Implementation of the conjugate heat transfer code in KIVA-4

KIVA is an open Computational Fluid Dynamics (CFD) source code that is capable to compute the transient two and three-dimensional chemically reactive fluid flows with spray. The latest version in the family of KIVA codes is the KIVA-4 which is capable of handling the unstructured mesh. This project focuses on the implementation of the Conjugate Heat Transfer code (CHT) in KIVA-4. The previous version of KIVA code with conjugate heat transfer code has been developed at Michigan Technological University by Egel Urip and is be used in this project. During the first phase of the project, the difference in the code structure between the previous version of KIVA and the KIVA-4 has been studied, which is the most challenging part of the project. The second phase involves the reverse engineering where the CHT code in previous version is extracted and implemented in KIVA-4 according to the new code structure. The validation of the implemented code is performed using a 4-valve Pentroof engine case. A solid cylinder wall has been developed using GRIDGEN which surrounds 3/4th of the engine cylinder and heat transfer to the solid wall during one engine cycle (0-720 Crank Angle Degree) is compared with that of the reference result. The reference results are nothing but the same engine case run in the previous version with the original code developed by Egel. The results of current code are very much comparable to that of the reference results which verifies that successful implementation of the CHT code in KIVA-4.

Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

Computational simulations of latent heat thermal energy storage systems - with innovative and first-principles based simulation for the underlying unsteady melting (and solidification) processes

This thesis develops an effective modeling and simulation procedure for a specific thermal energy storage system commonly used and recommended for various applications (such as an auxiliary energy storage system for solar heating based Rankine cycle power plant). This thermal energy storage system transfers heat from a hot fluid (termed as heat transfer fluid - HTF) flowing in a tube to the surrounding phase change material (PCM). Through unsteady melting or freezing process, the PCM absorbs or releases thermal energy in the form of latent heat. Both scientific and engineering information is obtained by the proposed first-principle based modeling and simulation procedure. On the scientific side, the approach accurately tracks the moving melt-front (modeled as a sharp liquid-solid interface) and provides all necessary information about the time-varying heat-flow rates, temperature profiles, stored thermal energy, etc. On the engineering side, the proposed approach is unique in its ability to accurately solve – both individually and collectively – all the conjugate unsteady heat transfer problems for each of the components of the thermal storage system. This yields critical system level information on the various time-varying effectiveness and efficiency parameters for the thermal storage system.

Computational fluids domain reduction to a simplified fluid network

The primary goal of this project is to demonstrate the practical use of data mining algorithms to cluster a solved steady-state computational fluids simulation (CFD) flow domain into a simplified lumped-parameter network. A commercial-quality code, “cfdMine” was created using a volume-weighted k-means clustering that that can accomplish the clustering of a 20 million cell CFD domain on a single CPU in several hours or less. Additionally agglomeration and k-means Mahalanobis were added as optional post-processing steps to further enhance the separation of the clusters. The resultant nodal network is considered a reduced-order model and can be solved transiently at a very minimal computational cost. The reduced order network is then instantiated in the commercial thermal solver MuSES to perform transient conjugate heat transfer using convection predicted using a lumped network (based on steady-state CFD). When inserting the lumped nodal network into a MuSES model, the potential for developing a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track temperatures near specific objects (such as equipment in vehicles).

Problems in the classical calculus of variations

This dissertation concerns convergence analysis for nonparametric problems in the calculus of variations and sufficient conditions for weak local minimizer of a functional for both nonparametric and parametric problems. Newton's method in infinite-dimensional space is proved to be well-defined and converges quadratically to a weak local minimizer of a functional subject to certain boundary conditions. Sufficient conditions for global converges are proposed and a well-defined algorithm based on those conditions is presented and proved to converge. Finite element discretization is employed to achieve an implementable line-search-based quasi-Newton algorithm and a proof of convergence of the discretization of the algorithm is included. This work also proposes sufficient conditions for weak local minimizer without using the language of conjugate points. The form of new conditions is consistent with the ones in finite-dimensional case. It is believed that the new form of sufficient conditions will lead to simpler approaches to verify an extremal as local minimizer for well-known problems in calculus of variations.

DESIGN AND SYNTHESIS OF NOVEL SYNTHETIC ANTIOXIDANTS FOR THE TREATMENT OF OXIDATIVE STRESS RELATED DISEASES

Free radicals play an important role in many physiological processes that occur in the human body such as cellular defense responses to infectious agents and a variety of cellular signaling pathways. While at low concentrations free radicals are involved in many significant metabolic reactions, high levels of free radicals can have deleterious effects on biomolecules like proteins, lipids, and DNA. Many physiological disorders such as diabetes, ageing, neurodegenerative diseases, and ischemia-reperfusion (I/R) injury are associated with oxidative stress.1 In particular, the deleterious effects caused by I/R injury developed during organ transplantation, cardiac infarct, and stroke have become the main cause of death in the United States and Europe.1,2 In this context, we synthesized and characterized a series of novel indole-amino acid conjugates as potential antioxidants for I/R injury. The synthesis of indole-phenol conjugate compounds is also discussed. Phenolic derivatives such as caffeic acid, butylated hydroxytoluene (BHT), butylated hydroxyanisole (BHA), resveratrol, and its analogues are known for their significant antioxidative properties. A series of resveratrol analogues have been designed and synthesized as potential antioxidants. The radical scavenging mechanisms for potential antioxidants and assays for the in vitro evaluation of antioxidant activities are also discussed.

DESIGN, SYNTHESIS AND APPLICATIONS OF FLUORESCENT AND ELECTROCHEMICAL PROBES

“Seeing is believing” the proverb well suits for fluorescent imaging probes. Since we can selectively and sensitively visualize small biomolecules, organelles such as lysosomes, neutral molecules, metal ions, anions through cellular imaging, fluorescent probes can help shed light on the physiological and pathophysiological path ways. Since these biomolecules are produced in low concentrations in the biochemical pathways, general analytical techniques either fail to detect or are not sensitive enough to differentiate the relative concentrations. During my Ph.D. study, I exploited synthetic organic techniques to design and synthesize fluorescent probes with desirable properties such as high water solubility, high sensitivity and with varying fluorescent quantum yields. I synthesized a highly water soluble BOIDPY-based turn-on fluorescent probe for endogenous nitric oxide. I also synthesized a series of cell membrane permeable near infrared (NIR) pH activatable fluorescent probes for lysosomal pH sensing. Fluorescent dyes are molecular tools for designing fluorescent bio imaging probes. This prompted me to design and synthesize a hybrid fluorescent dye with a functionalizable chlorine atom and tested the chlorine re-activity for fluorescent probe design. Carbohydrate and protein interactions are key for many biological processes, such as viral and bacterial infections, cell recognition and adhesion, and immune response. Among several analytical techniques aimed to study these interactions, electrochemical bio sensing is more efficient due to its low cost, ease of operation, and possibility for miniaturization. During my Ph.D., I synthesized mannose bearing aniline molecule which is successfully tested as electrochemical bio sensor. A Ferrocene-mannose conjugate with an anchoring group is synthesized, which can be used as a potential electrochemical biosensor.