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At least 937 records · Page 52

CD8 + lymphocyte control of SIV infection during antiretroviral therapy

CD8 + lymphocytes play an important role in suppressing in vivo viral replication in HIV infection. However, both the extent to which and the mechanisms by which CD8 + lymphocytes contribute to viral control are not completely understood. A recent experiment depleted CD8 + lymphocytes in simian immunodeficiency virus (SIV)-infected rhesus macaques (RMs) on antiretroviral treatment (ART) to study the role of CD8 + lymphocytes. CD8 + lymphocytes depletion resulted in temporary plasma viremia in all studied RMs. Viral control was restored when CD8 + lymphocytes repopulated. We developed a viral dynamic model to fit the viral load (VL) data from the CD8 depletion experiment. We explicitly modeled the dynamics of the latent reservoir and the SIV-specific effector cell population including their exhaustion and their potential cytolytic and noncytolytic functions. We found that the latent reservoir significantly contributes to the size of the peak VL after CD8 depletion, while drug efficacy plays a lesser role. Our model suggests that the overall CD8 + lymphocyte cytolytic killing rate is dynamically changing depending on the levels of antigen-induced effector cell activation and exhaustion. Based on estimated parameters, our model suggests that before ART or without ART the overall CD8 cytolytic killing rate is small due to exhaustion. However, after the start of ART, the overall CD8 cytolytic killing rate increases due to an expansion of SIV-specific CD8 effector cells. Further, we estimate that the cytolytic killing rate can be significantly larger than the cytopathic death rate in some animals during the second phase of ART-induced viral decay. Lastly, our model provides a new explanation for the puzzling findings by Klatt et al. and Wong et al. that CD8 depletion done immediately before ART has no noticeable effect on the first phase viral decay slope seen after ART initiation Overall, by incorporating effector cells and their exhaustion, our model can explain the effects of CD8 depletion on VL during ART, reveals a detailed dynamic role of CD8 + lymphocytes in controlling viral infection, and provides a unified explanation for CD8 depletion experimental data.

59 BASIC BIOLOGICAL SCIENCES↗

A Preliminary Study of a Novel Heat Pump Integrated Underground Thermal Energy Storage for Shaping Electric Demand of Buildings

A Dual-Purpose Underground Thermal Battery (DPUTB) innovatively integrates a ground heat exchanger with underground thermal energy storage. The DPUTB can be integrated with an Electric-Driven Heat Pump (EDHP) to enable more flexible electric load for meeting the thermal demands of a building (e.g., space cooling and space heating). A one-dimensional numerical model of the DPUTB is developed and validated against measured performance data of a small-scale DPUTB prototype. The validated DPUTB model is integrated with a heat pump model and a building energy simulation model to predict the load shifting performance and energy consumption of an integrated EDHP and DPUTB system. Preliminary simulation results indicate that the integrated system can flatten the electric load profile of a typical residential building and reduce the electric demand during peak hours by 37% on a typical summer day. In addition, the integrated EDHP and DPUTB system also reduces the daily power consumption of the building by 11% compared with a conventional residential space heating and cooling system.

Liu, Xiaobing↗

Charge transport model in nanodielectric composites based on quantum tunneling mechanism and dual-level traps

Charge transport properties in nanodielectrics present different tendencies for different loading concentrations. The exact mechanisms that are responsible for charge transport in nanodielectrics are not detailed, especially for high loading concentration. A charge transport model in nanodielectrics has been proposed based on quantum tunneling mechanism and dual-level traps. In the model, the thermally assisted hopping (TAH) process for the shallow traps and the tunnelling process for the deep traps are considered. For different loading concentrations, the dominant charge transport mechanisms are different. The quantum tunneling mechanism plays a major role in determining the charge conduction in nanodielectrics with high loading concentrations. While for low loading concentrations, the thermal hopping mechanism will dominate the charge conduction process. The model can explain the observed conductivity property in nanodielectrics with different loading concentrations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Machine Learning of Commercial and Residential Load Components in Northwestern United States

The impacts of weather attributes on commercial and residential electricity demands and their components in the northwestern United States were examined. Two machine learning methods, regression tree (RT), and random forest (RF), were integrated and compared. Both RT and RF models provide reliable prediction of commercial cooling load. RF models particularly yield higher accuracy with reduced overfitting.

Zhou, Huifen↗

Integrating External Resources with a Task-Based Programming Model

Accessing external resources (e.g., loading input data, checkpointing snapshots, and out-of-core processing) can have a significant impact on the performance of supercomputer applications. However, no existing programming systems for high-performance computing directly manage and optimize these external accesses. As a result, users must explicitly manage external accesses alongside their computation at the application level, which can result in both correctness and performance issues. We address this limitation by introducing Iris, a task-based programming model with semantics for external resources. Iris allows applications to describe their access requirements to external resources and the relationship of those accesses to the computation. Iris incorporates external I/O into a deferred execution model, reschedules external I/O to overlap I/O with computation, and reduces external I/O when possible. We evaluate Iris on three microbenchmarks representative of important workloads in HPC and a full combustion simulation, S3D. We demonstrate that the Iris implementation of S3D reduces the external I/O overhead by up to 20×, compared to the Legion and the Fortran implementations.

97 MATHEMATICS AND COMPUTING↗

Constrained model calibration of grain structure dependent spall dynamics in shock-loaded tantalum

Here, we perform a gas gun experiment by shock loading tantalum samples of varying grain structures to assess the suitability of a numerical model for simulating spall behavior. The observed differences in spall strength, as well spallation and re-compression history, are not captured in uncalibrated hydrodynamic simulations. An optimization is performed on the Johnson spall model to determine the best parameters that fit the observed trends. Linear stability analysis is employed to motivate bounds on those parameters. Herein, optimized simulations agree well with the experimental results, reproducing pullback depth and recompression timescales across the different samples tested. Further, the observed pullback time of the single crystal sample was found to imply, via the stability analysis, a percolation threshold in good agreement with the theoretical value for a body centered cubic lattice. Therefore, the combined linear stability and percolation analysis shows promise and may be applied to other materials with diverse microstructures. Collectively, the findings demonstrate that the model is suitable for reproducing spall-induced free surface behavior across various microstructures, but also points to caution in using model coefficients for uncalibrated microstructures.

58 GEOSCIENCES↗

Spent Nuclear Fuel Transportation: Rail Conveyance Transmissibility

Equipos Nucleares, S.A. (ENSA) and the US Department of Energy (DOE) are preparing a full scale Spent Nuclear Fuel (SNF) transportation test. This transportation testing will include road, rail, coastal, and trans-Atlantic shipments. The test campaign will use a full scale commercial transportation package and cradle. The package will be loaded with two instrumented fuel assemblies to measure strains at cladding locations and accelerations on the fuel assemblies, and thirty “dummy” assemblies. This testing is designed to closely match an actual SNF shipment. Accelerometers will also be used at various locations throughout the full conveyance system (i.e. rail car/truck, cask, transport cradle, and basket) to study the transmission of loads through the system and to provide validation for numerical models. Previous testing and modeling work has shown how the structural transmissibility of the transport system can affect the magnitude of these loads, and the importance of modeling all aspects of the transport system (i.e. rail car/truck, transport cradle, cask, basket, and fuel) (Ref 1, 2). This paper describes preliminary models that were constructed to estimate load transmission during rail transport, from the bottom of the cradle to an individual fuel rod within the package. The modeling studies in this paper evaluate the system response to postulated shock pulses and random vibration loads. These models describe the transmissibility of the conveyance, and demonstrate how loads can be amplified or attenuated as they are transmitted through the structure. This is done by coupling the rail vehicle dynamics code NUCARS, to the general finite element modeling code ANSYS, and the explicit dynamics code LS-DYNA. Models such as the ones presented herein will be used during the test campaign to help analyze and evaluate the test data as it is collected.

Cladding, Spent Fuel and Radiactive Waste, Used Fu↗

The mechanism of the emergence of distinct overstretched DNA states

Although multiple overstretched DNA states were identified in experiments, the mechanism of the emergence of distinct states is still unclear. Molecular dynamics simulation is an ideal tool to clarify the mechanism, but the force loading rates in stretching achieved by conventional all-atom DNA models are much faster, which essentially affect overstretching states. We employed a modified coarse-grained DNA model with an unprecedented low loading rate in simulations to study the overstretching transitions of end-opened double-stranded DNA. We observed two-strand peeling off for DNA with low stability and the S-DNA with high stability under tension. By introducing a melting-forbidden model which prevents base-pair breaking, we still observed the overstretching transition induced by the formation of S-DNA due to the change of dihedral angle. Hence, we confirmed that the competition between the two strain-softening manners, i.e., base-pair breaking and dihedral angle variation, results in the emergence of distinct overstretched DNA states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large-scale scenarios of electric vehicle charging with a data-driven model of control

Transportation electrification is forecast to bring millions of new electric vehicles to roads worldwide this decade. Planning to support those vehicles depends on detailed scenarios of their electricity demand in both uncontrolled and controlled or smart charging scenarios. In this work, we present a novel modeling approach to enable rapid generation of demand estimates that represent the impact of controlled charging for large-scale scenarios with millions of individual drivers. To model the effect of load modulation control on aggregate charging profiles, we propose a novel machine learning approach that replaces traditional optimization approaches. We demonstrate its performance modeling workplace charging control under a range of electricity rate schedules, achieving small errors (2.5%–4.5%) while accelerating computations by more than 4000 times. To generate the uncontrolled charging demand for scenarios with residential, workplace, and public charging we use statistical representations of a large data set of real charging sessions. We demonstrate the methodology by generating diverse sets of scenarios for California's charging demand in 2030 which consider multiple charging segments and controls, each run locally in under 50 s. We further demonstrate support for rate design by modeling the large-scale impact of a new, custom rate schedule for workplace charging.

33 ADVANCED PROPULSION SYSTEMS↗

NSTXU Diagnostic Disruption Dynamic Loading Represented by Response Spectra

This article presents the results of transient dynamic simulations of loads due to disruption eddy currents on the NSTXU vacuum vessel. Dynamic loading at diagnostic mounting locations is expressed as response spectra derived from the time history results of the dynamic structural simulations of a variety of disruption scenarios. The disruption simulations draw on a history of the project assessments of worst case disruptions for specific components. Major efforts to assess disruption loading have included the vacuum vessel which is the major structural support for the machine, as well as the passive plates (PPs), high harmonic fast wave (HHFW) antenna, and centerstack casing. Each one of these efforts included transient electromagnetic simulations producing time-dependent eddy current Lorentz loads (and in some cases halo loads) which then were applied to time-dependent structural dynamic analyses intended to obtain the proper dynamic amplification factors. In some instances, the EM model and structural model were identical allowing direct transfer of EM forces to the structural model. In other cases, the EM and structural model were not identical and the vector potential (VP) transfer method was used. The results files from these analyses were available (or re-run) to post process in ANSYS Classic time history postprocessor. In conclusion, the ANSYS command is used to create response spectra from time history data at desired points on the vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗

Effect of occupant behavior and air-conditioner controls on humidity in typical and high-efficiency homes

Increasing insulation levels and improved windows are reducing sensible cooling loads in high-efficiency homes. This trend raises concerns that the resulting shift in the balance of sensible and latent cooling loads may result in higher indoor humidity, occupant discomfort, and stunted adoption of high-efficiency homes. This study utilizes established moisture-buffering and air-conditioner latent degradation models in conjunction with an approach to stochastically model internal gains. Building loads and indoor humidity levels are compared for simulations of typical new construction homes and high-efficiency homes in 10 US cities. The sensitivity of indoor humidity to changes in cooling set point, air-conditioner capacity, and blower control parameters are evaluated. The results show that high-efficiency homes in humid climates have cooling loads with a higher fraction of latent loads than the typical new construction home, resulting in higher indoor humidity. Reducing the cooling set point is the easiest method to reduce indoor humidity, but it is not energy efficient, and overcooling may lead to occupant discomfort. Eliminating the blower operation at the end of cooling cycles and reducing the cooling airflow rate also reduce indoor humidity and with a smaller impact on energy use and comfort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Load-Displacement Relation and Gap Distribution Between Rough Surfaces: Partial Differential Equations Approach

We develop a theoretical model to predict the load-displacement relation and probability density function for gaps between contacting rough surfaces. We derive partial differential equations from the previous model (Joe et al., 2018), and extend them to the non-adhesive contact problem. The predictions of the present theory are compared with numerical results using the Green's function molecular dynamics algorithm, and a good agreement is obtained.

adhesion↗

Approximating a linear multiplicative objective in watershed management optimization

Implementing management practices in a cost-efficient manner is critical for regional efforts to reduce the amount of pollutants entering the Chesapeake Bay. We study the problem of selecting a subset of practices that minimizes pollutant load—subject to budgetary and environmental constraints—as simulated in a widely used regulatory watershed model. Mimicking the computation of pollutant load in the regulatory model, we formulate this problem as a continuous optimization model with a linear multiplicative objective function and linear constraints. To lay the groundwork for incorporating additional stakeholder requirements in the future, especially those that would require integer variables, we present and study a continuous linear optimization model that approximates the nonlinear model. The linear model, which requires an exponential number of variables, arises naturally as an alternative model for the same underlying physical process. We examine the theoretical behavior of these optimization models and investigate restrictions of the linear model to handle its large number of variables. Through extensive computational tests on real and randomly generated instances, we demonstrate that the linear model and its restrictions provide optimal solutions close to those of the nonlinear model in practice, despite poor approximation properties in the worst case. We conclude that the linear model—together with our approach to handling its large number of variables—provides a viable framework from which to extend the optimization model to better meet the needs of the Chesapeake Bay watershed management stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Modified Isotherm Modeling to Predict Cs Exchange with Crystalline Silicotitanate in Tank Waste Simulants

The U.S. Department of Energy is working to expedite processing of Hanford tank waste supernate at the Hanford Waste Treatment and Immobilization Plant. To support this goal, Washington River Protection Solutions is designing a Tank Side Cesium Removal (TSCR) system for suspended solids and cesium (Cs/ 137 Cs) removal from Hanford tank waste supernate. The ion exchange media selected for Cs removal at TSCR is crystalline silicotitanate (CST) that is manufactured in a nearly spherical form by Honeywell UOP LLC (UOP; Des Plaines, IL) as product IONSIV® R9140-B (Na form). The Zheng Anthony Miller (ZAM) isotherm model (Zheng et al. 1997) is a multicomponent ion exchange model used to predict the exchange of Group I metals onto CST. The ZAM isotherm has historically been used to predict Cs distribution values from Hanford and Savannah River Site (SRS) tank waste simulants. Figure S.1 summarizes model predictions from the ZAM isotherm that indicate poor prediction of Cs distribution values for simple and complex simulants with the engineered form of CST, IONSIV® R9140-B, and IONSIV® R9120-B where the solid line indicates a perfect fit by the model. The dotted lines indicate ±20% error. Batch contact testing with Hanford tank waste complex and simple simulants was used in conjunction with SRS simulants to experimentally determine Cs distribution values using a modification to the original isotherm model. The experimentally determined maximum Cs capacity for IONSIV® R9140-B CST in both the simple and complex matrices was found to be 0.53±0.3 mmoles Cs/g of CST. This value is not drastically different from the maximum Cs capacity of 0.58 mmoles Cs/g TAM-5 reported by Zheng et al. (1997). However, it is important to note that TAM-5 (commercially IONSIV® IE-910) is a powder. Hamm et al. (2002) determined that a dilution factor was needed to account for the Zr(OH)2 binder in the engineered form of CST. Hamm et al. determined that a dilution factor of 0.68 was appropriate to account for binder contribution and correct overprediction of Cs exchange on the engineered form of CST in ZAM calculations. This reduced the total capacity from 0.58 mmol/g with TAM-5 to 0.39 mmol/g for the engineered form of CST (Hamm et al. 2002). Despite substituting the experimentally determined maximum Cs capacity of 0.55 mmoles Cs/g for the literature-reported capacity of 0.39 mmoles Cs/g, it was determined that additional modifications to the model’s equilibrium rate constants were necessary in refining the isotherm model. The modified model overpredicted K+ uptake by the CST when compared to digested CST results described by Campbell et al. (2019). The modified model was further revised to omit three of the five K+ exchange equilibrium reactions described by ZAM to reduce the additional K+ loading seen by the model. Figure S.2 summarizes the revised model isotherm predictions plotted against measured Kd values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Load Estimation of Offshore Wind Turbines

The influence of 3 MW Hywind-II wind turbine wakes from an upstream offshore floating wind turbine on a downstream turbine with a separation distance of seven rotor diameters was studied for a site in the Gulf of Maine. The turbines and the platforms were subjected to atmospheric boundary layer flows. Various sensitivity studies on fatigue loads with respect to the positions of the downstream turbine were performed and validated with a large-eddy simulation tool. In particular, the effect of various lateral positions of the downstream turbine relative to the upstream turbine were considered using time-series turbine wake data generated from the large-eddy simulation tool which served as an input to an aero-elastic wind turbine model to assess the loads. The load response from the rotor, tower, and the floating platform for the downstream turbine were sensitive to the lateral offset positions where turbines that were partially exposed to upstream turbine wakes yielded significant increases in the cyclic load range. For the given set of lateral positions for the downstream turbine, the largest damage equivalent load occurred when the turbine was one rotor diameter to the left of the centerline, when looking upstream, which is the position of the turbine fully exposed to upstream turbine wake. On the other hand, the fatigue load on the downstream turbine placed on the right side of the position fully exposed to the upstream turbine wake, yielded lower stress due to the non-symmetric shape of the turbine wake. The configuration associated with the largest damage equivalent loads was further investigated in a large-eddy simulation, modeling both the upstream and downstream turbines. It was found that the energy spectra at the blade rotational frequency were a magnitude order higher for the downstream turbine, especially for surge, heave, pitch, and yaw motion of the platform. In conclusion, the increase of the damage equivalent load for the flapwise blade root moment was 45% compared to the upstream turbine, which can potentially reduce the turbine service life time.

17 WIND ENERGY↗

Development of an Offshore Direct-Drive Wind Turbine Model by Using a Flexible Multibody Simulation (Poster)

Modern wind turbines are complex, highly-coupled systems. The dynamic interaction between various components is especially pronounced for multi-megawatt wind turbines. As a result, design process is generally split in several phases. First step consists of creating a global aero-elastic model that includes essential dynamics of structural components using the minimum-possible number of degrees of freedom (d.o.f.). The most important simplifications concern drivetrain and rotor-nacelle assembly (RNA). This approach has been shown valid for several wind turbine configurations. Nevertheless, with increasing size of wind turbines, any simplified design approach must be validated. The present work deals with the comparison and validation of the two modeling approaches for directdrive offshore wind turbines. ARNA/drivetrain model idealized as collection of lumped masses and springs is compared to a detailed Finite Element Method (FEM) based model. The comparison between models focuses on dynamic loads concerning drivetrain system. The comparison is performed in several operational conditions in order to explore the range of validity of the simplified model. Finally, the paper proposes a numerical-based workflow to assess the validity of simplified models of RNA/drivetrain in an aero-elastic global WT model.

17 WIND ENERGY↗

Supporting mobile WEEE collection on demand: A method for multi-criteria vehicle routing, loading and cost optimisation

Highlights: • Multi-criteria method of WEEE mobile collection on demand. • Vehicle routing and loading problem included in the model and algorithm. • Optimisation of collecting vehicles routes including genetic algorithms and fuzzy logic. • Case study for heterogeneous fleet of collection vehicles for medium size city in Poland. • Possible application in a software supporting waste collection on demand. - Abstract: The task of increasing collection rates of waste electrical and electronic equipment (WEEE) is an important challenge in the global economy, and especially in the European Union where stiffer collection targets set out in a new WEEE directive are to be effective by 2019. As the circular economy approach replaces the linear model, resource recycling activities become a priority in waste management policy. As new techniques and possibilities of waste collection systems emerge, opportunities are created for improving efficiency for collection companies and affording benefits for the environment. A model proposed for mobile WEEE collection in this study considers a multi-criteria approach in developing a cost efficient method for pick up on demand from residents or electrical and electronic equipment (EEE) stores. The algorithm used in this model optimises vehicle routes and helps in selecting a number of vehicles from a heterogeneous fleet, incorporating the WEEE loading problem. Using genetic algorithm and fuzzy logic, this model optimises costs and resources required to complete the WEEE collection assuring timely pick up of the waste equipment. The numerical model is verified in a case study in Opole, a city in the south of Poland. The results show that the proposed model can handle the multiple parameter optimisation problem including operational costs, efficient use of vehicles from a fleet, efficient waste loading in vehicles and residents' satisfaction with timely pick up of the waste equipment from a household. Such system can be successfully applied even for large cities. The algorithm provides an opportunity for writing software or mobile apps design to be used by WEEE collection companies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗