Objective
This study aimed at assessing the risks associated with human exposure to heat-stress conditions by predicting organ- and tissue-level heat-stress responses under different exertional ...activities, environmental conditions, and clothing.
Methods
In this study, we developed an anatomically detailed three-dimensional thermoregulatory finite element model of a 50th percentile U.S. male, to predict the spatiotemporal temperature distribution throughout the body. The model accounts for the major heat transfer and thermoregulatory mechanisms, and circadian-rhythm effects. We validated our model by comparing its temperature predictions of various organs (brain, liver, stomach, bladder, and esophagus), and muscles (vastus medialis and triceps brachii) under normal resting conditions (errors between 0.0 and 0.5 °C), and of rectum under different heat-stress conditions (errors between 0.1 and 0.3 °C), with experimental measurements from multiple studies.
Results
Our simulations showed that the rise in the rectal temperature was primarily driven by the activity level (~ 94%) and, to a much lesser extent, environmental conditions or clothing considered in our study. The peak temperature in the heart, liver, and kidney were consistently higher than in the rectum (by ~ 0.6 °C), and the entire heart and liver recorded higher temperatures than in the rectum, indicating that these organs may be more susceptible to heat injury.
Conclusion
Our model can help assess the impact of exertional and environmental heat stressors at the organ level and, in the future, evaluate the efficacy of different whole-body or localized cooling strategies in preserving organ integrity.
•A framework to describe flow and deformation is applied to drying.•Rubbery/glassy phase transition to account for property changes.•Case-hardening phenomenon is explained in a mechanistic way.•Key ...textural attributes associated with dried products is predicted mechanistically.
A mechanistic framework for quality development such as shrinkage and case hardening in drying would allow new insights making the final quality in a drying process more predictable and controllable. A poromechanics model that includes multiphase (solid matrix/liquid water/vapor) transport and large deformation using hyperelastic constitutive relationship between the stress and strain is developed. Moisture and state (rubbery/glassy) dependent mechanical and transport properties are used. A complex shrinkage pattern that is not simply equal to the amount of water lost is observed at low moisture contents due to glass transition of the material. For high drying rates, the surface dries out faster than the core and forms a case-hardened layer resulting in early deviations in shrinkage. In contrast, for low drying rates, deviations in shrinkage occur at extremely low moisture contents due to a gradual rubbery/glassy transition. Key quality attributes, such as degree of crust formation, are predicted from fundamentals.
The present work involves development of a fundamentals-based coupled electromagnetics, multiphase transport and large deformation model to understand microwave drying of a hygroscopic porous ...material. Microwave drying is carried out in a 950W domestic microwave oven operating at 10% power level. Electric field distribution inside the oven cavity and porous material are obtained by solving Maxwell's equations for electromagnetics. Modes of fluid transport include capillarity, binary diffusion and gas pressure-driven flow. Large deformation, included by treating the solid as hyperelastic, is implemented in a novel way using the Arbitrary-Lagrangian–Eulerian framework for mesh movement. Deformation during microwave drying was found to critically alter material structure that significantly affected microwave absorption, heat and moisture transport within the material. Sensitivity analysis revealed that moisture loss and volumetric shrinkage were unaffected with changes in intrinsic permeability and elastic modulus of the material while stress state within the material was highly sensitive to elastic modulus values.
•Comprehensive description of microwave drying with all relevant physics.•Electromagnetics, multiphase transport and large deformation solid mechanics are three-way coupled.•Mechanical deformation critically affects electromagnetics and heat and moisture transport.•Volume change is primarily due to moisture loss.•Pressure gradients within the material are responsible for stress development.
Puffing of biomaterials involves mass, momentum and energy transport along with large volumetric expansion of the material. Development of fundamentals-based models that can describe heat and ...moisture transport, rapid evaporation and large deformations can help understand the factors affecting the puffing processes and optimize them. In this context, salt-assisted puffing of parboiled rice is described. A multiphase porous media model involving heat and mass transfer within the rice kernel undergoing large deformations is developed. The transport model involves different phases and multiple modes of transport. During puffing, intensive heating of rice leads to rapid evaporation of water to vapor resulting in large pressure development. Also, the rice starch undergoes Glass Transition from a rigid, glassy state to a soft, rubbery state. Development of large pressures within a soft matrix results in large volumetric expansion of the kernel causing it to puff. The developed model was validated against moisture changes and volumetric expansion of the rice kernel during the puffing process and good agreement was found. Gas porosity development in puffed rice was determined via 3D reconstruction of micro-CT images of rice puffed at different times which compared favorably well with model predictions. The expansion of the kernel began from the tip of the grain and the model could successfully capture this phenomenon. Expansion ratio, a key quality parameter associated with puffed products, was found to be sensitive to intrinsic permeability and bulk modulus of the solid matrix. The modeling framework for salt-assisted puffing was then extended to the process of gun-puffing (a completely different puffing process) without significant reformulations thus showing the applicability of the framework for a variety of puffing processes. The final expansion after gun-puffing was much higher compared with salt-assisted puffing and was found to be sensitive to the gun opening time.
•A framework for transport and deformation is presented for puffing-type processes.•Rubbery/glassy phase transition is a critical component for puffing-type processes.•Large gas pressure generation and glass-to-rubber phase transition cause puffing.•Salt-assisted and gun puffing of rice are explained in a fundamental way.
► The article focuses on estimating food properties in dynamic simulation environment. ► Models discussed range from completely theoretical to completely empirical. ► Preferred choice of models have ...been the ease of implementation and better accuracy.
During processing of a food, its temperature, moisture and other compositions, structure, etc., can change, continuously changing its physical properties. Realistic simulation of food processes require dynamic estimation of the food physical properties as they continue to change during the process. Having a few data points for a few states of the material, as is true for the majority of food properties data, is not sufficient for realistic process simulations. The goal of this article is a practical one: it is to develop a concise resource for the equations that can estimate food properties as they change during processing. Such a resource should make computer-aided food product, process and equipment design one step closer to reality by making the necessary input parameters available in one location and in a format that can be readily used in a simulation software. Several equilibrium, transport and electrical properties are included. The estimation equations for any property are chosen from among the most successful and accurate, staying away from property estimators that have theoretical basis but have not been as successful for food materials. For each property, implementation of its prediction equations in a computer model has also been discussed. Accuracy of each property estimation process have been included from the literature, showing most properties can be estimated to within 10% accuracy, sufficient for modeling purposes. Having such reasonable prediction models has the important implication that unavailability of sufficient data, that is expected to be always true due to the variety and complexity of food materials and processes, is not a bottleneck for computer-aided food process engineering.
The present investigation deals with the modelling and optimization of soybean hydration for facilitating soybean processing and it focuses on maximization of mass gain, water uptake and protein ...retention in the bean. Process variables considered for optimization were: soybean to water ratio (1:2.48 obtained with response surface methodology, RSM, and 1:1.19 obtained with artificial neural network and genetic algorithm, ANN/GA), time (2.0 h using RSM and 8.0 h using ANN/GA) and temperature (40.0°C using RSM and 45.1°C using ANN/GA). The findings in this first report on optimization of soaking conditions for soybean hydration employing response surface methodology, hybrid artificial neural network and genetic algorithms reveal a substantially better alternative to the time-consuming soaking process, extensively practiced in industries, in terms of process time economy. Reasonably accurate neural network model (regression coefficient of 0.9443) was obtained based on the experimental data. The optimized set of process conditions was predicted through genetic algorithm, and the effectiveness of the ANN/GA model, validated through experiments, was indicated by significant correlations (R.sup.2 and mean squared error (MSE) being 0.9380 and 5.9299, respectively). RSM also resulted in accurate models for predicting percentage mass gain, percentage water uptake and percentage protein retention (R.sup.2 and MSE in the range of 0.889-0.9297 and 0.80-4.94, respectively). Key words: response surface methodology (RSM), artificial neural network (ANN), genetic algorithms (GA), soybean soaking
In this study, we extended our previously developed anatomically detailed three-dimensional (3-D) thermoregulatory virtual human model for predicting heat stress to allow for predictions of heat and ...cold stress in one unified model. Starting with the modified Pennes bioheat transfer equation to estimate the spatiotemporal temperature distribution within the body as the underlying modeling structure, we developed a new formulation to characterize the spatial variation of blood temperature between body elements and within the limbs. We also implemented the means to represent heat generated from shivering and skin blood flow that apply to air exposure and water immersion. Then, we performed simulations and validated the model predictions with experimental data from nine studies, representing a wide range of heat- and cold-stress conditions in air and water and physical activities. We observed excellent agreement between model predictions and measured data, with average root mean squared errors of 0.2°C for core temperature, 0.9°C for mean skin temperature, and 27 W for heat from shivering. We found that a spatially varying blood temperature profile within the limbs was crucial to accurately predict core body temperature changes during very cold exposures. Our 3-D thermoregulatory virtual human model consistently predicted the body's thermal state accurately for each of the simulated hot and cold environmental conditions and exertional heat stress. As such, it serves as a reliable tool to assess whole body, localized tissue, and, potentially, organ-specific injury risks, helping develop injury prevention and mitigation strategies in a systematic and expeditious manner.
This work provides a new, unified modeling framework to accurately predict the human body's thermal response to both heat and cold stress caused by environmental conditions and exertional physical activity in one mathematical model. We show that this 3-D anatomically detailed model accurately predicts the spatiotemporal temperature distribution in the body under extreme conditions for exposures to air and water and could be used to help design medical interventions and countermeasures to prevent injuries.
•Microwave drying of a hygroscopic porous material is studied in a fundamental way.•A mechanistic framework for understanding microwave drying is presented.•Different sized spheres are dried in a ...domestic microwave oven at 10% power level.•Elaborate experimental setup is built to measure key process parameters.
To understand the effects of shape, size and property changes in a spherical sample during microwave drying, a fundamentals-based coupled electromagnetics and multiphase porous media model is developed and associated experimental details are described. Microwave drying of different sized spheres is carried out in a domestic microwave oven operating at 10% power level. Maxwell's equations for electromagnetics are solved inside a three dimensional (3D) microwave oven to obtain the electric field distribution inside the oven cavity and the spheres. The drying samples are treated as a porous media consisting of three phases: solid (skeleton), liquid (water) and gas (water vapor and air). Modes of transport for the fluid phases include capillary flow, binary diffusion between vapor and air, gas pressure driven flow and phase change between liquid water and vapor which is spatially distributed. An elaborate experimental system comprising of infrared camera, optical fiber probe and digital balance is built to validate the model in terms of temperature distribution, point temperatures, gas pressure generation and moisture loss from the samples at different times during the drying process. Results, validation, sensitivity analysis and “what-if” scenarios are presented in the companion paper. The work together would provide tremendous benefits when designing and developing microwave drying processes and products through a novel synergy between physics-based modeling and detailed experimentation.
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•A microwave continuous-flow heating system with a screw propeller was developed.•Implicit function and level set methods were used to solve the complex movement.•The EM-field ...distribution was updated with the rotation of the screw propeller.•Multiphysics model with stirring in the microwave continuous-flow reactor is validated.•More uniformity of the final temperature profiles was achieved.
To solve nonuniform heating when microwave energy is applied in a continuous-flow applicator, a microwave heating system with a screw propeller is designed. By introducing the implicit function and level set methods, the electromagnetic heat source input into the temperature field is updated with the rotation of the screw propeller. Combined with Arbitrary Lagrangian-Eulerian Formulation (ALE) machinery, the temperature distribution in the heating process is obtained. Water is taken as the sample in the experiment to verify the computational model. By using the proposed model, we also calculate the temperature distribution of two other commonly used liquids (ethylene glycol and glycerol). To analyze the effect of a screw propeller on heating uniformity, the temperature distribution of the cases with a screw propeller is quantitatively compared to that of the cases without a screw propeller.
•Intermediate sized spheres show significant microwave focusing.•This led to their explosion hallway into their drying process.•Smaller sized spheres undergo uniform and low temperature ...drying.•Capillary diffusion dominates in smaller sized samples.
The coupled electromagnetics and multiphase porous media model, developed in the companion paper, has been applied to the microwave drying of potato spheres. Microwave energy absorption, temperature, pressure and moisture distribution were obtained in 3D samples to gain a comprehensive understanding of the process and address issues such as overheating resulting from microwave focusing. The model was validated against key process parameters and good agreement was found between experimental data and predicted values. The model and experiments demonstrated that the different sized spheres behaved quite differently under similar conditions of drying and general guidelines were obtained for drying sphere-shaped materials. Intermediate sized spheres were found to be more prone to excessive volumetric heating via focusing of microwave energy compared with larger sized spheres. This led to their explosion midway through the drying process; whereas, smaller sized spheres underwent uniform, low temperature drying without any quality loss. Sensitivity analysis showed that the model was highly sensitive to the mass transfer coefficient of the surrounding air inside the microwave oven while intrinsic permeability did not affect moisture loss from the material. This indicated that capillary diffusion is the dominant mode of transport in small sized spheres. Development of this physics-based model would go a long way in making and improving computer-aided design and optimization of microwave drying processes.
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