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This thesis explores how the study of realistic mixes can expand current knowledge about multitrack music mixing. An essential component of music production, mixing remains an esoteric matter with few established best practices. Research on the topic is challenged by a lack of suitable datasets, and consists primarily of controlled studies focusing on a single type of signal processing. However, considering one of these processes in isolation neglects the multidimensional nature of mixing. For this reason, this work presents an analysis and evaluation of real-life mixes, demonstrating that it is a viable and even necessary approach to learn more about how mixes are created and perceived. Addressing the need for appropriate data, a database of 600 multitrack audio recordings is introduced, and mixes are produced by skilled engineers for a selection of songs. This corpus is subjectively evaluated by 33 expert listeners, using a new framework tailored to the requirements of comparison of musical signal processing. By studying the relationship between these assessments and objective audio features, previous results are confirmed or revised, new rules are unearthed, and descriptive terms can be defined. In particular, it is shown that examples of inadequate processing, combined with subjective evaluation, are essential in revealing the impact of mix processes on perception. As a case study, the percept `reverberation amount' is ex-pressed as a function of two objective measures, and a range of acceptable values can be delineated. To establish the generality of these findings, the experiments are repeated with an expanded set of 180 mixes, assessed by 150 subjects with varying levels of experience from seven different locations in five countries. This largely confirms initial findings, showing few distinguishable trends between groups. Increasing experience of the listener results in a larger proportion of critical and specific statements, and agreement with other experts.

This research explores the possibility of reproducing mixing decisions of a skilled audio engineer with minimal human interaction that can improve the overall listening experience of musical mixtures, i.e., intelligent mixing. By producing a balanced mix automatically musician and mixing engineering can focus on their creativity while the productivity of music production is increased. We focus on the two essential aspects of such a system, frequency and dynamics. This thesis presents an intelligent strategy for multitrack frequency and dynamics processing that exploit the interdependence of input audio features, incorporates best practices in audio engineering, and driven by perceptual models and subjective criteria. The intelligent frequency processing research begins with a spectral characteristic analysis of commercial recordings, where we discover a consistent leaning towards a target equalization spectrum. A novel approach for automatically equalizing audio signals towards the observed target spectrum is then described and evaluated. We proceed to dynamics processing, and introduce an intelligent multitrack dynamic range compression algorithm, in which various audio features are proposed and validated to better describe the transient nature and spectral content of the signals. An experiment to investigate the human preference on dynamic processing is described to inform our choices of parameter automations. To provide a perceptual basis for the intelligent system, we evaluate existing perceptual models, and propose several masking metrics to quantify the masking behaviour within the multitrack mixture. Ultimately, we integrate previous research on auditory masking, frequency and dynamics processing, into one intelligent system of mix optimization that replicates the iterative process of human mixing. Within the system, we explore the relationship between equalization and dynamics processing, and propose a general frequency and dynamics processing framework. Various implementations of the intelligent system are explored and evaluated objectively and subjectively through listening experiments.

Granular materials appear in a broad range of industrial processes, including mineral processing, plastics manufacturing, ceramic component, pharmaceutical tablets and food products. Engineers and scientists are always seeking efficient tools that can characterize, predict, or simulate the effective material properties in a timely manner and with acceptable accuracy, such that the cost for design and develop novel composite granular materials could be reduced. The major scope of this dissertation covers the development, verification and validation of particle system simulations, including solid-liquid two-phase particle mixing process and foaming asphalt process. High shear mixing process is investigated in detail with different types of mixers. Besides particle mixing study, one liquid-gas two phase foaming asphalt simulation is studied to show the broad capacity of our particulate dynamics simulation scheme. Methodologies and numerical studies for different scenarios are presented, and acceleration plans to speed up the simulations are discussed in detail. The dissertation starts with the problem statement, which briefly demonstrates the background of the problem and introduces the numerical models built from the physical world. In this work, liquid-solid two-phase particle mixing process is mainly studied. These mixing processes are conducted in a sealed mixer and different types of particles are mixed with the rotation of the mixer blades, to obtain a homogeneous particle mixture. In addition to the solid-liquid particle mixing problem, foaming asphalt problem, which is a liquid-gas two phase flow problem is also investigated. Foaming asphalt is generated by injecting a small amount of liquid additive (usually water) to asphalt at a high temperature. The volume change during this asphalt foaming process is studied. Given the problem statement, detailed methodologies of particle dynamics simulation are illustrated. For solid-liquid particle mixing, Smoothed Particle Hydrodynamics (SPH) and Discrete Element Method (DEM) are introduced and implemented to simulate the dynamics of solid and liquid particles, respectively. Solid-liquid particle interactions are computed according to Darcy`s Law. Then the proposed SPH coupling DEM model is verified by three classical case studies. For foaming asphalt problems, a SPH numerical model for foaming asphalt simulation is proposed, and simulations with different water contents, pressures and temperatures are conducted and the results agree with the experiments well. The coupled SPH-DEM method is applied to the particle mixing process, and several particle mixing numerical studies are conducted and these simulations are analyzed in multiple aspects. For the solid-liquid particle mixing problem, liquid plays an important role in the mixing performance. The effects of liquid content and liquid viscosity on mixing performance are studied. The mixing indexes of the mixture are applied to analyze the mixing quality, and the differences between three kinds of mixing indexes are discussed. Then mixers commonly used in industry such as Double Planetary Mixer (DPM) are modeled in mixing simulation and their results are compared with the experiments. Similar to other numerical simulation problems, the scale of the model and the accuracy of the simulation results are constrained by the computational capacity. Our in-house software package Particle Dynamics Parallel Simulator(PDPS) has been used as a platform to implement the algorithms above and conduct the simulations. Two parallel computing methods of Message Passing Interface (MPI) parallel computing and Graphics Processing Unit (GPU) acceleration have been used to accelerate the simulations. Speedup results for both MPI parallel computing and GPU methods are illustrated in the case studies. In summary, a comprehensive approach for particle simulation is proposed and applied to particle mixing process and asphalt foaming simulation. The simulation results are analyzed in various aspects to provide valuable insights to the problems studied in this work. Given the improvement of computational capacity, particle dynamics in higher resolution and simulations in more complex configurations can be obtained. This particle simulation platform is general and it can be straightforwardly extended to many-particle systems with more particle phases and solid-liquid-gas dynamics problems.

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This project will investigate mixing in microchannels. Specifically, the advection and diffusion of a passive scalar, using a split step Monte Carlo method. Numerically the implementation of this method is well understood. The current experimental geometry is a rectangular pipe with grooves on one wall. Mixing results with straight walls agree closely with experiment. The velocity field over grooves is also studied.

This work represents a first look at the general spatial distribution of trace metals and the inorganic carbon system in the surface waters of Tampa Bay. Tampa Bay's chemical environment bears many influences ranging from hydrological and geological to anthropogenic and meteorological. A large y-shaped estuary on the west-central side of the Florida Peninsula, Tampa Bay extends over 400 square miles and has a 2200 square mile watershed that includes extensive swamps, scrub, agricultural lands and densely urbanized areas. Reaching 37 miles from the northernmost point of Old Tampa Bay to the mouth of the estuary near the Sunshine Skyway Bridge, it is home to the largest port in Florida, and overall places 17th in the nation for tonnage. In addition to its ports, Tampa Bay supports the requirements of a broad range of industries including: ship building and repair, power generation, wastewater processing, development, and recreational and commercial fishing. The region experiences high rainfall during the summer and much reduced rainfall during the remaining portions of the year. The bay has a broad gradient of mixing intensities, with residence times ranging from 100+ days in Old Tampa Bay to less than 20 days at the mouth. Seventy-one percent of Tampa Bay's freshwater input is delivered by four primary rivers: the Hillsborough, Alafia, Manatee and Little Manatee; and the region is strongly influenced by spring outflow from the Floridan Aquifer. The largest river, the Hillsborough, spans 54 miles from the Green Swamp to its mouth in Hillsborough Bay. Samples were collected over a two-week period in January of 2013 along 13 sites on the Hillsborough River and 26 stations in Tampa Bay. Metal concentration analyses were conducted on twelve elements using inductively coupled plasma mass spectrometry (ICP-MS). These twelve elements included sodium, lithium, magnesium, calcium, strontium, barium, vanadium, molybdenum, manganese, nickel, antimony, and uranium. Within Tampa Bay, sodium, lithium, and magnesium exhibited strongly conservative behavior (showing simple two-end-member mixing). Calcium, strontium, molybdenum, and uranium show quasi-conservative behavior, with localized deviations from simple mixing of fresh water and seawater end members. The remaining elements showed variable behavior driven by solubility, redox reactions, and/or unique localized inputs based on local geology. Comparisons of baywater calcium concentrations and the concentrations of lithium, magnesium, strontium and barium revealed simple relationships that are promising for use in interpretations of otolith chemistry of teleosts and some agnatha (Campana, 1999; Carlström, 1963). Samples were collected from both the river and the bay for CO2 system analyses. Spectrophometric pH measurements were obtained using purified m-Cresol Purple (mCP) and the procedures of Liu et al. (2011). Dissolved inorganic carbon (DIC) was processed according to CDIAC's Guide to Best Practices, SOP:2 (Dickson, Sabine, & Christian, 2007). Total alkalinity samples were processed using the spectrophotometric procedures of Yao and Byrne (1998). Dissolved inorganic carbon in the bay ranged between 3500 µMol/L and 2250 µMol/L and, in the Hillsborough River, peaked at 3700 µMol/L just below the Green Swamp. A comparison of measured total alkalinity and calculated alkalinity (obtained using pH and DIC and CO2sys software) demonstrated the presence of substantial organic base concentrations within the bay.

The performance of flocculants used in the solid-liquid separation of red mud is often compromised by the methods used to mix the fast acting polymers into the slurry. A simple model of the relationship between flocculant performance and intensity of mixing is proposed and a device for mixing flocculant and slurry has been developed on the basis of the model.The intensity of mixing at the point of distributing the flocculant into the slurry is arguably the most important variable influencing the final flocculant performance. This relationship is established using data from flocculation tests in an agitated tank. The flocculant performance is monitored using an optical sensor and the settling rate of the solid-liquid interface is used as a comparison for the optical sensor. The difficulties, errors and merits of the optical sensor to study the flocculation of red mud and automatic control of flocculation processes are also assessed.The mixing device is connected to a pipe for flocculation tests with red mud. For the tests carried out, a high level of flocculation was recorded.The mixing device combines the flocculant and slurry as thin annular jets directed into one another. The opening for the slurry jet can be altered to provide a variation of the mixing that is achieved. The capability of the device to mix rapidly has been assessed using the diazo coupling reactions between l-naphthol and diazotised sulphanilic acid in alkaline, aqueous solution at room temperature. Variables studied included flow rate and slurry jet opening. Better mixing was indicated at higher flow rates and at reduced jet opening. The use of the diazo coupling reactions for studying micromixing is also assessed.

As ocean ecosystems continue to deteriorate in the face of human induced pressures, marine management professionals are increasingly being urged to predict the impacts of various activities on ocean ecosystems. Many ecosystem interactions are still not adequately understood, so managers often turn to scientists to provide data and analysis on impacts resulting from specific actions. One important physical ocean process in need of more empirical data is microscale turbulence. Because it is responsible for mixing across isopycnal surfaces in stratified waters, turbulence is important in many physical, chemical and biological processes in the ocean. An elementary description of turbulence and mixing is presented along with a summary of the role of turbulence in marine ecosystems. In order to be of use to scientists, turbulence must be measured over large areas of the ocean. This paper presents a discussion of techniques for measuring turbulence. Measurements of turbulence are specialized and costly. A new microstructure data acqusition system was developed to acquire microstructure data eight times faster than present methods allow. The design details of the high-speed microstructure data acquisition system called MicroSoar are presented along with some preliminary data obtained from its deployment on actual cruises. / Graduation date: 1998