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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,765 records · Page 98

Entrainment versus Dilution in Tropical Deep Convection

Abstract The distinction between entrainment and dilution is investigated with cloud-resolving simulations of deep convection in a tropical environment. A method for estimating the rate of dilution by entrainment and detrainment is presented and calculated for a series of bubble simulations with a range of initial radii. Entrainment generally corresponds to dilution of convection, but the two quantities are not well correlated. Core dilution by entrainment is significantly reduced by the presence of a shell of moist air around the core. Dilution by entrainment also increases with increasing updraft velocity but only for sufficiently strong updrafts. Entrainment contributes significantly to the total net dilution, but detrainment and the various source/sink terms play large roles depending on the variable in question. Detrainment has a concentrating effect on average that balances out the dilution by entrainment. The experiments are also used to examine whether entrainment or dilution scale with cloud radius. The results support a weak negative relationship for dilution but not for entrainment. The sensitivity to resolution is briefly discussed. A toy Lagrangian thermal model is used to demonstrate the importance of the cloud shell as a thermodynamic buffer to reduce the dilution of the core by entrainment. The results suggest that explicit cloud heterogeneity may be a useful consideration for future convective parameterization development.

54 ENVIRONMENTAL SCIENCES↗

Economic Valuation of Coccidioidomycosis (Valley Fever) Projections in the United States in Response to Climate Change

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000–15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were 400,000 USD per case, and the annual average total cost was 3.9 billion USD per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost 620,000 USD per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change–attributable damages in the United States.

54 ENVIRONMENTAL SCIENCES↗

Quantitative Evaluation of MD/HD Vehicle Electrification using Statistical Data

This paper presents a wide-ranging analysis of Class 3-8 commercial vehicle electrification by means of developing a framework tool which uses a quantitative method of estimating electric vehicle energy consumption and appropriate charging considerations. The Fleet DNA composite statistics on real-world driving behavior is used to evaluate feasible or market-ready battery electric vehicle (BEV) technologies in medium- and heavy-duty (MD/HD) applications. In the paper, ten representative Class 3-8 commercial vehicle electrifications have been evaluated as a function of various service coverages, including applications in port drayage tractors, refuse trucks, delivery trucks, buses, and bucket trucks. The results indicate significant energy savings and fuel cost savings across all MD/HD vehicle electrifications. The majority of MD BEVs, with the exception of Class 3 bucket trucks, achieve better than a 5-year payback with 50–75% service coverage. For HD BEVs, with the exception of the Class 8 port drayage tractors, the 90% service coverage results in a 10-year or longer payback time, while the 50% service coverage yields a 7–8 year payback. Class 8 port drayage tractors should achieve payback in no more than a 3.5 years with 50–75% service coverage. Thus, the analysis indicates a highly feasible potential for Class 3-6 MD vehicles to be electrified, and feasible opportunities for electrification in Class 7-8 HD short-distance applications.

33 ADVANCED PROPULSION SYSTEMS↗

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Uncertainty Propagation from Experiment Measurements to Modeling Approaches: A Case for SMR Steam Entrainment Testing

To license new and advanced reactor designs, regulators must be convinced that their unique safety cases—relative to existing large scale reactors—have been adequately addressed by the designed reactor protection systems. In water cooled small modular reactors (SMRs), droplet entrainment in steam flow has significant implications on the progression of accident scenarios due to its compact design features, which requires representative test data applicable to SMR designs. Computer code, modeling and simulation (M&S) tools and models require adequate verification, assessment, and qualification. This includes M&S results validation against scaled empirical data within allowable uncertainty bands to gain regulatory approvals during the various stages of reactor system design, demonstration, and commercialization. However, measurement uncertainty within the empirical datasets and test data applicability ranges requires careful consideration of M&S inputs (i.e., boundary conditions, and initial conditions), and verification and validation efforts. This study focuses on uncertainty quantification in designing scaled test facilities for SMR applications with appropriate measurements and a standard data-reduction method to estimate thermal hydraulics characteristics parameters that incorporate physics phenomena of interest. In addition, this study supports the evaluation model development and assessment process using M&S that interfaces with advanced computing tools and digital twin capabilities. This will allow synchronization between experiment and modeling approaches for droplet entrainment testing and analysis, improving diagnostics, prognostics, and decision-making to accelerate regulatory approval.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗

Stochastic Methods Applied to Power System Operations with Renewable Energy: A Review

Renewable energy resources have been rapidly integrated into power systems in many parts of the world, contributing to a cleaner and more sustainable supply of electricity. Wind and solar resources also introduce new challenges for system operations and planning in terms of economics and reliability because of their variability and uncertainty. Operational strategies based on stochastic optimization have been developed recently to address these challenges. In general terms, these stochastic strategies either embed uncertainties into the scheduling formulations (e.g., the unit commitment [UC] problem) in probabilistic forms or develop more appropriate operating reserve strategies to take advantage of advanced forecasting techniques. Other approaches to address uncertainty are also proposed, where operational feasibility is ensured within an uncertainty set of forecasting intervals. In this report, a comprehensive review is conducted to present the state of the art through Spring 2015 in the area of stochastic methods applied to power system operations with high penetration of renewable energy. Chapters 1 and 2 give a brief introduction and overview of power system and electricity market operations, as well as the impact of renewable energy and how this impact is typically considered in modeling tools. Chapter 3 reviews relevant literature on operating reserves and specifically probabilistic methods to estimate the need for system reserve requirements. Chapter 4 looks at stochastic programming formulations of the UC and economic dispatch (ED) problems, highlighting benefits reported in the literature as well as recent industry developments. Chapter 5 briefly introduces alternative formulations of UC under uncertainty, such as robust, chance-constrained, and interval programming. Finally, in Chapter 6, we conclude with the main observations from our review and important directions for future work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Probing the Spin Structure of the Proton Using Polarized Proton-Proton Collisions and the Production of W Bosons

This thesis discusses the process of extracting the longitudinal asymmetry, A$W±\atop{L}$ describing W → μ production in forward kinematic regimes. This asymmetry is used to constrain our understanding of the polarized parton distribution functions characterizing $\bar{u}$ and $\bar{d}$ sea quarks in the proton. This asymmetry will be used to constrain the overall contribution of the sea-quarks to the total proton spin. The asymmetry is evaluated over the pseudorapidity range of the PHENIX Muon Arms, 2.1 < |η| 2.6, for longitudinally polarized proton-proton collisions at 510 GeV √s. In particular, I will discuss the statistical methods used to characterize real muonic W decays and the various background processes is presented, including a discussion of likelihood event selection and the Extended Unbinned Maximum Likelihood t. These statistical methods serve estimate the yields of W muonic decays, which are used to calculate the longitudinal asymmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Neutron Resonance Theory for Nuclear Reactor Applications: Modern Theory and Practices.

The neutron resonance phenomena constitute one of the most fundamental subjects in nuclear physics as well as in reactor physics. It is the area where the concepts of nuclear interaction and the treatment of the neutronic balance in reactor fuel lattices become intertwined. The latter requires the detailed knowledge of resonance structures of many nuclides of practical interest to the development of nuclear energy. The most essential element in reactor physics is to provide an accurate account of the intricate balance between the neutrons produced by the fission process and neutrons lost due to the absorption process as well as those leaking out of the reactor system. The presence of resonance structures in many major nuclides obviously plays an important role in such processes. There has been a great deal of theoretical and practical interest in resonance reactions since Fermi’s discovery of resonance absorption of neutrons as they were slowed down in water. The resonance absorption became the center of attention when the question was raised as to the feasibility of the self-sustaining chain reaction in a natural uranium-fueled system. The threshold of the nuclear era was crossed almost eighty years ago when Fermi and Szilard observed that a substantial reduction in resonance absorption is possible if the uranium was made into the form of lumps instead of a homogeneous mixture with water. In the West, the first practical method for estimating the resonance escape probability in a reactor cell was pioneered by Wigner et al in early forties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SIERRA Multimechanics Module: Aria User Manual (V.4.44)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

97 MATHEMATICS AND COMPUTING↗

SIERRA Multimechanics Module: Aria User Manual Version 4.46.

Aria is a Galerkin fnite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

97 MATHEMATICS AND COMPUTING↗

Guide to the expression of uncertainty in measurements

The enabling objectives of this presentation are to: Provide a working knowledge of the ISO GUM method to estimation of uncertainties in safeguards measurements; Introduce GUM terminology; Provide brief historical background of the GUM methodology; Introduce GUM Workbench software; Isotope ratio measurements by MS will be discussed in the next session.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

State-of-the-Art for Hygrothermal Simulation Tools

The hygrothermal (heat and moisture) performance of buildings can be assessed by utilizing simulation tools. There are currently a number of available hygrothermal calculation tools available which vary in their degree of sophistication and runtime requirements. This report investigates three of the most commonly used models (WUFI, HAMT, and EMPD) to assess their limitations and potential to generate physically realistic results to prioritize improvements for EnergyPlus (which uses HAMT and EMPD). The outcome of the study shows that, out of these three tools, WUFI has the greatest hygrothermal capabilities. Limitations of these tools were also assessed including: WUFI’s inability to properly account for air leakage and transfer at surface boundaries; HAMT’s inability to handle air leakage, precipitationrelated moisture problems, or condensation problems from high relative humidity; and multiple limitations for EMPD as a simplified method to estimate indoor temperature and humidity levels and generally not used to estimate the hygrothermal performance of the building envelope materials. In conclusion, out of the three investigated simulation tools, HAMT has the greatest modeling potential, is open source, and we have prioritized specific features that can enable EnergyPlus to model all relevant heat and moisture transfer mechanisms that impact the performance of building envelope components.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SIERRA Multimechanics Module: Aria User Manual Version 4.42

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number (Re < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.

97 MATHEMATICS AND COMPUTING↗

Response Technical Tools User Guide [Manual]

Developed by the U.S. Nuclear Regulatory Commission for assessment of reactor accidents, Response Technical Manual (RTM) is a paper-based report which contains simple methods for estimating possible accident scenarios and relevant consequences for different kinds of radiological events. Based on RTM, a software called Response Technical Tools (RTT) was developed by Sandia National Laboratories to convert the paper manual into an automated and easy-to-use code. In particular, the RTT focuses on the nuclear power plant severe accidents and is informed by state-of-the-art analyses and software programs, such as MELCOR and MAAP. RTT evaluations can be used to track and predict, at a very coarse level, the progression of a severe accident in nuclear power plant. The RTT allows a user to track the progress of an accident in a nuclear power plant from the point of initiation through the point of containment breach and release to the environment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

An Extended Study on the Uncertainty Quantification of a Photodiode's Spectral Responsivity

An extended study was done on the analysis procedure for spectral responsivity of a silicon detector from the range of 200 nm to 1100 nm for the Optical Component Calibration laboratory at Livermore Operations in Livermore California. As a result, the uncertainty of the procedure was quantified to account for variables that contribute to uncertainty; such as the reproducibility and repeatability of the working standards, quantifying Type A and B uncertainties, validating laboratory equipment and associated software, and looking at environmental variables. The findings lead to a revised analysis reporting procedure that reports uncertainties depending on three spectral ranges, 300 nm to 400 nm, 400 nm to 700 nm, and 700 nm to 1100 nm. A proficiency test was done to compare the difference between both methods and a noticeable difference was found. The results showed that the previous reporting method over estimated uncertainty as much as 3.5% for the 300 nm to 400 nm range, 4% in the >400 nm to 700 nm range, and 2% in the >700 nm to 1100 nm range. The findings lead to the use of the revised procedure when producing calibration certificates, better quantified measurement uncertainties, and will be used for the process of updating the scope of accreditation from the National Voluntary Laboratory Accreditation Program.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SIERRA Multimechanics Module: Aria User Manual - Version 4.50

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( Re < 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities.

97 MATHEMATICS AND COMPUTING↗