the deterministic scheduling system. Then experimental design is applied to understand the behavior of the DSS and identify the best configuration of the DSS under different demand scenarios. Product-machine qualification decisions have long-term and significant impact on production scheduling. A robust product-machine qualification matrix is critical for meeting demand when demand quantity or mix varies. In the second part of this research, a stochastic mixed integer programming model is proposed to balance the tradeoff between current machine qualification costs and future backorder costs with uncertain demand. The L-shaped method and acceleration techniques are proposed to solve the stochastic model. Computational results are provided to compare the performance of different solution methods.
ContributorsFu, Mengying (Author) / Askin, Ronald G. (Thesis advisor) / Zhang, Muhong (Thesis advisor) / Fowler, John W (Committee member) / Pan, Rong (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog

The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Plasmon resonance in nanoscale metallic structures has shown its ability to concentrate electromagnetic energy into sub-wavelength volumes. Metal nanostructures exhibit a high extinction coefficient in the visible and near infrared spectrum due to their large absorption and scattering cross sections corresponding to their surface plasmon resonance. Hence, they can serve

Plasmon resonance in nanoscale metallic structures has shown its ability to concentrate electromagnetic energy into sub-wavelength volumes. Metal nanostructures exhibit a high extinction coefficient in the visible and near infrared spectrum due to their large absorption and scattering cross sections corresponding to their surface plasmon resonance. Hence, they can serve as an attractive candidate for solar energy conversion. Recent papers have showed that dielectric core/metallic shell nanoparticles yielded a plasmon resonance wavelength tunable from visible to infrared by changing the ratio of core radius to the total radius. Therefore it is interesting to develop a dispersion of core-shell multifunctional nanoparticles capable of dynamically changing their volume ratio and thus their spectral radiative properties. Nanoparticle suspensions (nanofluids) are known to offer a variety of benefits for thermal transport and energy conversion. Nanofluids have been proven to increase the efficiency of the photo-thermal energy conversion process in direct solar absorption collectors (DAC). Combining these two cutting-edge technologies enables the use of core-shell nanoparticles to control the spectral and radiative properties of plasmonic nanofluids in order to efficiently harvest and convert solar energy. Plasmonic nanofluids that have strong energy concentrating capacity and spectral selectivity can be used in many high-temperature energy systems where radiative heat transport is essential. In this thesis,the surface plasmon resonance effect and the wavelength tuning ranges for different metallic shell nanoparticles are investigated, the solar-weighted efficiencies of corresponding core-shell nanoparticle suspensions are explored, and a quantitative study of core-shell nanoparticle suspensions in a DAC system is provided. Using core-shell nanoparticle dispersions, it is possible to create efficient spectral solar absorption fluids and design materials for applications which require variable spectral absorption or scattering.
ContributorsLv, Wei (Author) / Phelan, Patrick E (Thesis advisor) / Dai, Lenore (Committee member) / Prasher, Ravi (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Optimization of surgical operations is a challenging managerial problem for surgical suite directors. This dissertation presents modeling and solution techniques for operating room (OR) planning and scheduling problems. First, several sequencing and patient appointment time setting heuristics are proposed for scheduling an Outpatient Procedure Center. A discrete event simulation model

Optimization of surgical operations is a challenging managerial problem for surgical suite directors. This dissertation presents modeling and solution techniques for operating room (OR) planning and scheduling problems. First, several sequencing and patient appointment time setting heuristics are proposed for scheduling an Outpatient Procedure Center. A discrete event simulation model is used to evaluate how scheduling heuristics perform with respect to the competing criteria of expected patient waiting time and expected surgical suite overtime for a single day compared to current practice. Next, a bi-criteria Genetic Algorithm is used to determine if better solutions can be obtained for this single day scheduling problem. The efficacy of the bi-criteria Genetic Algorithm, when surgeries are allowed to be moved to other days, is investigated. Numerical experiments based on real data from a large health care provider are presented. The analysis provides insight into the best scheduling heuristics, and the tradeoff between patient and health care provider based criteria. Second, a multi-stage stochastic mixed integer programming formulation for the allocation of surgeries to ORs over a finite planning horizon is studied. The demand for surgery and surgical duration are random variables. The objective is to minimize two competing criteria: expected surgery cancellations and OR overtime. A decomposition method, Progressive Hedging, is implemented to find near optimal surgery plans. Finally, properties of the model are discussed and methods are proposed to improve the performance of the algorithm based on the special structure of the model. It is found simple rules can improve schedules used in practice. Sequencing surgeries from the longest to shortest mean duration causes high expected overtime, and should be avoided, while sequencing from the shortest to longest mean duration performed quite well in our experiments. Expending greater computational effort with more sophisticated optimization methods does not lead to substantial improvements. However, controlling daily procedure mix may achieve substantial improvements in performance. A novel stochastic programming model for a dynamic surgery planning problem is proposed in the dissertation. The efficacy of the progressive hedging algorithm is investigated. It is found there is a significant correlation between the performance of the algorithm and type and number of scenario bundles in a problem instance. The computational time spent to solve scenario subproblems is among the most significant factors that impact the performance of the algorithm. The quality of the solutions can be improved by detecting and preventing cyclical behaviors.
ContributorsGul, Serhat (Author) / Fowler, John W. (Thesis advisor) / Denton, Brian T. (Thesis advisor) / Wu, Teresa (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2010
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Description
The colloidal solutions of nanoparticles have been seen as promising solutions forheat transfer enhancement. Additionally, there has been an accelerated study on the effects of ultrasound on heat transfer enhancement in recent years. A few authors have studied the combined impact of Al2O3 nanofluids and ultrasound on mini channels. This study focused on

The colloidal solutions of nanoparticles have been seen as promising solutions forheat transfer enhancement. Additionally, there has been an accelerated study on the effects of ultrasound on heat transfer enhancement in recent years. A few authors have studied the combined impact of Al2O3 nanofluids and ultrasound on mini channels. This study focused on the combined effects of Al2O3 nanofluids and ultrasound on heat transfer enhancement in a circular mini channel heat sink. Two concentrations of Al2O3-water nanofluids, i.e., 0.5% and 1%, were used for the experiments in addition to two heat input conditions, namely 40 W and 50 W providing a constant heat flux of 25000 W m-2 and 31250 W m-2 respectively. The effect on the nanofluids using 5 W ultrasound was analyzed. Experimental observations show that the usage of ultrasound increased the heat transfer coefficient. The heat transfer coefficient also increased with increasing nanoparticle concentration and high heat flux. The average heat transfer coefficient enhancement for 0.5% and 1% nanofluid due to increased heat flux in the absence of ultrasound was 12.4% and 9% respectively. At a constant heat input of 40 W, the induction of ultrasound enhanced the heat transfer coefficient by 22.8% and 23.9% for 0.5% and 1% nanofluid respectively. Similarly, for a constant heat input of 50 W, the usage of ultrasound enhanced the heat transfer coefficient by 19.8% and 22.9% for 0.5% and 1% nanofluid respectively Also, interesting findings are reported with low heat input with ultrasound vs. high heat input without ultrasound (i.e., 40 W with US vs. 50 W without US). The heat transfer coefficient and Nusselt number for 0.5% and 1% concentrations was enhanced by 9.2% and 13.6%, respectively. Furthermore, for fixed heat input powers of 40 W and 50 W, increasing the concentration from 0.5% to 1% along with ultrasound yielded an average enhancement in Nu of 38.3% and 32.4% respectively
ContributorsMastoi, Faisal Ali (Author) / Phelan, Patrick E (Thesis advisor) / Milcarek, Ryan (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The residential building sector accounts for more than 26% of the global energy consumption and 17% of global CO2 emissions. Due to the low cost of electricity in Kuwait and increase of population, Kuwaiti electricity consumption tripled during the past 30 years and is expected to increase by 20% by

The residential building sector accounts for more than 26% of the global energy consumption and 17% of global CO2 emissions. Due to the low cost of electricity in Kuwait and increase of population, Kuwaiti electricity consumption tripled during the past 30 years and is expected to increase by 20% by 2027. In this dissertation, a framework is developed to assess energy savings techniques to help policy-makers make educated decisions. The Kuwait residential energy outlook is studied by modeling the baseline energy consumption and the diffusion of energy conservation measures (ECMs) to identify the impacts on household energy consumption and CO2 emissions.



The energy resources and power generation in Kuwait were studied. The characteristics of the residential buildings along with energy codes of practice were investigated and four building archetypes were developed. Moreover, a baseline of end-use electricity consumption and demand was developed. Furthermore, the baseline energy consumption and demand were projected till 2040. It was found that by 2040, energy consumption would double with most of the usage being from AC. While with lighting, there is a negligible increase in consumption due to a projected shift towards more efficient lighting. Peak demand loads are expected to increase by an average growth rate of 2.9% per year. Moreover, the diffusion of different ECMs in the residential sector was modeled through four diffusion scenarios to estimate ECM adoption rates. ECMs’ impact on CO2 emissions and energy consumption of residential buildings in Kuwait was evaluated and the cost of conserved energy (CCE) and annual energy savings for each measure was calculated. AC ECMs exhibited the highest cumulative savings, whereas lighting ECMs showed an immediate energy impact. None of the ECMs in the study were cost effective due to the high subsidy rate (95%), therefore, the impact of ECMs at different subsidy and rebate rates was studied. At 75% subsidized utility price and 40% rebate only on appliances, most of ECMs will be cost effective with high energy savings. Moreover, by imposing charges of $35/ton of CO2, most ECMs will be cost effective.
ContributorsAlajmi, Turki (Author) / Phelan, Patrick E (Thesis advisor) / Kaloush, Kamil (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Liping (Committee member) / Hajiah, Ali (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Just for a moment! Imagine you live in Arizona without air-conditioning systems!

Air-conditioning and refrigeration systems are one of the most crucial systems in anyone’s house and car these days. Energy resources are becoming more scarce and expensive. Most of the currently used refrigerants have brought an international concern about global

Just for a moment! Imagine you live in Arizona without air-conditioning systems!

Air-conditioning and refrigeration systems are one of the most crucial systems in anyone’s house and car these days. Energy resources are becoming more scarce and expensive. Most of the currently used refrigerants have brought an international concern about global warming. The search for more efficient cooling/refrigeration systems with environmental friendly refrigerants has become more and more important so as to reduce greenhouse gas emissions and ensure sustainable and affordable energy systems. The most widely used air-conditioning and refrigeration system, based on the vapor compression cycle, is driven by converting electricity into mechanical work which is a high quality type of energy. However, these systems can instead be possibly driven by heat, be made solid-state (i.e., thermoelectric cooling), consist entirely of a gaseous working fluid (i.e., reverse Brayton cycle), etc. This research explores several thermally driven cooling systems in order to understand and further overcome some of the major drawbacks associated with their performance as well as their high capital costs. In the second chapter, we investigate the opportunities for integrating single- and double-stage ammonia-water (NH3–H2O) absorption refrigeration systems with multi-effect distillation (MED) via cascade of rejected heat for large-scale plants. Similarly, in the third chapter, we explore a new polygeneration cooling-power cycle’s performance based on Rankine, reverse Brayton, ejector, and liquid desiccant cycles to produce power, cooling, and possibly fresh water for various configurations. Different configurations are considered from an energy perspective and are compared to stand-alone systems. In the last chapter, a new simple, inexpensive, scalable, environmentally friendly cooling system based on an adsorption heat pump system and evacuated tube solar collector is experimentally and theoretically studied. The system is destined as a small-scale system to harness solar radiation to provide a cooling effect directly in one system.
ContributorsAlelyani, Sami M (Author) / Phelan, Patrick E (Thesis advisor) / Wang, Liping (Committee member) / Stechel, Ellen B (Committee member) / Calhoun, Ronald J (Committee member) / Alalili, Ali R (Committee member) / Arizona State University (Publisher)
Created2018
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Waste heat energy conversion remains an inviting subject for research, given the renewed emphasis on energy efficiency and carbon emissions reduction. Solid-state thermoelectric devices have been widely investigated, but their practical application remains challenging because of cost and the inability to fabricate them in geometries that are easily compatible

Waste heat energy conversion remains an inviting subject for research, given the renewed emphasis on energy efficiency and carbon emissions reduction. Solid-state thermoelectric devices have been widely investigated, but their practical application remains challenging because of cost and the inability to fabricate them in geometries that are easily compatible with heat sources. An intriguing alternative to solid-state thermoelectric devices is thermogalvanic cells, which include a generally liquid electrolyte that permits the transport of ions. Thermogalvanic cells have long been known in the electrochemistry community, but have not received much attention from the thermal transport community. This is surprising given that their performance is highly dependent on controlling both thermal and mass (ionic) transport. This research will focus on a research project, which is an interdisciplinary collaboration between mechanical engineering (i.e. thermal transport) and chemistry, and is a largely experimental effort aimed at improving fundamental understanding of thermogalvanic systems. The first part will discuss how a simple utilization of natural convection within the cell doubles the maximum power output of the cell. In the second part of the research, some of the results from the previous part will be applied in a feasibility study of incorporating thermogalvanic waste heat recovery systems into automobiles. Finally, a new approach to enhance Seebeck coefficient by tuning the configurational entropy of a mixed-ligand complex formation of copper sulfate aqueous electrolytes will be presented. Ultimately, a summary of these results as well as possible future work that can be formed from these efforts is discussed.
ContributorsGunawan, Andrey (Author) / Phelan, Patrick E (Thesis advisor) / Buttry, Daniel A (Committee member) / Mujica, Vladimiro (Committee member) / Chan, Candace K. (Committee member) / Wang, Robert Y (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling

Traditional deterministic reserve requirements rely on ad-hoc, rule of thumb methods to determine adequate reserve in order to ensure a reliable unit commitment. Since congestion and uncertainties exist in the system, both the quantity and the location of reserves are essential to ensure system reliability and market efficiency. The modeling of operating reserves in the existing deterministic reserve requirements acquire the operating reserves on a zonal basis and do not fully capture the impact of congestion. The purpose of a reserve zone is to ensure that operating reserves are spread across the network. Operating reserves are shared inside each reserve zone, but intra-zonal congestion may block the deliverability of operating reserves within a zone. Thus, improving reserve policies such as reserve zones may improve the location and deliverability of reserve.

As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired.

One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones.

Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies.
ContributorsWang, Fengyu (Author) / Hedman, Kory W. (Thesis advisor) / Zhang, Muhong (Committee member) / Tylavsky, Daniel J. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2015