Doctor of Philosophy, The Ohio State University, 2024, Food, Agricultural and Biological Engineering

The smoking process for a food product involves the deposition and absorption of smoke on the product surface, followed by a drying step to reduce the product moisture content to a defined level. The uniformity of air velocity and temperature within a smokehouse significantly influences final product quality, including color, texture, and flavor. Additionally, process efficiency and production capacity depend on uniform heat and mass transfer at the surface for all products in the smokehouse. While Computational Fluid Dynamics (CFD) has been used to study airflow patterns, air velocity and temperature distributions due to ventilation systems, research on applications to airflow distribution in a smokehouse have been limited. The overall objective of this research was to develop and validate CFD simulations of a smokehouse ventilation system to investigate the applications to airflow uniformity within a smokehouse. A CFD simulation of airflow distribution in a smokehouse without product was developed and used to investigate the influence of smokehouse ventilation configuration on uniformity of air velocity. The ventilation system configuration with outlet vents positioned near the inlet vents at both sides of the smokehouse ceiling exhibited the highest air velocity uniformity index of 0.64. An investigation of three different outlet vent dimensions indicated that outlet vent size did not influence the uniformity of air velocity distribution within the empty smokehouse. The influence of model products in the smokehouse was investigated using the CFD simulation. The average air velocity at 20 locations decreased from 3.9 ±1.4 m/s to 2.7 ±0.90 m/s when the ratio of model product to smokehouse volume was increase from 0 to 0.047. The influence of ventilation configuration was also evaluated by comparing outlet vents positioned near the inlet vents at both sides of the smokehouse ceiling to the outlet vent located in the ceiling at the middle of the smokehouse. The ave (open full item for complete abstract)

Committee: Dennis Heldman (Advisor); Sudhir Sastry (Committee Member); Sandip Mazumder (Committee Member); Osvaldo Campanella (Committee Member) Subjects: Engineering; Fluid Dynamics; Food Science

Doctor of Philosophy, The Ohio State University, 2024, Earth Sciences

Knowledge of the distribution of Fe2+ and Mg between olivine and melt (the distribution coefficient, KD) is crucial to understand the origin and evolution of magmas. However, there is disagreement regarding which variables (temperature, melt composition, and oxygen fugacity – fO2) influence the value of KD, as well as the magnitude of their effects. To evaluate the dependence of KD on these variables, data were compiled from literature consisting of equilibrium olivine-melt pairs in experiments at controlled temperature, fO2, and 1 atm pressure. The results confirm that KD is essentially independent of temperature and fO2. However, it is strongly dependent on melt composition (particularly the concentration of silica and alkalis). An evaluation of different published formulations for KD using these data demonstrates that the expression of Gee and Sack (1988) is the most accurate and precise. Furthermore, a new and simpler model based on variation of KD with silica and alkalis has been fit to the olivine-melt database. This reproduces KD with the same accuracy and precision as the Gee and Sack (1988) formulation. The olivine-melt database also illustrates that KD can be used to calculate the proportion of the different valence states of iron in the melt (the Fe3+/ΣFe ratio), which cannot be measured using routine analytical techniques. The melt Fe3+/ΣFe can then be related to fO2 using empirical relationships. This method, referred to as the Olivine-Melt Equilibrium (OME) method, reproduces the fO2 imposed on the experiments within ±0.3 log units. This method was applied to compiled data for natural samples from literature from mid-ocean ridges, ocean islands, back-arc basin spreading centers, and volcanic arcs. Olivine-melt calculated values of fO2 for each location investigated agree with the results of independent techniques. These include compiled measurements of Fe3+/ΣFe ratios using Fe K-edge μ-X-ray Absorption Near Edge Structure (XANES) spectroscopy, as we (open full item for complete abstract)

Committee: Michael Barton (Advisor); Berry Lyons (Committee Member); Daniel Kelley (Committee Member); Derek Sawyer (Committee Member); David Cole (Committee Member) Subjects: Earth; Geochemistry; Geological; Geology; Petrology; Plate Tectonics

MS, Kent State University, 2023, College of Arts and Sciences / Department of Earth Sciences

Piping or internal erosion has been responsible for almost half of all dam failures worldwide. In this research, we studied the influence of grain size heterogeneity, as characterized by sediment size (d50) and the uniformity coefficient (Cu), on piping potential. A novel experimental setup was designed in-house that included sediment mass, pressure, and turbidity sensors allowing the examination of transient changes during piping events. Porosity and conductivity were analyzed in order to compare trends across varying grain size distributions. Mass values of soil lost during piping failure via a continuous mass balance and a turbidity meter to capture fines that remain in suspension were both utilized to capture the magnitude of piping failure. Minute Piping and Clogging events that are only able to be captured via the pressure transducers were recorded during this experiment, adding complexity to the onset of piping phenomena. The smaller the Cu, the less clogging events occurred before piping failure. It was noted that these minute piping and clogging events would stabilize as the sediment column reached equilibrium. This research allows for further studies to expand on these piping and clogging events as well as depicted trends between soil heterogeneity and piping potential.

Committee: Kuldeep Singh (Advisor); David Hacker (Committee Member); Anne Jefferson (Committee Member) Subjects: Civil Engineering; Earth; Engineering; Environmental Engineering; Environmental Geology; Experiments; Geology; Hydrologic Sciences; Hydrology; Soil Sciences

Master of Science, Miami University, 2022, Chemical, Paper and Biomedical Engineering

The need for more efficient drug design and development has become more prevalent in just the last few years, leading to the development of the SAMPL challenges to promote exploration of methods to compute physical properties key to drug development. Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1- octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute.

Committee: Andrew Paluch (Advisor); Alim Dewan (Committee Member); Jason Boock (Committee Member) Subjects: Chemical Engineering

MS, University of Cincinnati, 2021, Engineering and Applied Science: Computer Science

This thesis presents an algorithm for finding approximate maximal cliques in a very large graph using the distributed computational framework of Hadoop and spark. The primary motivation behind approximate maximal cliques enumeration is that many candidate maxcliques in graphs have almost all the needed edges but just a few ones are missing. In our approach, a heuristic search algorithm is used to list all strongly connected components of an undirected graph network. All approximate maximal cliques with connectivity higher than a threshold are produced by our algorithm. Starting from a triangle as a seed (smallest available Maximal Clique), we expand it using the lists of all vertices in the graph connected to the seed triangle's vertices. One or more combinations of vertices from the lists vertices connected to the triangle can form approximate Maximal Cliques. From the lists of nodes, we eliminate the least promising nodes one at a time. A* search algorithm performs the elimination of nodes to find the strongly connected components. As A* search algorithm works well with heuristics, three different heuristics are considered for this project. They are 1) Approximate maximal clique connectivity based on degree distribution, 2) Small-tail distribution of the degree of nodes connected to the triangle, and 3) Approximate maximal clique connectivity based on clustering coefficient. These heuristics are tested on three separate datasets, and values for different metrics are compared.

Committee: Raj Bhatnagar Ph.D. (Committee Chair); Gowtham Atluri Ph.D. (Committee Member); Ali Minai Ph.D. (Committee Member) Subjects: Computer Science

Master of Science (MS), Wright State University, 2008, Earth and Environmental Sciences

Using batch and stream recirculating flume experiments to compare and contrast one clayey sediment (Warden Ditch) and two analytical grade clay minerals (montmorillonite and kaolinite), the dynamic interactions between two aquatic stressors (suspended solids and nickel) were explored. Aldrich humic acid was incorporated to demonstrate the mitigating effects of dissolved organic carbon (DOC) on Ni toxicity. The flux of Ni between compartments (dissolved and sorbed) was quantified as a partition/distribution coefficient. The USEPA test organism Daphnia magna (neonates, < 24 h) was utilized to evaluate toxicity in dynamic non-renewal, short-term bioassays. Generally, toxicity showed a linear relationship with turbidity level. Conversely, sorption coefficients were experiment specific, making them difficult to predict and assess. Clay functioned as an adsorbent, scavenging Ni. Results support the hypotheses that solids and metals act as stressors in streams, DOC attenuates the toxicity of Ni, and Ni fluxes quickly between system compartments.

Committee: G. Allen Burton PhD (Committee Chair); David Dominic PhD (Committee Member); Songlin Cheng PhD (Committee Member); Chad Hammerschmidt PhD (Committee Member) Subjects: Earth; Environmental Science; Geology; Toxicology

MS, University of Cincinnati, 2004, Engineering : Environmental Engineering

The longitudinal dispersion coefficient of a conservative tracer (CaCl2) was calculated from continuous flow tests in a dead-end pipe system. The system consisted of 6-inch diameter PVC pipe with a test length of approximately 44 meters. Flow conditions ranged from laminar to turbulent regimes, with a Reynolds number range of 1000 to 10000. Two static mixers in series were used to homogenize the tracer concentration across the cross-section of pipe. The conductivity of the tracer was measured at two locations downstream of the injection and mixers using a conductivity probe at a point in the cross-section. Dispersion coefficients calculated by the method of moments are plotted versus Reynolds number. Test results show increasing time-averaged dispersion rate in the laminar flow regime and a portion of the transitional flow regime with increasing Reynolds number. At a flow rate corresponding to a Reynolds number (Re) of approximately Re=2400, the dispersion rate reaches a maximum value and then decreases until approximately Re=4000. As the tests enter the turbulent flow regime, the dispersion rate is minimized due to the plug-flow behavior inherent to turbulent flow. Results indicate that dispersion plays a more important role in mass transport in laminar and transitional flow than advective mass transport. Incorporating dispersion estimates into network water quality models will improve quality predictions for the dead-end portions of the network.

Committee: Dr. Steven Buchberger (Advisor) Subjects: Engineering, Environmental

MS, Kent State University, 2010, College of Arts and Sciences / Department of Computer Science

The backbone of the Internet is made up of a network of autonomous systems. The Autonomous System Network, also referred to as the ASN, provides an organized system of routing between hosts and other autonomous systems. Knowledge of the ASN is important to the understanding of the Internet. The Internet can be viewed as the ASN itself for the purposes of study in order to comprehend the major issues of performance and growth involved with it. However, the complexity, size, and pattern of evolution in the ASN make the network difficult to track over time. Previous research on the topic has done little to clarify the picture of the ASN. The majority of studies use static data like snapshots and small data sets to study the autonomous systems. Furthermore, recent researchers do not discuss the structural aspects of the ASN. We aim to expand on both the dynamic and structural properties of the ASN utilizing a variety of metrics. Included in these measurements is a new process incorporating familiar topological patterns and generating functions. We discuss several such topological structures and the new technique, which involves the comparison of the complex network graph to different topologies that show signatures and generating functions similar to the network. This process is then applied to a data set representing several states of the ASN that encompasses information collected from a variety of sources over the course of five years. The findings of this study reveal interesting and important information about the evolutionary state of the ASN, providing a complete and thorough analysis of multiple key properties of the Internet.

Committee: Javed Khan PhD (Advisor); Arden Ruttan PhD (Committee Member); Hassan Peyravi PhD (Committee Member) Subjects: Computer Science