SFF-Oriented Modeling and Process Planning of Functionally Graded Materials Using a Novel Equal Distance Offset Approach

This paper deals with the modeling and process planning of solid freeform fabrication (SFF) of 3D functionally graded materials (FGMs). A novel approach of representation and process planning of FGMs, termed as equal distance offset (EDO), is developed. In EDO, a neutral arbitrary 3D CAD model is adaptively sliced into a series of 2D layers. Within each layer, 2D material gradients are designed and represented via dividing the 2D shape into several sub-regions enclosed by iso-composition contours. If needed, the material composition gradient within each of sub-regions can be further determined by applying the equal distance offset algorithm to each sub-region. Using this approach, an arbitrary-shaped 3D FGM object with linear or non-linear composition gradients can be represented and fabricated via suitable SFF machines.Mechanical Engineerin

Biomass gasification for syngas and biochar co-production: Energy application and economic evaluation

Syngas and biochar are two main products from biomass gasification. To facilitate the optimization of the energy efficiency and economic viability of gasification systems, a comprehensive fixed-bed gasification model has been developed to predict the product rate and quality of both biochar and syngas. A coupled transient representative particle and fix-bed model was developed to describe the entire fixed-bed in the flow direction of primary air. A three-region approach has been incorporated into the model, which divided the reactor into three regions in terms of different fluid velocity profiles, i.e. natural convection region, mixed convection region, and forced convection region, respectively. The model could provide accurate predictions against experimental data with a deviation generally smaller than 10%. The model is applicable for efficient analysis of fixed-bed biomass gasification under variable operating conditions, such as equivalence ratio, moisture content of feedstock, and air inlet location. The optimal equivalence ratio was found to be 0.25 for maximizing the economic benefits of the gasification process

Modeling Three-dimensional Invasive Solid Tumor Growth in Heterogeneous Microenvironment under Chemotherapy

A systematic understanding of the evolution and growth dynamics of invasive solid tumors in response to different chemotherapy strategies is crucial for the development of individually optimized oncotherapy. Here, we develop a hybrid three-dimensional (3D) computational model that integrates pharmacokinetic model, continuum diffusion-reaction model and discrete cell automaton model to investigate 3D invasive solid tumor growth in heterogeneous microenvironment under chemotherapy. Specifically, we consider the effects of heterogeneous environment on drug diffusion, tumor growth, invasion and the drug-tumor interaction on individual cell level. We employ the hybrid model to investigate the evolution and growth dynamics of avascular invasive solid tumors under different chemotherapy strategies. Our simulations reproduce the well-established observation that constant dosing is generally more effective in suppressing primary tumor growth than periodic dosing, due to the resulting continuous high drug concentration. In highly heterogeneous microenvironment, the malignancy of the tumor is significantly enhanced, leading to inefficiency of chemotherapies. The effects of geometrically-confined microenvironment and non-uniform drug dosing are also investigated. Our computational model, when supplemented with sufficient clinical data, could eventually lead to the development of efficient in silico tools for prognosis and treatment strategy optimization.Comment: 41 pages, 8 figure

Validation and clinical implementation of an accurate Monte Carlo code for pencil beam scanning proton therapy.

Monte Carlo (MC)-based dose calculations are generally superior to analytical dose calculations (ADC) in modeling the dose distribution for proton pencil beam scanning (PBS) treatments. The purpose of this paper is to present a methodology for commissioning and validating an accurate MC code for PBS utilizing a parameterized source model, including an implementation of a range shifter, that can independently check the ADC in commercial treatment planning system (TPS) and fast Monte Carlo dose calculation in opensource platform (MCsquare). The source model parameters (including beam size, angular divergence and energy spread) and protons per MU were extracted and tuned at the nozzle exit by comparing Tool for Particle Simulation (TOPAS) simulations with a series of commissioning measurements using scintillation screen/CCD camera detector and ionization chambers. The range shifter was simulated as an independent object with geometric and material information. The MC calculation platform was validated through comprehensive measurements of single spots, field size factors (FSF) and three-dimensional dose distributions of spread-out Bragg peaks (SOBPs), both without and with the range shifter. Differences in field size factors and absolute output at various depths of SOBPs between measurement and simulation were within 2.2%, with and without a range shifter, indicating an accurate source model. TOPAS was also validated against anthropomorphic lung phantom measurements. Comparison of dose distributions and DVHs for representative liver and lung cases between independent MC and analytical dose calculations from a commercial TPS further highlights the limitations of the ADC in situations of highly heterogeneous geometries. The fast MC platform has been implemented within our clinical practice to provide additional independent dose validation/QA of the commercial ADC for patient plans. Using the independent MC, we can more efficiently commission ADC by reducing the amount of measured data required for low dose "halo" modeling, especially when a range shifter is employed

Optimized normal and distance matching for heterogeneous object modeling

This paper presents a new optimization methodology of material blending for heterogeneous object modeling by matching the material governing features for designing a heterogeneous object. The proposed method establishes point-to-point correspondence represented by a set of connecting lines between two material directrices. To blend the material features between the directrices, a heuristic optimization method developed with the objective is to maximize the sum of the inner products of the unit normals at the end points of the connecting lines and minimize the sum of the lengths of connecting lines. The geometric features with material information are matched to generate non-self-intersecting and non-twisted connecting surfaces. By subdividing the connecting lines into equal number of segments, a series of intermediate piecewise curves are generated to represent the material metamorphosis between the governing material features. Alternatively, a dynamic programming approach developed in our earlier work is presented for comparison purposes. Result and computational efficiency of the proposed heuristic method is also compared with earlier techniques in the literature. Computer interface implementation and illustrative examples are also presented in this paper

Modeling Virus Transport and Removal during Storage and Recovery in Heterogeneous Aquifers

A quantitative understanding of virus removal during aquifer storage and recovery (ASR) in physically and geochemically heterogeneous aquifers is needed to accurately assess human health risks from viral infections. A two-dimensional axisymmetric numerical model incorporating processes of virus attachment, detachment, and inactivation in aqueous and solid phases was developed to systematically evaluate the virus removal performance of ASR schemes. Physical heterogeneity was considered as either layered or randomly distributed hydraulic conductivities (with selected variance and horizontal correlation length). Geochemical heterogeneity in the aquifer was accounted for using Colloid Filtration Theory to predict the spatial distribution of attachment rate coefficient. Simulation results demonstrate that the combined effects of aquifer physical heterogeneity and spatial variability of attachment rate resulted in higher virus concentrations in the recovered water at the ASR well (i.e. reduced virus removal). While the sticking efficiency of viruses to aquifer sediments was found to significantly influence virus concentration in the recovered water, the solid phase inactivation under realistic field conditions combined with the duration of storage phase had a predominant influence on the overall virus removal. The relative importance of physical heterogeneity increased under physicochemical conditions that reduced virus removal (e.g. lower value of sticking efficiency or solid phase inactivation rate). This study provides valuable insight on site selection of ASR projects and an approach to optimize ASR operational parameters (e.g. storage time) for virus removal and to minimize costs associated with post-recovery treatment