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At least 1,405 records · Page 78

A two-step model of TiO{sub 2} nanoparticle toxicity in human liver tissue

We examine the toxicity of titanium dioxide (TiO{sub 2}) nanoparticles on human liver through a two-step approach, including a physiologically-based pharmacokinetic (PBPK) model and a cell-response model. The PBPK model predicts the bio-distribution of nanoparticles that remain in the human body after exposure, with special attention to their accumulation in liver tissue. The cell-response model predicts liver cell death as a consequence of the accumulated TiO{sub 2} nanoparticles by considering cell fate dynamics through the interplay between cellular uptake of the nanoparticles and their dilution due to cell division. The results suggest that tissue damage from a low nanoparticle dose is negligible due to renewal cell division, but for higher doses larger fractions of cells must participate in the cell cycle to recover the original tissue mass. By combining the two models, it becomes possible to explain the liver cell viability and cell death after TiO{sub 2} nanoparticle exposure. - Highlights: • The cell-response model is proposed to study hepatotoxicity of TiO{sub 2} nanoparticles in the cellular level. • The model explains how the cell population responds to the deposited nanoparticles. • For low nanoparticle doses, tissue damage is negligible due to renewal through cell division. • For larger doses, larger fractions of cells must participate in the cell cycle to recover the original tissue mass.

60 APPLIED LIFE SCIENCES↗

Predicting metal–metal interactions. I. The influence of strain on nanoparticle and metal adlayer stabilities

Strain-engineering of bimetallic nanomaterials is an important design strategy for developing new catalysts. In this paper, we introduce an approach for including strain effects into a recently introduced, density functional theory (DFT)-based alloy stability model. The model predicts adsorption site stabilities in nanoparticles and connects these site stabilities with catalytic reactivity and selectivity. Strain-based dependencies will increase the model’s accuracy for nanoparticles affected by finite-size effects. In addition to the stability of small nanoparticles, strain also influences the heat of adsorption of epitaxially grown metal-on-metal adlayers. In this respect, we successfully benchmark the strain-including alloy stability model with previous experimentally determined trends in the heats of adsorption of Au and Cu adlayers on Pt (111). For these systems, our model predicts stronger bimetallic interactions in the first monolayer than monometallic interactions in the second monolayer. We explicitly quantify the interplay between destabilizing strain effects and the energy gained by forming new metal–metal bonds. While tensile strain in the first Cu monolayer significantly destabilizes the adsorption strength, compressive strain in the first Au monolayer has a minimal impact on the heat of adsorption. Hence, this study introduces and, by comparison with previous experiments, validates an efficient DFT-based approach for strain-engineering the stability, and, in turn, the catalytic performance, of active sites in bimetallic alloys with atomic level resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Damped Ly α absorbers and atomic hydrogen in galaxies: the view of the GAEA model

ABSTRACT Using the GAEA semi-analytic model, we analyse the connection between Damped Ly α systems (DLAs) and H i in galaxies. Our state-of-the-art semi-analytic model is tuned to reproduce the local galaxy H i mass function, and that also reproduces other important galaxy properties, including the galaxy mass–gas metallicity relation. To produce catalogues of simulated DLAs we throw 105 random lines of sight in a composite simulated volume: dark matter haloes with log$(\frac{M_{200}}{ {\rm M}_{\odot }}) \ge 11.5$ are extracted from the Millennium Simulation, while for $9.2 \le \log (\frac{M_{200}}{ \mathrm{M}_{\odot }})\lt 11.5$ we use the Millennium II, and for $8 \le \log (\frac{M_{200}}{\mathrm{M}_{\odot }}) \lt 9.2$ a halo occupation distribution model. At 2 < z < 3, where observational data are more accurate, our fiducial model predicts the correct shape of the column density distribution function, but its normalization falls short of the observations, with the discrepancy increasing at higher redshift. The agreement with observations is significantly improved increasing both the H i masses and the disc radii of model galaxies by a factor of 2, as implemented ‘a posteriori’ in our 2M−2R model. In the redshift range of interest, haloes with $M_{200} \ge {10}^{11} \, \mathrm{M}_{\odot }$ give the major contribution to ΩDLA, and the typical DLA host halo mass is $\sim \!{10}^{11} \, \mathrm{M}_{\odot }$. The simulated DLA metallicity distribution is in relatively good agreement with observations, but our model predicts an excess of DLAs at low metallicities. Our results suggest possible improvements for the adopted modelling of the filtering mass and metal ejection in low-mass haloes.

Di Gioia, Serafina↗

Investigation of heat transport using directly driven gold spheres

Recently, heat transport was investigated using a directly driven beryllium sphere [Farmer et al., Phys. Plasmas 27, 082701 (2020)]. Models that overly restrict heat transport were rejected. This paper extends work to directly driven gold spheres where radiation loss is more important. Here, gold coated spheres are directly driven at the OMEGA laser facility at intensities of 5×10 14 W/cm 2 . Plasma conditions, laser coupling, and x-ray flux are all measured. Additionally, comparisons to 2D radiation-hydrodynamic simulations are performed. Simulations use three common heat transport models: local transport with flux limiters of f = 0.15 and f = 0.03, and the nonlocal Schurtz–Nicolai–Busquet (SNB) model. It is shown that both the SNB model and f = 0.15 match the measured plasma conditions with the SNB model better capturing the temporal evolution of electron temperature. The f = 0.03 model predicts too low of an electron density and too hot of a temperature. The measured scattered light is roughly 6% of the incident energy, the f = 0.15 and SNB models predict 0.5% uncoupled light, and f = 0.03, 38% uncoupled light. The x-ray fluxes in the f = 0.15 and SNB simulations rise too quickly and are just outside the measurement's error, while the x-ray flux in the f = 0.03 simulation is low by a factor of two-three. For these reasons, the f = 0.03 model is rejected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reversal of Increasing Tropical Ocean Hypoxia Trends With Sustained Climate Warming

Dissolved oxygen (O 2 ) is essential for the survival of marine animals. Climate change impacts on future oxygen distributions could modify species biogeography, trophic interactions, biodiversity, and biogeochemistry. The Coupled Model Intercomparison Project Phase 5 models predict a decreasing trend in marine O 2 over the 21st century. Here we show that this increasing hypoxia trend reverses in the tropics after 2100 in the Community Earth System Model forced by atmospheric CO 2 from the Representative Concentration Pathway 8.5 and Extended Concentration Pathway 8.5. In tropical intermediate waters between 200 and 1,000 m, the model predicts a steady decline of O 2 and an expansion of oxygen minimum zones (OMZs) during the 21st century. By 2150, however, the trend reverses with oxygen concentration increasing and OMZ volume shrinking through 2300. A novel five-box model approach in conjunction with output from the full Earth system model is used to separate the contributions of biological and physical processes to the trends in tropical oxygen. The tropical O 2 recovery is caused mainly by reductions in tropical biological export, coupled with a modest increase in ventilation after 2200. The time-evolving oxygen distribution impacts marine nitrogen cycling, with potentially important climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Application of Physiologically Based Pharmacokinetic Modeling to Predict Acetaminophen Metabolism and Pharmacokinetics in Children

Acetaminophen (APAP) is a widely used analgesic and antipyretic drug that undergoes extensive phase I and II metabolism. To better understand the kinetics of this process and to characterize the dynamic changes in metabolism and pharmacokinetics (PK) between children and adults, we developed a physiologically based PK (PBPK) model for APAP integrating in silico, in vitro, and in vivo PK data into a single model. The model was developed and qualified for adults and subsequently expanded for application in children by accounting for maturational changes from birth. Once developed and qualified, it was able to predict clinical PK data in neonates (0–28 days), infants (29 days to <2 years), children (2 to <12 years), and adolescents (12–17 years) following intravenous and orally administered APAP. This approach represents a general strategy for projecting drug exposure in children, in the absence of pediatric PK information, using previous drug- and system-specific information of adults and children through PBPK modeling.

60 APPLIED LIFE SCIENCES↗

An Analytical Model for Predicting Turn-ON Overshoot in Normally-OFF GaN HEMTs

Recently, a major challenge in the adoption of wide bandgap semiconductors for power electronic applications is the need to trade device performance for device safety. In this article, methods for predicting gate voltage overshoot in normally-OFF gallium nitride (GAN) high electron mobility transistors (HEMTs) are derived in order to deliver optimal device performance. Two models are proposed; a simple, yet less accurate second order model and a complex, yet more accurate fourth order model. These models allow for the calculation of gate resistances necessary for a desired amount of gate voltage overshoot. The nonlinear capacitances of the device are considered in the analysis. The models are validated with an experimental double-pulse tester. Furthermore, these newly developed models allow design engineers to extract the best possible performance of commercially available GaN devices while keeping the devices in their safe-operating region.

42 ENGINEERING↗

RELAP5-3D Modeling of High Temperature Test Facility (HTTF) Test PG-26

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled nuclear reactors with prismatic fuel and reflector blocks. Several tests have been completed, and more are still planned to at the HTTF, including depressurized conduction cooldown (DCC) and pressurized conduction cooldown (PCC) transients. This report analyses test PG-26, a progression of the Double Ended Inlet-Outlet Crossover Duct Break transient that is referred to as a DCC. PG-26 has been performed at the HTTF between May 30 and June 30, 2019. Core initial conditions (i.e., before the DCC started) have been met using low power (<100 kW) and two of ten available electric heaters. The DCC transient was initiated during the 50 th hour of the test. The break valves were opened, and hot helium from the core and cold helium from the reactor cavity simulation tank (RCST) started mixing. The gases flowed in a countercurrent fashion, where the top half of the hot duct contained hot helium that flowed in one direction and cold helium that flowed in the other direction in the bottom half of the duct. After the pressure and density reached equilibrium, the event entered a diffusion mode. The onset of a reverse natural circulation was not observed during the DCC period of the test. Version 4.4.2ie of the RELAP5-3D computer code has been used to model the HTTF PG-26 test, and results have been compared to available high-quality measured data. The model used in this study is the quality-controlled HTTF RELAP5-3D model (HTTF base 2018-04-19 QA), originally developed by P. Bayless. The report includes RELAP5-3D results of the “base calculations” as well as some sensitivities to important uncertain model inputs, such as primary helium mass flow rate, core ceramic thermal properties, as well as heat evacuation and loop friction models. Using the base RELAP5-3D model predicts a countercurrent helium flow in the hot duct observed at the beginning of the DCC, but instead of going into a molecular diffusion mode, the model predicts the onset of natural convection. Increasing friction in the core and hot duct prevents the natural convection from happening in some of the simulations. Although some temperatures are well predicted (and even overpredicted), the general tendency is to underpredict the ceramic and helium temperatures and heat removal rates during the DCC, resulting in many of the assessment findings being in minimal or insufficient agreement with the data. It is worth noting that the described discrepancies between measured data and RELAP5-3D predictions are not RELAP5-3D code limitations. More so, they reflect limitations in boundary condition and thermal property knowledge. While the RELAP5-3D calculations of the test provide some insights into what happens during the transient, and point to missing or potentially uncertain data to which the experimenters can direct their attention, the principal conclusion is that the PG-26 test data are insufficient for a system code assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)

The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian “supersites” were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: https://doi.org/10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: https://doi.org/10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: https://doi.org/10.21343/m16p-pq17, O'Connor, 2023; Utqiagvik: https://doi.org/10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: https://doi.org/10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: https://doi.org/10.21343/y89m-6393, Holt, 2023; and Eureka: https://doi.org/10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models.

54 ENVIRONMENTAL SCIENCES↗

A predictive analytic model for the solar modulation of cosmic rays

An important factor limiting our ability to understand the production and propagation of cosmic rays pertains to the effects of heliospheric forces, commonly known as solar modulation. The solar wind is capable of generating time- and charge-dependent effects on the spectrum and intensity of low-energy (≲10 GeV) cosmic rays reaching Earth. Previous analytic treatments of solar modulation have utilized the force-field approximation, in which a simple potential is adopted whose amplitude is selected to best fit the cosmic-ray data taken over a given period of time. Making use of recently available cosmic-ray data from the Voyager 1 spacecraft, along with measurements of the heliospheric magnetic field and solar wind, we construct a time-, charge- and rigidity-dependent model of solar modulation that can be directly compared to data from a variety of cosmic-ray experiments. Here, we provide a simple analytic formula that can be easily utilized in a variety of applications, allowing us to better predict the effects of solar modulation and reduce the number of free parameters involved in cosmic-ray propagation models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered images were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction.

60 APPLIED LIFE SCIENCES↗

A microstructure-based modeling approach to predict the mechanical properties of Zr alloy with hydride precipitates

In nuclear reactors, hydrides can form in fuel cladding due to hydrogen absorption in ZIrcaloy and cause embrittlement. This work presents a microstructure-based finite element model to predict the stress-strain response of Zircaloy containing hydrides. Quantitative microstructural details extracted from scanning electron microscopy (SEM) images were used to generate heterogeneous microstructures including the morphology and spatial distribution of hydrides. The constitutive material model for zircaloy in this study is based on crystal plasticity theory which considers the hexagonal close-packed (HCP) atomic structure of Zircaloy material. The hydrides were modeled as brittle material along with a damage model. Hydride formation inside the zircoloy matrix results in residual stress. This phenomenon is also captured in this model. A parametric study has been conducted to understand the effect of volume fraction, orientation, and lamellae thickness of the hydride phase on the mechanical properties of the overall material.

Kulkarni, Shank S.↗

Improved Compaction Experiments and Modeling of Waste Isolation Pilot Plant Standard, Non-degraded, Waste Containers

A credible simulation of disposal room porosity at the Waste Isolation Pilot Plant (WIPP) requires a tenable compaction model for the 55-gallon waste containers within the room. A review of the legacy waste material model, however, revealed several out-of-date and untested assumptions that could affect the model’s compaction behavior. For example, the legacy model predicted non-physical tensile out-of-plane stresses under plane strain compression. (Plane strain compression is similar to waste compaction in the middle of a long drift.) Consequently, a suite of new compaction experiments were performed on containers filled with surrogate, non-degraded, waste. The new experiments involved uniaxial, triaxial, and hydrostatic compaction tests on quarter-scale and full-scale containers. Special effort was made to measure the volume strain during uniaxial and triaxial tests, so that the lateral strain could be inferred from the axial and volume strain. These experimental measurements were then used to calibrate a pressure dependent, viscoplastic, constitutive model for the homogenized compaction behavior of the waste containers. This new waste material model’s predictions agreed far better with the experimental measurements than the legacy model’s predictions, especially under triaxial and hydrostatic conditions. Under plane strain compression, the new model predicted reasonable compressive out-of-plane stresses, instead of tensile stresses. Moreover, the new model’s plane strain behavior was substantially weaker for the same strain, yet substantially stronger for the same porosity, than the legacy model’s behavior. Although room for improvement exists, the new model appears ready for prudent engineering use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Asymmetries at the Tevatron

In this report, we summarize the latest results of the top-quark pair production asymmetry and present the new result of bottom-quark pair production asymmetry. By looking at the results obtained by the CDF experiment, one can see a discrepancy in both $t\bar{t}$ inclusive and lepton-based measurements. The D0 results of the $t\bar{t}$ production asymmetry are compatible with the standard-model predictions as well as with the CDF results. The CDF measurement of $b\bar{b}$ production asymmetry presents consistency with both zero and with the standard-model predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at $0.06/kW-hr LCOE, energy conversion efficiency > 50%, and total power block cost < $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗

Physics based Reliability Models for Supercritical CO 2 Turbomachinery Components

CSP plants using sCO 2 power cycle can potentially achieve high thermal conversion efficiency at low capital cost due to compact turbo-machinery and other components. An sCO 2 expander and improved heat exchanger is expected to provide a major stepping stone for achieving CSP power at 0.06/kW-hr LCOE, energy conversion efficiency > 50 % ,and total power block cost< $1,200/kW installed. Hybrid gas bearings (HGB) and Dry gas seals (DGS) are two key components that are critical for robust and efficient operation of future sCO 2 power cycles. From a system perspective, HGBs can provide substantial benefits (~3 to 5%) to the modular CSP operation, while use of DGSs limits the leakage losses as well as the windage losses in the generator and can increase overall generator efficiency by ~ 8%. The life limiting mechanisms of HGBs and DGSs in high pressure, high temperature sCO 2 environment were not well understood and hence this program aims at developing physics-based performance prediction and life prediction models for these two components. The output of the performance models serves as input to the life models. The performance models were validated using experimental data and using data from literature. DGS and HGB models have shed light on some risks associated with its operation in sCO 2 expander and will guide more robust designs tailored towards sCO 2 cycle applications. A DGS was tested in 1MWe sCO 2 turbo expander to study its performance and validate the performance models. To understand the effect of high pressures, high temperatures and sCO 2 environment on crack initiation, crack propagation and LCF/HCF life of these components, a novel experimental setup was developed. The LCF test data was used to calibrate and validate the life prediction models. The effect of sCO 2 corrosion on the life of Ni-based super-alloys is quantified using long duration experiments. Advanced microstructure and spectroscopic analyses conducted shed light on some key differences between IN718 and IN617 in terms of oxidation morphology, chemical species diffusion and trapping, the formation of protective corrosion resistant layers and changes in surface properties. A novel crack initiation model was developed which takes into account strain distribution, temperature, hold times and activation energy at the gas-metal interface and predicts the number of cycles to initiate the crack in the Inconel alloy. An advanced 3D fracture mechanics-based crack propagation model was also developed which takes into account the transient loading mission of the component and predict how fast the crack will grow and what will be its final shape and size. High energy X-Ray tomography measurements were conducted to study and validate 3D morphology of crack growth inside the specimen. These two models along with chemical kinetics models obtained from corrosion tests can be combined to predict the total life of the component under given long term operating conditions. A Bayesian Hybrid Modeling (BHM) probabilistic framework was developed to quantify uncertainty in physics-based performance models and in crack initiation and crack propagation models, to calibrate the models and to validate the models with statistical confidence. Advanced coupled physics multi-phase flow models were developed to study condensation, boiling and phase change behavior of CO 2 under various sCO 2 turbomachinery and heat exchanger conditions. A novel experimental setup was also designed to observe phase change of CO 2 during its transition across liquid-gas-supercritical state lines.

14 SOLAR ENERGY↗

Electric train energy consumption modeling

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparison of fixed charge and polarizable models for predicting the structural, thermodynamic, and transport properties of molten alkali chlorides

Results from extensive molecular dynamics simulations of molten LiCl, NaCl, KCl, and RbCl over a wide range of temperatures are reported. Comparison is made between the “Polarizable Ion Model” (PIM) and the non-polarizable “Rigid Ion Model” (RIM). Densities, self-diffusivities, shear viscosities, ionic conductivities, and thermal conductivities are computed and compared with experimental data. In addition, radial distribution functions are computed from ab initio molecular dynamics simulations and compared with the two sets of classical simulations as well as experimental data. Here, the two classical models perform reasonably well at capturing structural and dynamic properties of the four molten alkali chlorides, both qualitatively and often quantitatively. With the singular exception of liquid density, for which the PIM is more accurate than the RIM, there are few clear trends to suggest that one model is more accurate than the other for the four alkali halide systems studied here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗