Brian A. Fricke

Development of correlations for soil thermal conductivity

Abstract Soil thermal conductivity is significantly influenced by saturation and dry density. In this paper, a family of empirical correlations are presented which relate soil thermal conductivity to saturation for five soil types, namely, gravel, sand, silt, clay and peat, in both the frozen and unfrozen states. These correlations were developed from a soil thermal conductivity database which was constructed from measured data available in the literature. The effects of dry density are also examined.

Food thermophysical property models

The design engineer must predict the thermophysical properties of foods in order to design food storage and refrigeration equipment and estimate process times for refrigerating, freezing, heating or drying of foods. Since the thermophysical properties of foods are strongly dependent upon chemical composition and temperature, composition based models provide a means of estimating these properties. Numerous models of this type have been proposed and the designer of food processing equipment is thus faced with the challenge of selecting appropriate models from the plethora of those available. This paper describes selected food thermophysical property models and evaluates their performance by comparing their results to experimental thermophysical property data. The results given in this paper will be of value to the design engineer in the selection of appropriate food thermophysical property models.

BULK REFRIGERATION OF FRUITS AND VEGETABLES PART I: THEORETICAL CONSIDERATIONS OF HEAT AND MASS TRANSFER

A computer algorithm was developed that estimates the latent and sensible heat loads due to the bulk refrigeration of fruits and vegetables. The algorithm also predicts the commodity moisture loss and temperature distribution which occurs during refrigeration. This algorithm includes the combined phenomena of transpiration, respiration, air flow, and convective heat and mass transfer. The development and performance of the computer algorithm are presented in two parts. This paper, Part I, discusses commodity thermophysical properties and flowfield parameters which govern the heat and mass transfer from fruits and vegetables. Commodity thermophysical properties include transpiration and respiration, while flowfield parameters include psychrometric properties and convective heat and mass transfer coefficients. Part I describes the modeling treatment of these properties and parameters. The second paper, Part II, discusses the heat and mass transfer models, compares algorithm results to experimental data, and...

Structural and Drug Diffusion Models of Conventional and Auxetic Drug-Eluting Stents

Most balloon angioplasty procedures include the insertion of tiny cylindrical wire mesh structures, called cardiovascular stents, into the artery to prevent the elastic recoil that follows arterial dilatation. The scaffolding characteristics of the stent provide strength to the artery wall. However, vascular injury during stent deployment and/or recognition of the stent as a foreign material triggers neointimal hyperplasia, causing re-closure, or restenosis, of the artery. A recent advancement to counteract restenosis is to employ drug-eluting stents to locally deliver immunosuppressant and antiproliferative drugs. In this project, Fick’s law of diffusion was used to model drug diffusion from the stent matrix into the adjacent arterial tissue. An analytical procedure was also developed to estimate the circumferential and the flexural stiffnesses of stents. Furthermore, a unique auxetic (negative Poisson’s ratio) stent structure was proposed that exhibits high circumferential strength in its expanded configuration and low flexural rigidity in its crimped configuration. Results generated with the analytical diffusion model, developed in this project, compare favorably with previously published clinical and experimental data. The circumferential and flexural stiffnesses estimated using the analytical procedure developed in this project compare favorably with the results from rigorous finite element analyses and previously published experimental data.

Mechanical Properties and Surface Characterization of Beta Titanium and Stainless Steel Orthodontic Wire Following Topical Fluoride Treatment

OBJECTIVE To study the effect of fluoride prophylactic agents on the loading and unloading mechanical properties and surface quality of beta titanium and stainless steel orthodontic wires. MATERIALS AND METHODS Rectangular beta titanium and stainless steel wires were immersed in either an acidulated fluoride agent, a neutral fluoride agent, or distilled water (control) for 1.5 hours at 37 degrees C. After immersion, the loading and unloading elastic modulus and yield strength of the wires were measured using a 3-point bend test in a water bath at 37 degrees C. A one-way analysis of variance and Dunnetts post hoc, alpha = .05, were used to analyze the mechanical testing data. Scanning electron microscopy was also used to qualitatively evaluate the wire topography as a function of the fluoride treatments. RESULTS Unloading mechanical properties of beta titanium and stainless steel wires were significantly decreased (P <or= .05) after exposure to both fluoride agents. Corrosive changes in surface topography were also observed after exposure to both the neutral and the acidulated phosphate fluoride agents. CONCLUSIONS The results suggest that using topical fluoride agents with beta titanium and stainless steel wire could decrease the functional unloading mechanical properties of the wires and potentially contribute to prolonged orthodontic treatment.

Evaluation of Thermophysical Property Models for Foods

The thermophysical properties of foods are required in order to calculate process times and to design equipment for the storage and preservation of food. There are a multitude of food items available, whose properties are strongly dependent upon chemical composition and temperature. Composition-based thermophysical property models provide a means of estimating properties of foods as functions of temperature. Numerous models have been developed and the designer of food processing equipment is faced with the challenge of selecting appropriate ones from those available. In this paper selected thermophysical property models are quantitatively evaluated by comparison to a comprehensive experimental thermophysical property data set compiled from the literature. For ice fraction prediction, the equation by Chen (1985b) performed best, followed closely by that of Tchigeov (1979). For apparent specific heat capacity, the model of Schwartzberg (1976) performed best, and for specific enthalpy prediction, the Chen (1985a) equation gave the best results, followed closely by that of Miki and Hayakawa (1996). Finally, for thermal conductivity, the model by Levy (1981) performed best.

CALCULATION OF HEAT TRANSFER COEFFICIENTS FOR FOODS

ABSTRACT The design of food refrigeration equipment requires estimation of the cooling and freezingtimes of foods and beverages, as well as the corresponding refrigeration loads. The accuracyof these estimates, in turn, depends upon accurate estimates of the surface heat transfercoefficient for the cooling or freezing operation. A unique iterative algorithm, utilizing theconcept of “equivalent heat transfer dimensionality,” was developed to obtain heat transfercoefficients from cooling curves. Cooling curves were obtained from an industrial survey,and, utilizing the iterative algorithm, heat transfer coefficients were determined for variousfood items. A small portion of that data presented in this paper. This information will makepossible a more accurate determination of cooling and freezing times and correspondingrefrigeration loads. Introduction In many food processing applications, including cooling and freezing, transient convective heattransfer occurs between a fluid medium and the solid food item [1]. Knowledge of the surface heat transfercoefficient is required to design the equipment wherein convection heat transfer is used to process foods andbeverages. Newtons law of cooling defines the surface heat transfer coefficient,

Hydrocooling time estimation methods

Precooling refers to the rapid removal of field heat from freshly harvested fruits and vegetables prior to shipping, storage or processing. Hydrocooling is a form of precooling in which the product is sprayed with or immersed in an agitated bath of chilled water. The design of hydrocooling systems requires accurate estimation of the hydrocooling times of fruits and vegetables as well as the corresponding refrigeration loads. Numerous methods for predicting the hydrocooling times of fruits and vegetables have been proposed, and the designer is faced with the challenge of selecting an appropriate estimation method from those available. Therefore, this paper reviews selected estimation methods for the hydrocooling times of fruits and vegetables, and quantitatively evaluates the selected hydrocooling time estimation methods by comparing their numerical results to a comprehensive experimental hydrocooling time data set compiled from the literature.

FREEZING TIMES OF REGULARLY SHAPED FOOD ITEMS

Abstract The freezing of food is one of the most significant applications of refrigeration. In order for freezing operations to be cost-effective, it is necessary to optimally design the refrigeration equipment. This requires estimation of the freezing times of foods. Numerous semianalytical/empirical methods for predicting food freezing times have been proposed. The designer of food refrigeration facilities is thus faced with the challenge of selecting an appropriate estimation method from the plethora of available methods. Therefore, a review of selected semi-analytical/empirical food freezing time prediction methods applicable to regularly shaped food items is given in this paper. The performance of these various methods is evaluated by comparing their results to experimental freezing time data obtained from the literature.

A Theoretical Model of the Thermal Conductivity of Idealized Soil

Accurate prediction of soil thermal conductivity is of prime importance in the numerical simulation of heat transmission through soils. This paper focuses upon empirical and semi-empirical prediction methods for soil thermal conductivity. A family of empirical correlations are presented which relate soil thermal conductivity to saturation for five soil types: gravel, sand, silt, clay, and peat. These correlations are developed from a database of measured data available in the literature. Also, a theoretical model of soil thermal conductivity is developed for granular materials composed of rotund particles in an almost dry state. This theoretical model includes the effects of the micro-structure and the conductivity of the solid phase. It explicitly relates soil thermal conductivity to dry density and agrees well with experimental data. This paper also presents a review and discussion of those factors which affect soil thermal conductivity, previously reported prediction methods, and conductivity measureme...