Modeling flotation separation in a semi-batch process

A model for a semi-batch flotation separation process has been developed, based on available microprocess probabilities, and compared to experimental data obtained using a WEMCO laboratory flotation cell. In general, the model predicts the correct experimental trends. In many cases, the model also predicts removal efficiency very well. Parametric studies reveal that the model predictions are sensitive to a stability parameter, the turbulent energy density in the flotation cell, the contact angle between the solid particle and fluid, and the ratio of initial-to-critical film thickness.     

Modeling Condensation and Evaporation on Fruit Surface

Rewarming of fruits and vegetables after cooling is characterized by heat and mass transfer processes, which leads commonly to condensation of water on the produce surface at temperatures below the dew point. This effect may affect the produce quality due to microbial growth at unfavorable environmental conditions. The amount of condensed water is a function of the produce surface temperature and of the surrounding conditions as air temperature, air humidity, and air flow. Under practical conditions, both the warming and the condensation are strongly affected by the packaging system used. Depending on the flow conditions close to the produce surface, parameters of heat and mass transfer under laboratory conditions were measured. A mathematical model was developed for the determination of the amount of condensed water on fruit surfaces, its reevaporation, and its total dwell time dependent on the environment air conditions. The model describes the heat and mass transfer processes on single fruits. The process of diffusion of humidity in air and proceed of surface temperature is the basis for the model.     

Atmospheric Freeze Drying—Modeling and Simulation of a Tunnel Dryer

Drying is an important unit operation in processing of foods and other biotechnological products. Vacuum freeze drying is said to be the best drying technology regarding product quality of the end product, but the disadvantages are, among others, expensive operational costs and batch drying. Atmospheric freeze drying was introduced to lower the production costs of high-quality dried foods, and the need of simulation tools became important in estimations of the industrial drying processes.

A simplified mathematical model (AFDsim) is developed based on uniformly retreating ice front (URIF) considerations. The model is used to calculate theoretical drying curves of atmospheric freeze dried foods in a tunnel dryer. Studies of thermal and mass transfer properties during drying are essential for understanding the changes in product quality and for designing and dimensioning the drying process. The model can be used to simulate industrial atmospheric freeze drying of different foodstuff in a tunnel. The results from AFDsim modeling are in good accordance with the experimental results.     

Influence of Solution Composition on the Formation of Crystalline Scales

Scale formation is a difficulty encountered with water containing ions of sparingly soluble salts that can readily precipitate on heat transfer surfaces in evaporative concentration operations. Scale formation, hindering the heat transfer process, increases specific energy consumption and operating costs and causes frequent shut down of the evaporator for cleaning. The effects of changes in composition of the solution due to evaporation and CO₂ release on the formation of crystalline scales in seawater evaporators are studied. A model that predicts the CO₂ release is presented. The carbonate system in the salt solution on its whole flow path through the evaporator and the scaling (crystallization) tendency are described. Simulation results for different process configurations are shown and the differences are discussed, particularly with regard to the incrustation tendency.     

Speed–accuracy tradeoff in Fitts’ law tasks—on the equivalency of actual and nominal pointing precision

Pointing tasks in human–computer interaction obey certain speed–accuracy tradeoff rules. In general, the more accurate the task to be accomplished, the longer it takes and vice versa. Fitts’ law models the speed–accuracy tradeoff effect in pointing as imposed by the task parameters, through Fitts’ index of difficulty (I_d) based on the ratio of the nominal movement distance and the size of the target. Operating with different speed or accuracy biases, performers may utilize more or less area than the target specifies, introducing another subjective layer of speed–accuracy tradeoff relative to the task specification. A conventional approach to overcome the impact of the subjective layer of speed–accuracy tradeoff is to use the a posteriori “effective” pointing precision W_e in lieu of the nominal target width W. Such an approach has lacked a theoretical or empirical foundation. This study investigates the nature and the relationship of the two layers of speed–accuracy tradeoff by systematically controlling both I_d and the index of target utilization I_u in a set of four experiments. Their results show that the impacts of the two layers of speed–accuracy tradeoff are not fundamentally equivalent. The use of W_e could indeed compensate for the difference in target utilization, but not completely. More logical Fitts’ law parameter estimates can be obtained by the W_e adjustment, although its use also lowers the correlation between pointing time and the index of difficulty. The study also shows the complex interaction effect between I_d and I_u, suggesting that a simple and complete model accommodating both layers of speed–accuracy tradeoff may not exist.     

Tailored Microstructures: Can a Dream come True?

The mechanical properties of crystalline solids are determined by the spatial distribution of chemical elements and crystal defects, which is referred to as microstructure. Microstructure changes during processing, and its evolution can be influenced by processing conditions and external fields. Advanced microstructure codes can cover the through‐process microstructural evolution and allow first predictions of terminal materials properties.     

Determination of gas dispersion in vapor extraction of heavy oil and bitumen

In this work, a mathematical model is developed and simulated to determine gas dispersion along with solubility during the vapor extraction (Vapex) of live oil from a laboratory scale physical model. The physical model is a rectangular block of homogenous porous medium saturated with heavy oil and bitumen. At a given temperature and pressure, the block is initially exposed on its side to a solvent gas, which diffuses into the medium and gets absorbed. The absorption of gas reduces the viscosity of heavy oil and bitumen causing it to drain under gravity. The low-viscosity “live oil” is produced at the bottom of the porous block. The production of live oil with time is accompanied by the shrinkage of oil in the block as well as its increased exposure to gas from top. These phenomena of Vapex are described by the mathematical model, which is used to calculate live oil production with various values of gas solubility and dispersion. Their optimal values are determined for the vapor extraction of Cold Lake bitumen with butane by matching calculated live oil production with its experimental values published earlier.     

Polymerization Kinetics of Fischer‐Tropsch Reaction on Iron Based Catalysts and Product Grade Optimization

The polymerization kinetics of Fischer‐Tropsch reactions on a K‐promoted Fe catalyst was studied. To represent the product distribution, a kinetic model was developed based on alkyl and alkenyl mechanisms for hydrocarbon chain propagation, which were assumed to occur simultaneously in the Fischer‐Tropsch synthesis. The conclusion was drawn that superimposed Anderson‐Schulz‐Flory (ASF) distributions with different chain growth probabilities, on iron catalysts, can be the result of different chain growth mechanisms. The polymerization mechanism was used to obtain the product distribution for several conditions, and the optimum conditions for the production of transportation fuels were found.     

Multiresolution Representation of 2D CSG Models

Multiresolution is currently one of the main schemes used in CAD modeling for representing objects, particularly when large-scale geometric data must be transferred interactively over a network, as in the case of collaborative design. Increasingly complex products and growing competition have turned design into a collaborative team effort. Furthermore, the widespread development of Internet viewers has also necessitated the transfer and display of large-scale CAD models over networks. In order to reduce the volume of transferred data, efforts have been made to transfer CSG (Constructive Solid Geometry) models rather than those based on B_rep (Boundary Representation). This paper presents an original new method for speeding up data transfer by using multiresolution CSG models at different levels of details (LOD). The multiresolution CSG algorithm generates a hierarchy of multiresolution CSG trees; at each level, the shape is further approximated and represented by a smaller number of CSG primitives. The paper analyzes the proposed algorithm, and demonstrates its feasibility.     

D-side: A facility and workforce planning group multi-criteria decision support system for Johnson Space Center

“To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers” is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility's alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility's replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach.