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At least 1,405 records · Page 78

Experimental determination of lead carbonate solubility at high ionic strengths: A Pitzer model description

In this article, solubility measurements of lead carbonate, PbCO 3 (cr), cerussite, as a function of total ionic strengths are conducted in the mixtures of NaCl and NaHCO 3 up to I = 1.2 mol•kg –1 and in the mixtures of NaHCO 3 and Na 2 CO 3 up to I = 5.2 mol•kg –1 , at room temperature (22.5 ± 0.5 °C). The solubility constant (log K sp ) for cerussite, PbCO 3 (cr) = Pb 2+ + CO 3 2- was determined as –13.76 ± 0.15 (2σ) with a set of Pitzer parameters describing the specific interactions of PbCO 3 (aq), Pb(CO 3 ) 2 2- , and Pb(CO 3 )Cl – with the bulk-supporting electrolytes, based on the Pitzer model. The model developed in this work can reproduce the experimental results including model-independent solubility values from the literature over a wide range of ionic strengths with satisfactory accuracy. The model is expected to find applications in numerous fields, including the accurate description of chemical behavior of lead in geological repositories, the modeling of formation of oxidized Pb–Zn ore deposits, and the environmental remediation of lead contamination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Micro-Mechanism-Based Continuum Corrosion Fatigue Damage Model for Steels

A micro-mechanism-based corrosion fatigue damage model is developed for studying the high-cycle corrosion fatigue of steel from multi-scale viewpoint. The developed physical corrosion fatigue damage model establishes micro-macro relationships between macroscopic continuum damage evolution and collective evolution behavior of microscopic pits and cracks, which can be used to describe the multi-scale corrosion fatigue process of steel. As a case study, the model is used to predict continuum damage evolution and number density of the corrosion pit and short crack of steel component in 5% NaCl water under constant stress amplitude at 20 kHz, and the numerical results are compared with experimental results. It shows that the model is effective and can be used to evaluate the continuum macroscopic corrosion fatigue damage and study microscopic corrosion fatigue mechanisms of steel.

36 MATERIALS SCIENCE↗

Predicting Sintering Window of Binder Jet Additively Manufactured Parts Using a Coupled Data Analytics and CALPHAD Approach

Batch-to-batch variation in powder compositions for binder jet additive manufacturing (BJAM) can significantly deter defining an “ideal” sintering window for a given alloy. One way to overcome the problem is by running sintering experiments at various temperatures for each batch of the powder. However, such an approach increases the time required to achieve large-scale production of parts. The predictive capabilities of computational thermodynamic tools like CALPHAD can be leveraged to overcome the challenge, especially for binder jet additive manufacturing, since the process occurs under near-equilibrium conditions. However, calculating the sintering window using CALPHAD can be computationally expensive, considering many possible feedstock compositions within “specification”. Here, we generate high throughput CALPHAD data for nickel-based superalloys to develop machine learning models to predict the sintering window rapidly. The predictive capability of the models has been validated using published results on BJAM of Inconel 718 and 625. Further, validated models are lightweight and can be deployed in an industrial setting to get sintering window in an accelerated manner.

36 MATERIALS SCIENCE↗

Kinetics and morphological evolution of liquid metal dealloying

Liquid metal dealloying (LMD) has recently emerged as a novel technique to fabricate bulk nanostructures using a bottom-up self-organization method, but the literature lacks fundamental studies of this kinetic process. In this work, we conduct an in-depth study of the kinetics and fundamental microstructure evolution mechanisms during LMD using Tisingle bondTa alloys immersed in molten Cu as a model system. We develop a model of LMD kinetics based on a quantitative characterization of the effects of key parameters in our system including alloy composition, dealloying duration, and dealloying temperature. Further, this work demonstrates that the dealloying interface is at or near equilibrium during LMD, and that the rate-limiting step is the liquid-state diffusion of dissolving atoms away from the dealloying interface (diffusion-limited kinetics). The quantitative comparison between theoretically predicted and measured dealloying rates further reveals that convective transport and rejection of the dissolving element during coarsening of the structure also influence the dealloying kinetics.

36 MATERIALS SCIENCE↗

The role of elastic and plastic anisotropy in intergranular spall failure

Recent mesoscale experimental observations of dynamic ductile failure have demonstrated a strong relationship between grain boundary (GB) misorientation and the likelihood of failure initiation along said GB. This correlation has been attributed to inherent GB weakness of particular misorientation. Here we discuss the role played by mechanics, i.e. elastic and plastic anisotropy, on the experimental observation. We make use of a recently developed framework for modeling dislocation-based crystal plasticity and ductile failure of single crystals under dynamic loading (CPD-FE). Polycrystals are studied at the mesoscale level through the explicit resolution of individual grains, i.e. resolving each individual grain's size, shape, and orientation. In our simulations, failure naturally localizes along the GBs with no necessity for ad hoc rules governing damage nucleation. We carry out a few thousand mesoscale calculations, systematically varying the misorientation angles of the GB in the computational microstructure. Despite the fact that we neglect the possibility of variations in inherent GB weakness, our simulations agree favorably with the experimental observations, implying that stress concentration generated by elastic and plastic anisotropies across GBs is a dominant governing factor in this phenomenon. Lastly, we find that misorientation angle is an insufficient GB descriptor to predict the likelihood of intergranular spall failure, which is better understood through the consideration of additional GB degrees of freedom.

36 MATERIALS SCIENCE↗

Techno-economic optimization of shale gas to dimethyl ether production processes via direct and indirect synthesis routes

The shale gas to dimethyl ether process via direct synthesis route with a syngas H2/CO=1 has a higher dimethyl ether yield than that via indirect synthesis route. However, the direct synthesis route involves various energy and capital-intensive processes, such as the complicated dimethyl ether separation process, and the CO2 recycle and comprssion process. In this study, a techno-economic analysis of the shale gas to dimethyl ether process via direct and indirect synthesis routes is performed using Aspen Process Economic Analyzer based on the rigorous process model developed in Aspen Plus. Effects of different CO2 removal technologies and dimethyl ether synthesis technologies from syngas are evaluated. Both, direct and indirect plants are optimized in Aspen Plus equation-oriented environment using the rigorous process models. The effects of key design parameters (i.e. H2/CO in the syngas) as well as investment parameters (i.e. prices of raw materials, products, and utilities, plant scale) on the process economics as been evaluated. The direct dimethyl ether synthesis route processing a syngas with H2/CO =1 and using the Rectisol process for CO2 capture has the highest overall thermal efficiency on the lower heat value basis is found to be much lower than the current U.S. market diesel price indicating the feasibility of the process.

Mevawala, Chirag↗

Predictive modeling of a subcritical pulverized-coal power plant for optimization: Parameter estimation, validation, and application

As renewable power generation deployment increases, fossil fuel plants are increasingly required to operate more flexibly. Many coal-fired power plants were originally designed to operate at base load and do not operate optimally at partial load. Predictive first-principles plant-wide models can be employed to identify opportunities for flexibility improvements and diagnose low-load operating issues. This paper describes the application of the Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES) to model and optimize flexible power plant operations. The key benefits of using IDAES are that it provides an open-source, fully equation-oriented modeling framework for efficient modular model construction, reuse, and customization, together with a mathematical optimization framework leveraging powerful, state-of-the-art solvers. The process systems engineering workflow from predictive process simulation to parameter estimation, model validation, and plant optimization is applicable to a variety of existing and next-generation energy systems as well as other chemical and environmental processes. Here, to demonstrate this capability, a physics-based, steady-state model was developed to improve full- and part-load performance of the Escalante Generating Station, a 245 MWe (net) subcritical pulverized coal-fired power plant owned and operated by Tri-State Generation and Transmission Association. Specifically, sixty-nine model parameters were simultaneously estimated from several months of operating data enabling prediction of flow rates, temperatures, pressures, and steam quality throughout the plant. The validated model was leveraged by Escalante to reduce the minimum operating load from 90 MW to 50 MW by diagnosing a low-load water-hammer issue, enabling coal usage and emissions reductions during periods of low power demand. Additionally, opportunities for heat rate reduction (i.e., efficiency improvement) through a steeper sliding-pressure approach to load-following and optimization of other boiler operating variables were also identified and quantified. For example, a potential efficiency improvement of 0.7 percentage points was observed at half-load operation.

01 COAL, LIGNITE, AND PEAT↗

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nurr1 overexpression exerts neuroprotective and anti-inflammatory roles via down-regulating CCL2 expression in both in vivo and in vitro Parkinson's disease models

The abnormality of nuclear receptor-related protein 1 (Nurr1) in expression and function can contribute to neurodegeneration of dopaminergic neurons and occurrence of Parkinson's disease (PD). However, its related mechanism in PD is still unknown. In this study, we found that Nurr1 was down-regulated and CCL2 was up-regulated in PD patients and PD mice. CCL2 promoted apoptosis and secretion of TNF-α and IL-1β in SH-SY5Y cells and inhibited cell viability while knockdown of CCL2 exerted the opposite effects. Nurr1 overexpression inhibited apoptosis, the release of TNF-α and IL-1β and promoted viability in α-Syn-treated SH-SY5Y cells, which was markedly promoted by CCL2 antibody and dramatically reversed by CCL2. Nurr1 overexpression negatively regulated CCL2 expression in vivo and in vitro. Furthermore, Nurr1 overexpression remarkably relieved MPTP-induced movement disorder and spatial memory deficits and played neuroprotective and anti-inflammatory roles in MPTP-induced PD mice by down-regulating CCL2 in vivo. In conclusion, Nurr1 overexpression exerts neuroprotective and anti-inflammatory roles via down-regulating CCL2 in both in vivo and in vitro PD models, contributing to developing mechanism-based and neuroprotective strategies against PD. - Highlights: • Nurr1 was down-regulated and CCL2 was up-regulated in PD patients and PD mice. • Nurr1 overexpression inhibited apoptosis, release of TNF-α and IL-1β and promoted viability in α-Syn-treated SH-SY5Y cells. • CCL2 reversed the effect of Nurr1 overexpression on apoptosis, inflammatory cytokines secretion and viability. • Nurr1 overexpression negatively regulated CCL2 expression in vivo and in vitro. • Nurr1 overexpression remarkably relieved MPTP-induced movement disorder and spatial memory deficits.

60 APPLIED LIFE SCIENCES↗

PANNA: Properties from Artificial Neural Network Architectures

We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Prediction of the visual impact of motorways using GIS

Large scale transportation projects can adversely affect the visual perception of environmental quality and require adequate visual impact assessment. In this study, we investigated the effects of the characteristics of the road project and the character of the existing landscape on the perceived visual impact of motorways, and developed a GIS-based prediction model based on the findings. An online survey using computer-visualised scenes of different motorway and landscape scenarios was carried out to obtain perception-based judgements on the visual impact. Motorway scenarios simulated included the baseline scenario without road, original motorway, motorways with timber noise barriers, transparent noise barriers and tree screen; different landscape scenarios were created by changing land cover of buildings and trees in three distance zones. The landscape content of each scene was measured in GIS. The result shows that presence of a motorway especially with the timber barrier significantly decreases the visual quality of the view. The resulted visual impact tends to be lower where it is less visually pleasant with more buildings in the view, and can be slightly reduced by the visual absorption effect of the scattered trees between the motorway and the viewpoint. Based on the survey result, eleven predictors were identified for the visual impact prediction model which was applied in GIS to generate maps of visual impact of motorways in different scenarios. The proposed prediction model can be used to achieve efficient and reliable assessment of visual impact of motorways. - Highlights: • Motorways induce significant visual impact especially with timber noise barriers. • Visual impact is negatively correlated with amount of buildings in the view. • Visual impact is positively correlated with percentage of trees in the view. • Perception-based motorway visual impact prediction model using mapped predictors • Predicted visual impacts in different scenarios are mapped in GIS.

54 ENVIRONMENTAL SCIENCES↗

Flow behavior of hydraulic fractured tight formations considering Pre-Darcy flow using EDFM

For tight reservoirs/formations, flow in fracture and matrix obey different flow patterns. Pre-Darcy flow always exists in low permeability subsurface porous media while Darcy flow can be applied in fracture. It is an outstanding challenge to understand the flow behavior coupling different flow mechanisms. As numerical simulation can predict field-scale performance so the development of efficient simulation method becomes a key issue to evaluate the flow behavior. In this paper, we develop an improved discrete fracture model based on the widely used embedded discrete facture model (EDFM) to simulate the transport both in homogenous and heterogeneous porous media in the presence of Pre-Darcy flow. The conservation equations are derived for fracture and matrix firstly and then discretized by fully implicit method. The transmissibility of different connection types is defined and the detailed calculation workflow is presented as well. The proposed model is verified through the comparison with the model using local grid refined (LGR) method. It is discovered that our simulation method exhibits good accuracy when analyzing the effect of Pre-Darcy flow. Some examples are shown including 1D scalar transport, 2D heterogeneous, 3D flow, complex fracture system and multiple well system problems with fully-coupled flow in fracture and matrix. The pressure distribution and well flux are demonstrated to analyze the Pre-Darcy flow characteristics. Results indicate that the new model works robustly for different flow problems which provide further insight into the Pre-Darcy flow in low permeability media.

02 PETROLEUM↗

Warming rate drives microbial nutrient demand and enzyme expression during peat decomposition

Recent developments of enzyme-based decomposition models highlight the importance of enzyme kinetics with warming, but most modeling exercises are based on studies with a step-wise warming. This approach may mask the effect of temperature in controlling in-situ activities as in most ecosystems the rate of warming is more gradual than these step warming studies. We conducted an experiment to test the effects of contrasting warming rates on the kinetics of carbon (C), nitrogen (N), and phosphorus (P) degradation enzymes in subtropical peat soils. We also wanted to evaluate if the stoichiometry of enzyme kinetics shifts under contrasting warming rates and if so, how does it relate to the stoichiometry in microbial biomass. Contrasting warming rates altered microbial biomass stoichiometry leading to differing patterns of microbial demand for C vs. nutrient (N and P) and enzyme expression following the optimum foraging strategy. Activity (higher Vmax) and efficiency (lower Km) of C acquisition enzymes were greater in the step treatment; however, expressions of nutrient (N and P) acquiring enzymes were enhanced in the ramp treatment at the end of the experiment. In the step treatment, there was a typical pattern of an initial peak in the Vmax and drop in the Km for all enzyme groups followed by later adjustments. On the other hand, a consistent increase in Vmax and decline in Km of all enzyme groups were observed in the ramp treatment. These changes were sufficient to alter microbial identity (as indicated by enzyme Km and biomass stoichiometry) with two apparently different endpoints under contrasting warming rates. This observation resembles the concept of alternate stable states and highlights a need for improved representation of warming effects on enzymes in decomposition models. Using peat soils of Florida Everglades, here we have demonstrated that contrasting warming rates can influence the dynamics of microbial and enzymatic kinetics. Hence, we suggest that future laboratory and field warming studies could consider our approach to accurately represent microbial and enzymatic kinetics in biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗

Cyclic loading–unloading impacts on geomechanical stability of multiple salt caverns for underground hydrogen storage

Underground caverns in a salt dome are promising geologic features to store hydrogen because of salt’s extremely low permeability and self-healing behavior. The salt cavern storage community, however, has not fully understood the geomechanical behaviors of salt rock driven by quick operation cycles of injection–production, which may significantly impact the cost-effective storage-recovery performance of multiple caverns. Our field-scale generic model captures the impact of cyclic loading–unloading on the salt creep behavior and deformation under different cycle frequencies, operating pressure, and spatial order of operating cavern(s). This systematic simulation study indicates that the initial operation cycle and arrangement of multiple caverns play a significant role in the creep-driven loss of cavern volumes and cavern deformation. Finally, our future study will develop a new salt constitutive model based on geomechanical tests of site-specific salt rock to probe the cyclic behaviors of salt precisely both beneath and above the dilatancy boundary, including reverse (inverse transient) creep, the Bauschinger effect, and damage-healing mechanism.

08 HYDROGEN↗

Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic FFT-based framework for predicting ductile fracture in 3D polycrystalline materials

Ductile materials, such as metal alloys, can undergo substantial deformation before failure. Additionally, these materials are usually of polycrystalline composition and exhibit strongly anisotropic behavior at small length scales. Previously developed fast Fourier transform (FFT)-based models can model ductile fracture of isotropic materials or the elastic–plastic behavior of anisotropic polycrystalline materials; however, there remains a need to couple both capabilities. This work extends a large-strain FFT-based crystal plasticity model to simulate ductile fracture of polycrystalline materials. In this work, a triaxiality-based continuum damage mechanics (CDM) formulation is incorporated into a large-strain elasto-viscoplastic FFT (LS-EVPFFT) framework. The CDM formulation is augmented with an integral-based nonlocal regularization approach that correctly handles gas-phase material necessary to model unconstrained surfaces. To validate the damage-enabled LS-EVPFFT framework, mesoscale copper tensile coupons were machined using microwire electrical discharge machining and experimentally characterized using electron backscatter diffraction. In-situ optical digital image correlation was performed during uniaxial testing to provide a side-by-side comparison of the experimental and computational strain fields and stress–strain responses. The damage-enabled LS-EVPFFT framework can simulate the complete macroscopic stress–strain response of ductile polycrystals to failure. The model reproduces necking behavior that qualitatively agrees with experimental observations. By leveraging the relatively low computational cost of the damage-enabled LS-EVPFFT framework, the framework presented here allows the ductile fracture response of 3D polycrystalline materials to be tractably predicted.

36 MATERIALS SCIENCE↗

Examining deformation localization of irradiated tungsten under uniaxial compression with crystal plasticity

In this work, the deformation behavior of irradiated tungsten at elevated service temperatures is examined using mechanism-based crystal plasticity finite element framework by considering multiple mechanisms, including thermal softening and irradiation hardening. The previously developed mechanism-based crystal plasticity model is first utilized to assess the yield stress of unirradiated and irradiated tungsten upon low-temperature irradiation. Additionally, the engineering stress-strain response under uniaxial compression is then predicted by considering the effect of irradiation-induced defect clusters on the motion of deformation-induced dislocations, and the predicted results agree well with the experimental measurements. More importantly, the formation and evolution of plastic strain localization zones in the form of shear bands are qualitatively captured, and the maximal principal strain distribution is quantitatively linked to the dose of irradiation damage. Finally, the deformation-induced shear band as a result of plastic instability in the compressed tungsten specimen is discussed.

36 MATERIALS SCIENCE↗

Interfraction Liver Shape Variability and Impact on GTV Position During Liver Stereotactic Radiotherapy Using Abdominal Compression

Purpose: For patients receiving liver stereotactic body radiotherapy (SBRT), abdominal compression can reduce organ motion, and daily image guidance can reduce setup error. The reproducibility of liver shape under compression may impact treatment delivery accuracy. The purpose of this study was to measure the interfractional variability in liver shape under compression, after best-fit rigid liver-to-liver registration from kilovoltage (kV) cone beam computed tomography (CBCT) scans to planning computed tomography (CT) scans and its impact on gross tumor volume (GTV) position. Methods and Materials: Evaluable patients were treated in a Research Ethics Board-approved SBRT six-fraction study with abdominal compression. Kilovoltage CBCT scans were acquired before treatment and reconstructed as respiratory sorted CBCT scans offline. Manual rigid liver-to-liver registrations were performed from exhale-phase CBCT scans to exhale planning CT scans. Each CBCT liver was contoured, exported, and compared with the planning CT scan for spatial differences, by use of in house-developed finite-element model-based deformable registration (MORFEUS). Results: We evaluated 83 CBCT scans from 16 patients with 30 GTVs. The mean volume of liver that deformed by greater than 3 mm was 21.7%. Excluding 1 outlier, the maximum volume that deformed by greater than 3 mm was 36.3% in a single patient. Over all patients, the absolute maximum deformations in the left-right (LR), anterior-posterior (AP), and superior-inferior directions were 10.5 mm (SD, 2.2), 12.9 mm (SD, 3.6), and 5.6 mm (SD, 2.7), respectively. The absolute mean predicted impact of liver volume displacements on GTV by use of center of mass displacements was 0.09 mm (SD, 0.13), 0.13 mm (SD, 0.18), and 0.08 mm (SD, 0.07) in the left-right, anterior-posterior, and superior-inferior directions, respectively. Conclusions: Interfraction liver deformations in patients undergoing SBRT under abdominal compression after rigid liver-to-liver registrations on respiratory sorted CBCT scans were small in most patients (<5 mm).

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accurate Analysis of the Change in Volume, Location, and Shape of Metastatic Cervical Lymph Nodes During Radiotherapy

Purpose: To establish a method for the accurate acquisition and analysis of the variations in tumor volume, location, and three-dimensional (3D) shape of tumors during radiotherapy in the era of image-guided radiotherapy. Methods and Materials: Finite element models of lymph nodes were developed based on computed tomography (CT) images taken before the start of treatment and every week during the treatment period. A surface geometry map with a volumetric scale was adopted and used for the analysis. Six metastatic cervical lymph nodes, 3.5 to 55.1 cm{sup 3} before treatment, in 6 patients with head and neck carcinomas were analyzed in this study. Three fiducial markers implanted in mouthpieces were used for the fusion of CT images. Changes in the location of the lymph nodes were measured on the basis of these fiducial markers. Results: The surface geometry maps showed convex regions in red and concave regions in blue to ensure that the characteristics of the 3D tumor geometries are simply understood visually. After the irradiation of 66 to 70 Gy in 2 Gy daily doses, the patterns of the colors had not changed significantly, and the maps before and during treatment were strongly correlated (average correlation coefficient was 0.808), suggesting that the tumors shrank uniformly, maintaining the original characteristics of the shapes in all 6 patients. The movement of the gravitational center of the lymph nodes during the treatment period was everywhere less than {+-}5 mm except in 1 patient, in whom the change reached nearly 10 mm. Conclusions: The surface geometry map was useful for an accurate evaluation of the changes in volume and 3D shapes of metastatic lymph nodes. The fusion of the initial and follow-up CT images based on fiducial markers enabled an analysis of changes in the location of the targets. Metastatic cervical lymph nodes in patients were suggested to decrease in size without significant changes in the 3D shape during radiotherapy. The movements of the gravitational center of the lymph nodes were almost all less than {+-}5 mm.

62 RADIOLOGY AND NUCLEAR MEDICINE↗