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At least 973 records · Page 54

Reference Natural Gas Flames at Nominally Autoignitive Engine-Relevant Conditions

Laminar natural gas flames are investigated at engine-relevant thermochemical conditions where the ignition delay time r is short due to very high ambient temperatures and pressures. At these conditions, it is not possible to measure or calculate well-defined values for the laminar flame speed S-l, laminar flame thickness delta(l), and laminar flame time scale tau(l) = delta(l)/S-l due to the explosive thermochemical state. Here, the corresponding reference values, S-R, delta(R), and tau(R) = S-R/S-R, that account for the effects of autoignition, are numerically estimated to investigate the enhancement of flame propagation, and the competition with autoignition that arises under nominally autoignitive conditions (characterised here by the number tau/tau(R)). Large values of tau/tau(R) indicate that autoignition is unimportant, values near or below unity indicate that flame propagation is not possible, and intermediate values indicate that a combination of both flame propagation and autoignition may be important, depending upon factors such as device geometry, turbulence, stratification, et cetera. The reference quantities are presented for a wide range of temperatures, equivalence ratios, pressures, and hydrogen concentrations, which includes conditions relevant to stationary gas turbine reheat burners and boosted spark ignition engines. It is demonstrated that the transition from flame propagation to autoignition is only dependent on residence time, when the results are non-dimensionalised by the reference values. The temporal evolution of the reference values are also reported for a modelled boosted SI engine. It is shown that the nominally autoignitive conditions enhance flame propagation, which may be an ameliorating factor for the onset of engine knock. The calculations are performed using a recently-developed, detailed 177 species mechanism for C0-C3 chemistry that is derived from theoretical chemistry and is suitable for a wide range of thermochemical conditions as it is not tuned or optimised for a particular operating condition. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

autoignition↗

Reduced-order modeling for nonlocal diffusion problems

In several settings, diffusive behavior is observed to not follow the rate of spread predicted by parabolic partial differential equations (PDEs) such as the heat equation. Such behaviors, often referred to as anomalous diffusion, can be modeled using nonlocal equations for which points at a finite distance apart can interact. An example of such models is provided by fractional derivative equations. Because of the nonlocal interactions, discretized nonlocal systems have less sparsity, often significantly less, compared with corresponding discretized PDE systems. As such, the need for reduced-order surrogates that can be used to cheaply determine approximate solutions is much more acute for nonlocal models compared with that for PDEs. In this paper, we consider the construction, application, and testing of proper orthogonal decomposition (POD) reduced models for an integral equation model for nonlocal diffusion. For certain modeling parameters, the model we consider allows for discontinuous solutions and includes fractional Laplacian kernels as a special case. Preliminary computational results illustrate the potential of using POD to obtain accurate approximations of solutions of nonlocal diffusion equations at much lower costs compared with, for example, standard finite element methods. Copyright © 2016 John Wiley & Sons, Ltd.

97 MATHEMATICS AND COMPUTING↗

Energy Deposition Analysis of VERA Progression Problems using MCNP6

The current energy deposition model in the CASL neutronics code MPACT assumes all the fission energy is deposited locally. This approximation limits the accurate represen tation of the heating source distribution in the reactor core, which is essential for the thermal/hydraulic coupling calculations. There has been ongoing work to develop im proved models in MPACT to account for the energy deposition distribution of gamma rays, including direct fission gamma (prompt and delayed) and the gamma rays from neutron capture. Also, the neutron/photon coupling transport calculation has been considered as a potential capability to be added in MPACT to provide high-fidelity heating calculations. In order to provide a reference solution for these gamma heating models, MCNP has been used in this work to develop a set of energy deposition bench mark problems, based on the elective VERA Progression Problems, including single pin cells, 2-D assemblies and 2-D quarter core cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ComStock Measure Documentation: Fan Static Pressure Reset for Multizone Variable Air Volume Systems

This report assesses the potential for nationwide adoption of a duct static pressure reset in MZ VAV systems in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario—Fan Static Pressure Reset for Multizone Variable Air Volume (VAV) Systems—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ComStock Measure Documentation: Thermostat Setbacks During Unoccupied Periods

This report assesses the potential for nationwide adoption of thermostat setbacks in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario— Thermostat Setbacks During Unoccupied Periods—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use cases (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ComStock Measure Documentation: High-Efficiency Rooftop Unit

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - high-efficiency rooftop unit (RTU) - and briefly introduces key results. The full public data set can be accessed on the Comstock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ComStock Measure Documentation: Variable-Speed Pumps

Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - variable speed pumps - and briefly introduces key results. The full public data set can be accessed on the ComStock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dynamic Line Rating Models and Their Potential for a Cost‐Effective Transition to Carbon‐Neutral Power Systems

Most transmission system operators (TSOs) currently use seasonally steady-state models considering limiting weather conditions that serve as reference to compute the transmission capacity of overhead power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions, and the degradation of lines in a cost-effective way. DLR can also be used in the long run in grid extension and new power capacity planning. In the short run, it should be used to help operate power systems with congested lines. The operation of the power systems is planned to have the market trading into account; thus, it computes transactions hours ahead of real-time operation, using power flow forecasts affected by large errors. In the near future, within a “smart grid” environment, in real-time operation conditions, TSOs should be able to rapidly compute the capacity rating of overhead lines using DLR models and the most reliable weather information, forecasts, and line measurements, avoiding the current steady-state approach that, in many circumstances, assumes ampacities above the thermal limits of the lines. Here, this work presents a review of the line rating methodologies in several European countries and the United States. Furthermore, it presents the results of pilot projects and studies considering the application of DLR in overhead power lines, obtaining significant reductions in the congestion of internal networks and cross-border transmission lines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Transfer learning of memory kernels for transferable coarse-graining of polymer dynamics

The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters. In particular, we focus on implicit-solvent CG modeling of polymer solutions. The CG model is based on the generalized Langevin equation, where the memory kernel plays the critical role in determining the dynamics in all time scales. Thus, we propose methods for transfer learning of memory kernels. The key ingredient of our methods is Gaussian process regression. By integration with the model order reduction via proper orthogonal decomposition and the active learning technique, the transfer learning can be practically efficient and requires minimum training data. Through two example polymer solution systems, we demonstrate the accuracy and efficiency of the proposed transfer learning methods in the construction of transferable memory kernels. The transferability allows for out-of-sample predictions, even in the extrapolated domain of parameters. Built on the transferable memory kernels, the CG models can reproduce the dynamic properties of polymers in all time scales at different thermodynamic conditions (such as temperature and solvent viscosity) and for different systems with varying concentrations and lengths of polymers.

Ma, Zhan↗

Simulink Modeling and Dynamic Study of Fixed-Speed, Variable-Speed, and Ternary Pumped Storage Hydropower

Pumped Storage Hydropower (PSH) is one of the most popular energy storage technologies in the world. It uses an upper reservoir to store water which can be later used during high-demand. In the United States, most of the energy storage capability actually corresponds to PSH. Moreover, PSH also brings multiple benefits to grid operation. This report presents the Simulink models of three common PSH technologies: Fixed-Speed (FS), Variable-Speed (VS), and Ternary (T)-PSH. These models are available to the general public on this GitHub repository, which contains the MATLAB model initialization files, the Simulink model files, and supplementary MATLAB code used to obtain the figures in this work. For each PSH model, an introductory description of the model components and other relevant functionalities are provided. For further information regarding the models and the initialization parameters, the reader is referred to the shared files in the repository. This report also presents the dynamic behavior of each model. The response of such models to a load event is analyzed and matched with each model's features. A custom IEEE 39 bus case is employed for the FS and T-PSH simulations, while the VS-PSH is simulated on a simplified three-bus test system due to the computational complexity of the model. For the T-PSH, the steady-state and the switching between several operating modes are also studied in this work.

13 HYDRO ENERGY↗

A coarse-graining approach for molecular simulation that retains the dynamics of the all-atom reference system by implementing hydrodynamic interactions

We report on a new approach for deriving coarse-grained intermolecular forces that retains the frictional contribution that is often discarded by conventional coarse-graining methods. The approach is tested for water and an aqueous glucose solution, and the results from the new implementation for coarse-grained molecular dynamics simulation show remarkable agreement with the dynamics obtained from reference all-atom simulations. The agreement between the structural properties observed in the coarse-grained and all-atom simulations is also preserved. We discuss how this approach may be applied broadly to any existing coarse-graining method where the coarse-grained models are rigorously derived from all-atom reference systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-Stage Adjusted Regression Forecasting for Software Defect Prediction

In this paper, a three-stage adjusted regression forecasting model is proposed to forecast the local regression model [6]. This is a growth curve approximation model that predicts the parameters for a future linear model based on a sliding window of previous linear models. The three stages of the model are as follows: • Initial fit: train regression models on a sliding window of the date and record model coefficients. • Prediction: fit new regression models to the coefficient lists and predict the value of the next coefficient. • Error correction: correct coefficient prediction error using the residual of the last point of the coefficient list and moving average. The resulting model from the multi-stage process is a forecast of the local regression model that represents the future window of data and is referred to as the predicted line. Results suggest the three-stage model demonstrates better prediction capability compared to existing solutions.

Pritchard, Shadow↗

First measurement of jet mass in Pb–Pb and p–Pb collisions at the LHC

This letter presents the first measurement of jet mass in Pb–Pb and p–Pb collisions at $\sqrt{s}$$_ {NN}$ =2.76 TeV and $\sqrt{s}$$_ {NN}$ =5.02 TeV, respectively. Both the jet energy and the jet mass are expected to be sensitive to jet quenching in the hot Quantum Chromodynamics (QCD) matter created in nuclear collisions at collider energies. Jets are reconstructed from charged particles using the anti-k T jet algorithm and resolution parameter R=0.4. The jets are measured in the pseudorapidity range |η jet | < 0.5 and in three intervals of transverse momentum between 60 GeV/c and 120 GeV/c. The measurement of the jet mass in central Pb–Pb collisions is compared to the jet mass as measured in p–Pb reference collisions, to vacuum event generators, and to models including jet quenching. It is observed that the jet mass in central Pb–Pb collisions is consistent within uncertainties with p–Pb reference measurements. Furthermore, the measured jet mass in Pb–Pb collisions is not reproduced by the quenching models considered here and is found to be consistent with PYTHIA expectations within systematic uncertainties.

43 PARTICLE ACCELERATORS↗

Effect of geometry and operational parameters on the dehumidification performance of a desiccant coated heat exchanger

Solid desiccant dehumidification systems are an alternative to vapor-compression-based air dehumidification systems. They use solid desiccant materials to adsorb air moisture in space cooling. DCHE can integrate the cooling component in the heat exchanger to achieve higher dehumidification capacity. Comprehensive numeric modeling would be necessary to assist in the design and operation of the DCHE under development to achieve maximum performance. Here, we provide the details of a heat and mass transfer model developed for this purpose. The model aims to cover a gap in existing models by independently modeling heat transfer on the solid desiccant, fin, and tube. The model results were compared with an experimental reference for validation. The air outlet humidity and temperature results for dehumidification and regeneration showed a deviation lower than 15% from the experiment. The validated model was used to perform a parametric study for a series of design and operating conditions. The parametric analysis showed that an increase of 25% in desiccant layer thickness and thermal contact resistance between solid elements reduces moisture removal by 9.1% and 1%, respectively. These results indicate the need to independently model the desiccant layer.

42 ENGINEERING↗

Thermodynamics of Anharmonic Systems: Uncoupled Mode Approximations for Molecules

The partition functions, heat capacities, entropies, and enthalpies of selected molecules were calculated using uncoupled mode (UM) approximations, where the full-dimensional potential energy surface for internal motions was modeled as a sum of independent one-dimensional potentials for each mode. The computational cost of such approaches scales the same with molecular size as standard harmonic oscillator vibrational analysis using harmonic frequencies (HO hf ). To compute thermodynamic properties, a computational protocol for obtaining the energy levels of each mode was established. The accuracy of the UM approximation depends strongly on how the one-dimensional potentials of each modes are defined. If the potentials are determined by the energy as a function of displacement along each normal mode (UM-N), the accuracies of the calculated thermodynamic properties are not significantly improved versus the HO hf model. Significant improvements can be achieved by constructing potentials for internal rotations and vibrations using the energy surfaces along the torsional coordinates and the remaining vibrational normal modes, respectively (UM-VT). For hydrogen peroxide and its isotopologs at 300 K, UM-VT captures more than 70% of the partition functions on average. By con trast, the HO hf model and UM-N can capture no more than 50%. For a selected test set of C2 to C8 linear and branched alkanes and species with different moieties, the enthalpies calculated using the HO hf model, UM-N, and UM-VT are all quite accurate comparing with reference values though the RMS errors of the HO model and UM-N are slightly higher than UM-VT. However, the accuracies in entropy calculations differ significantly between these three models. For the same test set, the RMS error of the standard entropies calculated by UM-VT is 2.18 cal mol -1 K -1 at 1000 K. By contrast, the RMS error obtained using the HO model and UM-N are 6.42 and 5.73 cal mol -1 K -1 , respectively. For a test set composed of nine alkanes ranging from C5 to C8, the heat capacities calculated with the UM-VT model agree with the experimental values to within a RMS error of 0.78 cal mol -1 K -1 , which is less than one-third of the RMS error of the HO hf (2.69 cal mol -1 K -1) and UM-N (2.41 cal mol -1 K -1) models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of Local Structural Loads Computed by OpenFAST Against Measurements From the FOCAL Experimental Campaign

This work presents the validation of the local structural load modeling capability in OpenFAST for floating substructures based on data from the FOCAL experimental campaign. Previously, OpenFAST could only represent the floating substructure as a rigid body, and though this approach can model the global response of the floater in most cases, it is not able to capture the structural loads within the floater's individual members. Consideration of local substructure loads is important for some floating designs, because the pursuit of cost reduction often results in lighter and more flexible structures. To address this limitation, the HydroDyn (hydrodynamics) and SubDyn (substructure dynamics) modules of OpenFAST have been recently extended to account for the flexibility of floating substructures. To validate this new capability, we compare the results obtained by OpenFAST with data measured during the FOCAL experimental campaign, which analyzed a 1:70 scale performance-matched model of the IEA 15-MW reference turbine atop a modified University of Maine VolturnUS-S semisubmersible in a wave basin under the action of both wind and waves. For the purposes of the present work, the most important feature of the experiment is the presence of load cells at the root of each pontoon, and our objective is to assess how well those loads are reproduced by OpenFAST. To model the distributed hydrodynamic and hydrostatic loads along the floating substructure, we adopt a strip-theory approach based on the Morison equation, and we discuss the impact of different hydrodynamic modeling options (wave stretching, MacCamy-Fuchs correction, and second-order wave kinematics) on both motions and loads. For simplicity, we focus on wave-only conditions, both regular and irregular. The results demonstrate good overall agreement for the loads at the root of the pontoons for the waves analyzed in this work, especially given the assumptions and simplifications inherent to a simple strip-theory model.

floating offshore wind turbine↗

Validation of Local Structural Loads Computed by OpenFAST Against Measurements From the Focal Experimental Campaign: Preprint

This work presents the validation of the local structural load modeling capability in OpenFAST for floating substructures based on data from the FOCAL experimental campaign. Previously, OpenFAST could only represent the floating substructure as a rigid body, and though this approach can model the global response of the floater in most cases, it is not able to capture the structural loads within its individual members. Consideration of local substructure loads is important for some floating designs, as the pursuit of cost reduction often results in lighter and more flexible structures. To address this limitation, the HydroDyn (hydrodynamics) and SubDyn (substructure dynamics) modules of OpenFAST have been recently extended to account for the flexibility of floating substructures. To validate this new capability, we compare the results obtained by OpenFAST with data measured during the FOCAL experimental campaign, which analyzed a 1:70 scale performance-matched model of the IEA 15-MW reference turbine atop a modified University of Maine VolturnUS-S semisubmersible in a wave basin under the action of both wind and waves. For the purposes of the present work, the most important feature of the experiment is the presence of load cells at the root of each pontoon, and our objective is to assess how well those loads are reproduced by OpenFAST. To model the distributed hydrodynamic and hydrostatic loads along the floating substructure, we adopt a strip-theory approach based on the Morison equation, and we discuss the impact of different hydrodynamic modeling options (wave stretching, MacCamy-Fuchs correction, and second-order wave kinematics) on both motions and loads. For simplicity, we focus on wave-only conditions, both regular and irregular. The results demonstrate good overall agreement for the loads at the root of the pontoons for the waves analyzed in this work, especially given the assumptions and simplifications inherent to a simple strip-theory model.

floating offshore wind turbine↗

On Residual Stresses and Reference Temperatures in Thermomechanical Simulations of Photovoltaic Modules Using the Finite Element Method

Thermomechanical simulation of photovoltaic (PV) modules using the finite element method (FEM) is a useful tool to evaluate module design features in terms of structural integrity, reliability, and durability. One of the main challenges in the numerical modeling of a PV module is the incorporation of residual stresses induced by the manufacturing process. Modeling assumptions and abstractions are necessary to limit the model complexity and reduce the computational time. However, oversimplifications and incorrect assumptions can lead to erroneous numerical results. Unfortunately, much simulation work still neglects process-induced stresses. This can lead to incorrect predictions of the stress-strain history and erroneous conclusions during the design process. In this work, we review current modeling practices for incorporating process-induced stresses, and contrast numerical models that consider residual stresses with those that neglect them. We find that the simulation objective and available material properties dictate which process steps need to be modeled, and explore in depth the modeling of residual stresses induced by the lamination process. We demonstrate that a simplified cooldown procedure at the beginning of the simulation can increase the model accuracy and discuss appropriate choices for starting and reference temperatures in the finite element model.

14 SOLAR ENERGY↗