Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

The application of 3D printing to study microfluidic architecture for 'on-chip' mixing systems for SRCD and UV spectroscopy

This paper details methodologies that have been explored for the fast proofing of on-chip architectures for Circular Dichroism techniques. Flow-cell devices fabricated from UV transparent Quartz are used for these experiments. The complexity of flow-cell production typically results in lead times of six months from order to delivery. Only at that point can the on-chip architecture be tested empirically and any required modifications determined ready for the next six month iteration phase. By using the proposed 3D printing and PDMS moulding techniques for fast proofing on-chip architectures the optimum design can be determined within a matter of hours prior to commitment to quartz chip production.

Constructal Design of Energy Systems

This dissertation shows the use of Constructal law to find the relation between the morphing of the system configuration and the improvements in the global performance of the complex flow system. It shows that the better features of both flow and heat transfer architecture can be found and predicted by using the constructal law in energy systems. Chapter 2 shows the effect of flow configuration on the heat transfer performance of a spiral shaped pipe embedded in a cylindrical conducting volume. Several configurations were considered. The optimal spacings between the spiral turns and spire planes exist, such that the volumetric heat transfer rate is maximal. The optimized features of the heat transfer architecture are robust. Chapter 3 shows the heat transfer performance of a helically shaped pipe embedded in a cylindrical conducting volume. It shows that the optimized features of the heat transfer architecture are robust with respect to changes in several physical parameters. Chapter 4 reports analytically the formulas for effective permeability in several configurations of fissured systems, using the closed-form description of tree networks designed to provide flow access. The permeability formulas do not vary much from one tree design to the next, suggesting that similar formulas may apply to naturally fissured porous media with unknown precise details, which occur in natural reservoirs. Chapter 5 illustrates a counterflow heat exchanger consists of two plenums with a core. The results show that the overall flow and thermal resistance are lowest when the core is absent. Overall, the constructal design governs the evolution of flow configuration in nature and energy systems.

Design of Latent Thermal Energy Storage Systems

This dissertation documents the results of a theoretical and numerical study of time dependent storage of energy by melting a phase change material. The heating is provided along invading lines, which change from single-line invasion to tree-shaped invasion. Chapter 2 identifies the special design feature of distributing energy storage in time-dependent fashion on a territory, when the energy flows by fluid flow from a concentrated source to points (users) distributed equidistantly on the area. The challenge in this chapter is to determine the architecture of distributed energy storage. The chief conclusion is that the finite amount of storage material should be distributed proportionally with the distribution of the flow rate of heating agent arriving on the area. The total time needed by the source stream to ‘invade’ the area is cumulative (the sum of the storage times required at each storage site), and depends on the energy distribution paths and the sequence in which the users are served by the source stream. Chapter 3 shows theoretically that the melting process consists of two phases: “invasion” thermal diffusion along the invading line, which is followed by “consolidation” as heat diffuses perpendicularly to the invading line. This chapter also reports the duration of both phases and the evolution of the melt layer around the invading line during the two-dimensional and three-dimensional invasion. It also shows that the amount of melted material increases in time according to a curve shaped as an S. These theoretical predictions are validated by means of numerical simulations in chapter 4. This chapter also shows that the heat transfer rate density increases (i.e., the S curve becomes steeper) as the complexity and number of degrees of freedom of the structure are increased, in accord with the constructal law. The optimal geometric features of the tree structure are detailed in this chapter. Chapter 5 documents a numerical study of time-dependent melting where the heat transfer is convection dominated, unlike in chapter 3 and 4 where the melting is ruled by pure conduction. In accord with constructal design, the search is for effective heat-flow architectures. The volume-constrained improvement of the designs for heat flow begins with assuming the simplest structure, where a single line serves as heat source. Next, the heat source is endowed with freedom to change its shape as it grows. The objective of the numerical simulations is to discover the geometric features that lead to the fastest melting process. The results show that the heat transfer rate density increases as the complexity and number of degrees of freedom of the structure are increased. Furthermore, the angles between heat invasion lines have a minor effect on the global performance compared to other degrees of freedom: number of branching levels, stem length, and branch lengths. The effect of natural convection in the melt zone is documented.

Experimental and Theoretical Models to Probe Mechanisms of Biological Charge Flow

Nature is challenged to move charge efficiently over many length scales. From sub-nm to μm distances, electron-transfer proteins orchestrate energy conversion, storage, and release both inside and outside the cell. Uncovering the detailed mechanisms of biological electron-transfer reactions, which are often coupled to bond-breaking and bond-making events, is essential to designing durable, artificial energy conversion systems that mimic the specificity and efficiency of their natural counterparts. Here, we use theoretical modeling of long-distance charge hopping (Chapter 3), synthetic donor-bridge-acceptor molecules (Chapters 4, 5, and 6), and de novo protein design (Chapters 5 and 6) to investigate general principles that govern light-driven and electrochemically driven electron-transfer reactions in biology. We show that fast, μm-distance charge hopping along bacterial nanowires requires closely packed charge carriers with low reorganization energies (Chapter 3); singlet excited-state electronic polarization of supermolecular electron donors can attenuate intersystem crossing yields to lower-energy, oppositely polarized, donor triplet states (Chapter 4); the effective static dielectric constant of a small (~100 residue) de novo designed 4-helical protein bundle can change upon phototriggering an electron transfer event in the protein interior, providing a means to slow the charge-recombination reaction (Chapter 5); and a tightly-packed de novo designed 4-helix protein bundle can drastically alter charge-transfer driving forces of photo-induced amino acid radical formation in the bundle interior, effectively turning off a light-driven oxidation reaction that occurs in organic solvent (Chapter 6). This work leverages unique insights gleaned from proteins designed from scratch that bind synthetic donor-bridge-acceptor molecules that can also be studied in organic solvents, opening new avenues of exploration into the factors critical for protein control of charge flow in biology.

Design of binary polymeric systems containing ɩ-carrageenan and hydroxypropylcellulose for use in cataract surgery.

This study describes the design and characterisation of the rheological and mechanical properties of binary polymeric systems composed of 2-Hydroxypropylcellulose and ɩ-carrageenan, designed as ophthalmic viscoelastic devices (OVDs). Platforms were characterised using dilute solution, flow and oscillatory rheometry and texture profile analysis. Rheological synergy between the two polymers was observed both in the dilute and gel states. All platforms exhibited pseudoplastic flow. Increasing polymer concentrations significantly decreased the loss tangent and rate index yet increased the storage and loss moduli, consistency, gel hardness, compressibility and adhesiveness, the latter being related to the in-vivo retention properties of the platforms. Binary polymeric platforms exhibited unique physicochemical properties, properties that could not be engineered using mono-polymeric platforms. Using characterisation methods that provide information relevant to their clinical performance, low-cost binary platforms (3% hydroxypropylcellulose and either 1% or 2% ɩ-carrageenan) were identified that exhibited rheological, textural and viscoelastic properties advantageous for use as OVDs.

Damping Torque Analysis of Power Systems with DFIGs for Wind Power Generation

A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

A novel methodology for analysis of large scale interconnected power and gas systems

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

Integrated Optimal Power Flow for Distribution Networks in Local and Urban Scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

Field investigation of contactless displacement measurement using computer vision systems for civil engineering applications

Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950s and 1960s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and bridge type. This paper investigates the use of computer vision systems for SHM. A series of field tests have been carried out to test the accuracy of displacement measurements using contactless methods. A video image of each test was processed using a modified version of the optical flow tracking method to track displacement. These results have been validated with an established measurement method using linear variable differential transformers (LVDTs). The results obtained from the algorithm provided an accurate comparison with the validation measurements. The calculated displacements agree within 2% of the verified LVDT measurements, a number of post processing methods were then applied to attempt to reduce this error.

Continuous flow gas phase photoreforming of methanol at elevated reaction temperatures sensitised by Pt/TiO2

Gas phase photoreforming of methanol using a Pt/TiO2 photocatalyst has been performed under flow conditions at elevated temperatures. Comparing the activity of the reforming process as a function of temperature under dark and irradiated conditions shows a significant enhancement in the rate of H2 production using the photo-assisted conditions at temperatures between 100-140 °C. At higher temperatures, the effect of irradiation is small with the process dominated by the thermal process. Deactivation of the catalyst was observed under irradiation but the catalyst was easily regenerated using an oxygen treatment at 120 °C. Diffuse Reflectance Infra-red Fourier Transform Spectroscopy (DRIFTS) showed that the activity of the catalyst could be correlated with the presence of the photogenerated trapped electrons. In addition, lower amounts of CO adsorbed on Pt, compared to those observed in the dark reaction, were found for the UV-irradiated systems. It is proposed that CO and adsorbed intermediates, such as formate, can act as inhibitors in the photoreforming process and this is further supported by the observation that, before and after the regeneration process in O2, the CO and surface adsorbed organic intermediate products are removed and the activity is recovered.

Mathematical methods for the configuration of transportation systems with a focus on continuous and modular matrix conveyors

The lack of flexibility in logistic systems currently on the market leads to the development of new innovative transportation systems. In order to find the optimal configuration of such a system depending on the current goal functions, for example minimization of transport times and maximization of the throughput, various mathematical methods of multi-criteria optimization are applicable. In this work, the concept of a complex transportation system is presented. Furthermore, the question of finding the optimal configuration of such a system through mathematical methods of optimization is considered.

Flow Regime Identification Methodology with Mcnp-X Code And Artificial Neural Network

This paper presents flow regimes identification methodology in multiphase system in annular, stratified and homogeneous oil-water-gas regimes. The principle is based on recognition of the pulse height distributions (PHD) from gamma-ray with supervised artificial neural network (ANN) systems. The detection geometry simulation comprises of two NaI(Tl) detectors and a dual-energy gamma-ray source. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be explored. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to acquire information about the different flow regimes. The PHDs obtained by the detectors were used as input to ANN. The data sets required for training and testing the ANN were generated by the MCNP-X code from static and ideal theoretical models of multiphase systems. The ANN correctly identified the three different flow regimes for all data set evaluated. The results presented show that PHDs examined by ANN may be applied in the successfully flow regime identification.

Dimensionality hyper-reduction and machine learning for dynamical systems with varying parameters

Thesis (Ph.D.)--University of Washington, 2016-08