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At least 1,639 records · Page 91

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DOE OSTI2015

New simplified formulae of estimation the total number of fissions based on the Nordheim-Fuchs model - 14297

This article presents simplified formulae for the estimation of the total number of fissions for criticality accidents. One of these formulae is based on the Nordheim-Fuchs model. An additional formula takes into account the boiling for solution systems. These formulae are adapted to homogeneous media and can be used for solution and metal accidents. The principle of these formulae, associated with their assumptions, is described. Then, these formulae are compared with practical applications for SILENE and CRAC reactors (solution systems) and past criticality accidents with metal assemblies as well as a previous simplified formula. The proposed new formulae give bounding estimates of the total number of fissions, provided that their area of applicability are respected and that the simulations performed to calculate the necessary input data are representative of the criticality accident configuration. These new formulae require the determination of more parameters than previous simplified formulae, which make them more complicated to use, but may point out and quantify the impact of some physical phenomenon (for instance for the solution boiling). In particular, the comparison with past criticality accidents with metal assemblies shows that more detailed simulations (in terms of geometry and reflection conditions) might be performed in future work to improve the estimate of the number of fissions based on the Nordheim-Fuchs model. (authors)

42 ENGINEERING↗

DOE OSTI2019

Development and case study of the liquid desiccant system module in sorption system simulation program (SorpSim)

Liquid desiccant systems (LDS) have recently seen an increase in research interest as they can utilize low-grade heat resources and separate the sensible and latent cooling loads by efficiently removing moisture in the air without cooling it to the dew point. Yet, simulation and analysis of LDS had remained complex and demanding due to the limited resources of LDS simulation tools. This work presents the new LDS module developed in the Sorption system Simulation program (SorpSim), which is an open-source and flexible platform for steady-state simulation and analysis of various sorption systems. First, the new LDS module containing a finite-difference model and an effectiveness-NTU model for the heat and mass transfer in LDS dehumidifier/regenerator component was introduced. Then the simulation results of the new module were verified using data from the literature. Lastly, a case study was carried out in SorpSim where an LDS cycle was built and simulated using the new module. The impacts of design and operating parameters on the simulated LDS performance were investigated. The parametric study revealed that a high source temperature improved moisture removal rate (MRR) but reduced the system coefficient of performance (COP); the COP increased monotonically with the desiccant solution recirculation ratio, while the MRR peaked at a ratio of 85%; and an internal solution heat exchanger with UA of 800 W/K was found to be sufficient for optimal performance under high recirculation ratios. The case study demonstrated the LDS module’s capability to facilitate the analysis of LDS design and operation. The LDS module can be further coupled with other component models in SorpSim to simulate and analyze various liquid-desiccant-based systems.

42 ENGINEERING↗

DOE OSTI2016

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota

In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers. More specifically, the CASL VUQ Strategy [33] prescribes the use of Predictive Capability Maturity Model (PCMM) assessments [37]. PCMM is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated with an intended application. Exercising a computational model with the methods in Dakota will yield, in part, evidence for a predictive capability maturity model (PCMM) assessment. Table 1.1 summarizes some key predictive maturity related activities (see details in [33]), with examples of how Dakota fits in. This manual offers CASL partners a guide to conducting Dakota-based VUQ studies for CASL problems. It motivates various classes of Dakota methods and includes examples of their use on representative application problems. On reading, a CASL analyst should understand why and how to apply Dakota to a simulation problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2010

Home Energy Saver v3 (website) and APIs

A web-based residential energy calculator with APIs that run two LBNL websites: http://hes.lbl.gov and http://hespro.lbl.gov. Provide customized estimates of residential energy use, energy bills, and CO2 emissions, based on building description information provided by the user. Energy use is estimated by end-use and device, using engineering models developed at LBNL. Space heating and cooling use is based on the DOE-2.1 E building simulation model. Other end-uses (water heating, appliances, lighting, and miscellaneous equipment) are based on engineering models developed by LBNL. Users can estimate their household carbon footprint and compare it to average values for their neighborhood and other regions, displayed using the Google Maps API. Energy bills can be calculated using either average energy price data or actual utility tariffs. The HES software also includes extensive default input for required user inputs. Hardware req.: Multi-platform; Type of files: Source code, installation instructions other; programmer documentation; user manual; electronic format.

Mills, Evan↗

DOE OSTI2016

Home Energy Scoring Tools (website) and Application Programming Interfaces, APIs (aka HEScore)

A web-based residential energy rating tool with APIs that runs the LBNL website: Provides customized estimates of residential energy use and energy bills based on building description information provided by the user. Energy use is estimated using engineering models developed at LBNL. Space heating and cooling use is based on the DOE-2. 1E building simulation model. Other end-users (water heating, appliances, lighting, and misc. equipment) are based on engineering models developed by LBNL.

Mills, Evan↗

DOE OSTI2017

Evaluation of the shear rate effect on the interfacial forces acting on a single bubble

Owing to the outstanding characteristics of mass and heat transfer efficiency, two-phase bubbly flows have wide applications in the nuclear engineering fields. However, the physics behind the bubbly flows phenomenon can be very complex due to the various parameters and phenomena involved. Thanks to the increasing computing power and advanced algorithms, computational fluid dynamics (CFD) approach has emerged as an effective tool for exploring the bubbly flows. In typical laminar channel or pipe flow, the flow field develops a parabolic velocity profile due to the wall friction. Assuming the shear rate across the bubble diameter is constant, the bubble will encounter various shear rates depending on its transverse position. Different shear rates may lead to the acceleration of transverse migration speed and influence the bubble rising velocity. In this summary, we evaluate the effect of shear rate on the interfacial forces (lift and drag) acting on a single bubble with the shear rate ranging from 3.8 to 8.3 s{sup -1} and the Eotvos number ranging from 2.58 to 4.45.

42 ENGINEERING↗

DOE OSTI2016

Powertrain Test Procedure Development for EPA GHG Certification of Medium- and Heavy-Duty Engines and Vehicles

xiii ABSTRACT The goal of this project is to develop and evaluate powertrain test procedures that can accurately simulate real-world operating conditions, and to determine greenhouse gas (GHG) emissions of advanced medium- and heavy-duty engine and vehicle technologies. ORNL used their Vehicle System Integration Laboratory to evaluate test procedures on a stand-alone engine as well as two powertrains. Those components where subjected to various drive cycles and vehicle conditions to evaluate the validity of the results over a broad range of test conditions. Overall, more than 1000 tests were performed. The data are compiled and analyzed in this report.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗

DOE OSTI2019

Nanoparticle Injection Technology for Remediating Leaks of CO 2 Storage Formation (Final Technical Report)

Leakage of a well can occur through the wellbore, the annulus between well tubing and steel casing, or on the outside of the casing. The overall goal of the project is to develop a new technology that can repair or reduce the leakage of wellbore. The new technology is based on simultaneously injecting nanoparticles electrochemically and removing some of the harmful ions in the system so the distressed cement materials can be densified and the corrosion risk of steel casing can be reduced. There were two objectives. One is the development of the injection technology for leakage repair and the other is the development of new numerical simulation models that can simulate and predict the performance of the new repair technology. An electro-migration testing unit and an in-house wellbore testing system were developed; healing agents with nanoparticles were selected, numerical models were developed to simulate the electro-migration technology, and the effectiveness of the new technology was evaluated.

42 ENGINEERING↗

DOE OSTI2019

Virtual Simulation of Spent Nuclear Fuel Repackaging Facility Design Concepts - 19479

This paper presents recent implementation of virtual simulation of SNF repackaging facility operation. The development was based on recent wet and dry facility design concepts. The development involved creating equipment and facility models and implementation of discrete event simulation of large-scale facility-level operation. Lastly, it presented how a hardware-in-the-loop simulation is possible and that a good amount of accuracy was retained from virtual simulation to hardware simulation for the tested configuration. It is expected that this type of simulation will act as a proof of concept for system engineers and help them make more informed decisions when considering potential solutions for SNF handling and disposal. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

On fast simulation of dynamical system with neural vector enhanced numerical solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Hybrid Heavy-Duty Diesel Power System for Off-Road Applications - Concept Definition

A multi-year Power System R&D project was initiated with the objective of developing an off-road hybrid heavy-duty concept diesel engine with front end accessory drive-integrated energy storage. This off-road hybrid engine system is expected to deliver 15-20% reduction in fuel consumption over current Tier 4 Final-based diesel engines and consists of a downsized heavy-duty diesel engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy recovery through both mechanical (high speed flywheel) and electrical systems. The first year of this project focused on the definition of the hybrid elements using extensive dynamic system simulation over transient work cycles, with hybrid supervisory controls development focusing on energy recovery and transient load assist, in Caterpillar’s DYNASTY™ software environment. Three key off-road applications were the focus of the hybrid concept definition with an aim of understanding the system’s modular capability for the diverse off-road heavy-duty market. Core engine performance 1D and 3D simulations isolated the efficiency contributions from the downsized engine, turbocompounding, and in-cylinder thermal barrier coatings. A fuel consumption improvement range of 14 to 24% was predicted, resulting in successful project progression to the design and experimental validation phase. Furthermore, an overview of the experimental engine and hybrid system status concludes the discussion along with the multi-year project’s next steps.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Floquet Engineering of Interactions and Entanglement in Periodically Driven Rydberg Chains

Neutral atom arrays driven into Rydberg states constitute a promising approach for realizing programmable quantum systems. Enabled by strong interactions associated with Rydberg blockade, they allow for simulation of complex spin models and quantum dynamics. We introduce a new Floquet engineering technique for systems in the blockade regime that provides control over novel forms of interactions and entanglement dynamics in such systems. Our approach is based on time-dependent control of Rydberg laser detuning and leverages perturbations around periodic many-body trajectories as resources for operator spreading. These time-evolved operators are utilized as a basis for engineering interactions in the effective Hamiltonian describing the stroboscopic evolution. As an example, we show how our method can be used to engineer strong spin exchange, consistent with the blockade, in a one-dimensional chain, enabling the exploration of gapless Luttinger liquid phases. In addition, we demonstrate that combining gapless excitations with Rydberg blockade can lead to dynamic generation of large-scale multipartite entanglement. Experimental feasibility and possible generalizations are discussed.

Floquet systems↗

DOE OSTI2019

An (adjustable RN)-based multi-OLT PON and the dynamic programming algorithm for downstream channel

In this paper, a multiple optical line terminal (OLT) passive optical network (PON) and the dynamic programming algorithm for downstream channel is proposed. By wavelength-selectable module, the adjustable remote node (RN) is constructed. By this adjustable RN, a simple and efficient multi-OLT PON is designed. By the way of first-plan and then-load, optical network unit (ONU) groups are established in order to realize the fast loading of ONUs. Specially, by introducing dynamic programming algorithm, the wavelength bandwidth utilization is maximized. Finally, by the simulation and analysis, the effectiveness of the proposed scheme is demonstrated.

42 ENGINEERING↗

DOE OSTI2016

Outcomes from the DOE Workshop on Turbulent Flow Simulation at the Exascale

This paper summarizes the outcomes from the Turbulent Flow Simulation at the Exascale: Opportunities and Challenges Workshop, which was held 4-5 August 2015, and was sponsored by the U.S. Department of Energy Office of Advanced Scientific Computing Research. The workshop objective was to define and describe the challenges and opportunities that computing at the exascale will bring to turbulent-flow simulations in applied science and technology. The need for accurate simulation of turbulent flows is evident across the U.S. Department of Energy applied-science and engineering portfolios, including combustion, plasma physics, nuclear-reactor physics, wind energy, and atmospheric science. The workshop brought together experts in turbulent-flow simulation, computational mathematics, and high-performance computing. Building upon previous ASCR workshops on exascale computing, participants defined a research agenda and path forward that will enable scientists and engineers to continually leverage, engage, and direct advances in computational systems on the path to exascale computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Infiltration Data Package for the E-Area Low-Level Waste Facility Performance Assessment

The infiltration data package contains the input parameters, the cap design and material properties assumptions, and the modeling results for the Hydrologic Evaluation of Landfill Performance (HELP) infiltration model simulations performed in support of the E-Area Low-Level Waste Facility Performance Assessment (PA). The infiltration estimates establish the upper boundary condition for the PORFLOW vadose-zone model and GoldSim model simulations for the following E-Area disposal unit types: Slit and Engineered Trenches, Low-Activity Waste Vault (LAWV), Intermediate-Level Vault (ILV), Componentin- Grout (CIG) special waste form trench segments, and the Naval Reactor Component Disposal Areas (NRCDAs). The infiltration data package builds upon relevant, foundational PA technical reports and memoranda from the past 15 years and is supported by three important components: the HELP model input parameter datasheets, HELP model input and output filenames and directory structure, and infiltration rates as a function of time for each scenario for each disposal unit type. For Slit and Engineered Trenches, a single best-estimate Bahia-grass case of two-percent slope and 585- foot slope length represents an upper bound on intact closure-cap infiltration rates over a 10,000-year period. Building upon the single, bounding, and intact case, two different approaches were considered for incorporating the effect of localized cap subsidence on infiltration rates in the PORFLOW flow and transport model simulations. In the first approach, a Monte Carlo probabilistic model was developed to calculate infiltration rates for 0.54%, 2%, 3.6%, and 4.9% subsidence scenariosa reflecting historical and future non-crushable content for the Slit and Engineered Trenches. The resulting blended (spatially and slope-length averaged) infiltration rates become an inflow upper boundary condition for the PORFLOW vadose zone model simulations. In the second and preferred approach, a Monte Carlo rectangle packing algorithm (Danielson, 2019) and a simplified equation for the total mass flux of water draining into a subsided compartment (Equation 1) will be employed to implement a weighted blending of radionuclide fluxes to the water table using the results of deterministic PORFLOW vadose zone simulations representative of specific subsidence cases. Finally, HELP-model results from sensitivity studies of the intact infiltration case were fit to a log-logistic function to generate infiltration profiles over a 10,000-year period for most-optimistic, more-optimistic, best-estimate, more-pessimistic, and most-pessimistic cases, for both the intact and four subsidence scenarios. For the LAWV and IL vaults, infiltration rate profiles for a 10,000-year period were developed for both an on-vault (above the concrete/metal vault roof) and an off-vault (10-foot soil zone adjacent to vault walls) scenario. The purpose of the off-vault simulations was to confirm that subsurface runoff from the concrete vault roof will adequately drain through the lowermost backfill layers adjacent to the vault walls. The LAWV and ILV infiltration profiles assume collapse of the concrete roof at relative Years 2,905 and 7,100, respectively. The identical Bahia-grass case with two-percent slope and 585-foot slope length assumed for the Slit and Engineered Trenches will represent an upper bound on intact infiltration rates for the NRCDAs and CIG special waste form as well. While the NRCDA casks are assumed to remain structurally intact (i.e., non-assumed to collapse 300 years after the end of operations. Because both rows of the existing CIG trench segments in ST23 (formerly CIG01) extend across the planned cap crest, the subsided CIG trench segments are treated conservatively in the HELP model as a 100%-subsidence case with zero subsurface run-on. The CIG special waste form trench segment infiltration profile, therefore, consists of an intact-cap period from relative Year 100 to Year 300, followed by a 100%-subsidence period from relative Year 300 to Year 10,100.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Understanding Soot Development and Thermal Stratification in Combustion Engines through Hyperspectral Non-linear Optical Diagnostics Development

Progress towards next-generation internal combustion engine technologies is dramatically hindered by the complexity of both simulating and measuring key processes, such as thermal stratification and soot formation, in an operating prototype. In general, spectroscopic methods for in-operando probing become limitingly complex at the high pressures and temperature encountered in such systems, and numerical methods for simulating device performance become computationally expensive due to the turbulent flow field, detailed chemistry, and range of important length-scales involved. This report presents parallel experimental and theoretical advances to conquer these limitations. We report the development of high pressure and high temperature ultrafast coherent anti-Stokes Raman spectroscopy measurements, up to a pressure and temperature regime relevant to engine conditions. This report also presents theoretical results using a stochastic one-dimensional turbulence (ODT) model providing insight into the local thermochemical state and its consequences by resolving the full range of reaction-diffusion scales in a stochastic model.

36 MATERIALS SCIENCE↗