Most engineering systems have some degree of uncertainty in their input and operating parameters. The interaction of these parameters leads to the uncertain nature of the system performance and outputs. In order to quantify this uncertainty in a computational model, it is necessary to include the full range of uncertainty in the model. Currently, there are two major technical barriers to achieving this: (1) in many situations -particularly those involving multiscale phenomena-the stochastic nature of input parameters is not well defined, and is usually approximated by limited experimental data or heuristics; (2) incorporating the full range of uncertainty across all uncertain input and operating parameters via conventional techniques often results in an inordinate number of computational scenarios to be performed, thereby limiting uncertainty analysis to simple or approximate computational models. This first objective is addressed through combining molecular and macroscale modeling where the molecular modeling is used to quantify the stochastic distribution of parameters that are typically approximated. Specifically, an adsorption separation process is used to demonstrate this computational technique. In this demonstration, stochastic molecular modeling results are validated against a diverse range of experimental data sets. The stochastic molecular-level results are then shown to have a significant role on the macro-scale performance of adsorption systems. The second portion of this research is focused on reducing the computational burden of performing an uncertainty analysis on practical engineering systems. The state of the art for uncertainty analysis relies on the construction of a meta-model (also known as a surrogate model or reduced order model) which can then be sampled stochastically at a relatively minimal computational burden. Unfortunately these meta-models can be very computationally expensive to construct, and the complexity of construction can scale exponentially with the number of relevant uncertain input parameters. In an effort to dramatically reduce this effort, a novel methodology "QUICKER (Quantifying Uncertainty In Computational Knowledge Engineering Rapidly)" has been developed. Instead of building a meta-model, QUICKER focuses exclusively on the output distributions, which are always one-dimensional. By focusing on one-dimensional distributions instead of the multiple dimensions analyzed via meta-models, QUICKER is able to handle systems with far more uncertain inputs. / Ph. D.

Multiphase transport phenomena primarily encompass the fundamental principles and applications concerning the systems where overall dynamics are precept by phase change evolution. On the other hand, multiscale transport phenomena essentially corroborate to a domain where the transport characteristics often contain components at disparate scales. Relevant examples as appropriate to multiphase and multiscale thermofluidic transport phenomena comprise solid-liquid phase change during conventional solidification process and hydrodynamics through narrow confinements. The additional effect of superimposed magnetic field over such multiphase and multiscale systems may give rise to intriguing transport characteristics, significantly unique in nature as compared to flows without it. The present investigation focuses on multiphase, multi-scale transport phenomena in physical systems subjected to the superimposed magnetic field, considering four important and inter-linked aspects. To begin with, for a multiphase system concerning binary alloy solidification, a normal mode linear stability analysis has been carried out to investigate stationary and oscillatory convective stability in the mushy layer in the presence of external magnetic field. The stability results indicate that the critical Rayleigh number for stationary convection shows a linear relationship with increasing Ham (mush Hartmann number). Magnetohydrodynamic effect imparts a stabilizing influence during stationary convection. In comparison to that of stationary convective mode, the oscillatory mode appears to be critically susceptible at higher values of  (a function of the Stefan number and concentration ratio), and vice versa for lower  values. Analogous to the behaviour for stationary convection, the magnetic field also offers a stabilizing effect in oscillatory convection and thus influences global stability of the mushy layer. Increasing magnetic strength shows reduction in the wavenumber and in the number of rolls formed in the mushy layer. In multiscale paradigm, the combined electroosmotic and pressure-driven transport through narrow confinements have been firstly analyzed with an effect of spatially varying non–uniform magnetic field. It has been found that a confluence of the steric interactions with the degree of wall charging (zeta potential) may result in heat transfer enhancement, and overall reduction in entropy generation of the system under appropriate conditions. In particular, it is revealed that a judicious selection of spatially varying magnetic field strength may lead to an augmentation in the heat transfer rate. It is also inferred that incorporating non–uniformity in distribution of the applied magnetic field translates the system to be dominated by the heat transfer irreversibility. Proceeding further, a semi-analytical investigation has been carried out considering implications of magnetohydrodynamic forces and interfacial slip on the heat transfer characteristics of streaming potential mediated flow in narrow fluidic confinements. An augmentation in the streaming potential field as attributable to the wall slip activated enhanced electromagnetohydrodynamic transport of the ionic species within the EDL has been found. Furthermore, the implications of Stern layer conductivity and magnetohydrodynamic influence on system irreversibility have been shown through analysis of entropy generation due to fluid friction and heat transfer. The results being obtained in this analysis have significant scientific and technological consequences in the context of novel design of future generation energy efficient devices, and can be useful in the further advancement of theory, simulation, and experimental work. Finally, the combined consequences of interfacial electrokinetics, rheology, and superimposed magnetic field subjected to a non-Newtonian (power-law obeying) fluid in a narrow confinement are studied in this work. The theoretical results demonstrate that the applied magnetic field imparts a retarding influence in the induced streaming potential development, whereas, triggers the heat transfer magnitude. Moreover, additional influences of power law index show reduction in heat transfer as well as the streaming potential magnitude. It is unveiled that the optimal combinations of power law index and the magnetic field lead to the minimization of the global total entropy generation in the system.