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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 235 records · Page 13

Multiphysics Coupling of PROTEUS-NODAL and SAM for Molten Salt Reactor Simulation

The purpose of this report is to document the new features and capabilities that have been implemented in the PROTEUS-NODAL code and the coupling procedure of PROTEUS-NODAL with SAM to analyze MSRs. This report is organized as follows. Section 2 presents the variational nodal P 1 solver for cylindrical geometries and its verification test results. Section 3 discusses the transient analysis capability implemented in the P 1 solvers of PROTEUS-NODAL. The solution methods for the coupled system of TFSP and precursor drift equations, the coarse mesh finite difference (CMFD) acceleration, the kinetics parameter evaluation method, and the thermal feedback are discussed. The verification test results against the SP 3 solutions are also discussed. Section 4 describes the coupling scheme of PROTEUS-NODAL and SAM under the MOOSE framework for MSR applications. The developed MOOSE applications named “TreeFrog” and “TreeKangaroo” are discussed. Verification test results for the coupled system are also discussed by comparing the MSFR steady state solution with that obtained from a manually coupled PROTEUS-NODAL and ANSYS CFX computational fluid dynamics (CFD) calculations and the MSFR transient analysis results with the open literature solutions and the PROTEUS-NODAL solutions obtained with the standalone thermal-hydraulics solver. Section 5 provides conclusions and future works.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Analyzing HM-5 data with NAIGEM v.2015.1.315 and NAIGEM v.2.1.4

Two HM-5 units were used to measure uranium items. For each measurement, the enrichment calibration was determined. The built-in software to determine the enrichment calibration was NAIGEM version 2015.1.315. The data were later analyzed by a standalone NAIGEM, version 2.1.4, in order to study the behavior of the NAIGEM software with the HM-5 data and the relationships between various parameters in the NAIGEM code and the HM-5.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Optimizing the LArSoft GaussHitFinder Module

The steps taken to optimize the GaussHitFinder module found in the LArSoft toolkit are documented in detail. By replacing the ROOT-based multi-Gaussian fitter with a custom standalone version, speedups of over 8× are achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Charged Microdroplets in Air: Characterization and Use in Surface Functionalization and Nanomaterials Preparation (Final Technical Report)

The major theme of this project is the exploration of ions and charged droplets in the open air. The specific goals are (1) focusing ions in the open air, (2) separating and measuring the sizes of charged droplets, (3) examining chemical reactions occurring within droplets, (4) examining chemical reactions occurring between charged droplets and chemical vapors, and (5) characterizing surfaces post droplet deposition. The analysis of ions in the open air greatly simplifies instrumentation as it removes the need for large, costly vacuum pumps. Major strides in this project include the sizing of electrospray droplets using structured illumination microscopy, 3D printed drift tube ion mobility (both standalone and coupled with mass spectrometry), and accelerated Suzuki reactions in Leidenfrost droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SIERRA Code Coupling Module: Arpeggio User Manual - Version 4.58

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

First ARM Mobile Facility (AMF1) Aerosol Observing System (AOS01) Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Mobile Aerosol Observing System – Aerosols (MAOS-A), designated AOS01, entered service in March of 2012 at the Los Alamos National Laboratory for the Pajarito Aerosol Coupling to Ecosystems (PACE) field campaign. The Aerosol Observing System is meant to be a standalone, completely autonomous, aerosol sampling system. It requires only power, 208VAC 1φ or 440 VAC 1φ, and an internet connection to be operational. The physical structure is a standard-sized shipping container, 20 feet long by 8 feet wide. Inside, the walls, ceiling, and floor are insulated using >3.5” of spray polyurethane foam with an R-value of 6.2/inch of insulation. The interior walls, floor and ceiling are lined with ¾” plywood for durability and have integrated unistrut for mounting equipment.

54 ENVIRONMENTAL SCIENCES↗

Second ARM Mobile Facility (AMF2) Aerosol Observing System (AOS) Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s second mobile facility (AMF2) Aerosol Observing System, designated AOS02, entered service in October of 2010 at Steamboat Springs, Colorado for the Storm Peak Laboratory Cloud Property Validation Experiment (StormVEx). The Aerosol Observing S ystem is meant to be a standalone, autonomous, aerosol sampling system. It requires only power, 208 or 440 VAC 1φ, and an internet connection to be operational. The physical structure is a standard-sized shipping container, 20 feet long by 8 feet wide. Inside, the walls, ceiling, and floors are insulated using >3.5” of spray polyurethane foam with an R-value of 6.2/inch of insulation. The interior walls, floor, and ceiling are lined with ¾” plywood for durability and have integrated unistrut for mounting equipment.

54 ENVIRONMENTAL SCIENCES↗

Third ARM Mobile Facility (AMF3) Aerosol Observing System (AOS) Instrument Handbook

The U.S. Department of Energy ARM user facility’s AMF3 AOS, designated AOS03, entered service in August of 2016 at the ARM Mobile Facility at Oliktok Point, Alaska. The Aerosol Observing System is meant to be a standalone, completely autonomous, aerosol sampling system. It requires only power, 208VAC, and an internet connection to be operational. The physical structure is a standard-sized shipping container, 20 feet long by 8 feet wide. Inside, the walls, ceiling, and floors are insulated using >3.5” of spray polyurethane foam with an R-value of 6.2/inch of insulation. The interior walls, floor, and ceiling are lined with ¾” plywood for durability and have integrated unistrut for mounting equipment.

54 ENVIRONMENTAL SCIENCES↗

Eastern North Atlantic (ENA) Aerosol Observing System (AOS) Instrument Handbook

The U.S. Department of Energy ARM user facility’s ENA AOS, designated AOS06, entered service in October of 2013 at the ARM Facility on Graciosa Island, Azores. The Aerosol Observing System is meant to be a standalone, completely autonomous, aerosol sampling system. It requires only power, 208VAC 1φ or 440 VAC 1φ, and an internet connection to be operational. The physical structure is a standard-sized shipping container, 20 feet long by 8 feet wide. Inside, the walls, ceiling, and floors are insulated using >3.5” of spray polyurethane foam with an R-value of 6.2/inch of insulation. The interior walls, floor, and ceiling are lined with ¾” plywood for durability and have integrated unistrut for mounting equipment.

54 ENVIRONMENTAL SCIENCES↗

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark (Q1 2020)

This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2020 (Q1 2020). We use a bottom-up method, accounting for all system and project-development costs incurred during the installation to model the costs for residential (with and without storage), commercial (with and without storage), and utility-scale systems (with and without storage). We also incorporate other system characteristics and performance factors, as well as ongoing costs, to benchmark LCOE for PV-standalone systems, and LCOSS for solar+storage.

14 SOLAR ENERGY↗

SIERRA Code Coupling Module: Arpeggio User Manual (V.5.0)

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

97 MATHEMATICS AND COMPUTING↗

Sensitivity Analysis of MFiX-PIC Parameters Using Nodeworks, PSUADE, and DAKOTA

The study presented in this report was aimed to demonstrate UQ analysis performed not only with Nodeworks, but also two other well-established UQ software tools from the U.S. DOE’s National Laboratories (PSUADE from Lawrence Livermore National Laboratory and DAKOTA from Sandia National Laboratory). It is important to emphasize that the motivation of this study was not to determine the best UQ software, but to verify if the global sensitivity analyses from the end-to-end workflow in Nodeworks are consistent with the results of other two UQ software. The components of Nodeworks from Python’s ecosystem have been tested as standalone libraries. However, an assessment study for the complete workflow targeting a specific UQ analysis has not been performed for Nodeworks. Hence, this study is expected to serve as an equivalent of solution verification for Nodeworks using other established UQ tools as reference solution. For this purpose, three distinct flow configurations (i.e., settling bed, bubbling fluidized, and circulating fluidized bed) have been used as representative multiphase flow problems of interest. The results of the systematic simulation campaigns performed in an earlier study using the particle-in-cell (PIC) approach in the Multiphase Flow with Interphase eXchanges (MFIX) suite of solvers (i.e., MFiX-PIC) was utilized. The same set of tabulated results was provided as input to the different UQ software for global sensitivity analysis. Results for the three cases indicate that based on the Sobol’ Sensitivity Indices method the order of importance ranking determined by Nodeworks for the Sobol’ Total Sensitivity Indices is consistent with PSUADE and DAKOTA in each case for the five model parameters considered. The input files for Nodeworks for the three cases are also shared through NETL’s Gitlab repository for the reader interested in reproducibility and further analysis (See Section 1.2).

97 MATHEMATICS AND COMPUTING↗

Canary

CANARY is a wearable environmental sampling device that is small, lightweight, and low-power. CANARY integrates a novel mechanism that uses magnets rather than powered pumps to mimic human breathing. In its current form, CANARY breathes, but sensor integration can easily turn this into a standalone device for use in airborne detection of chemicals, biologicals, viruses, etc. CANARY has a small footprint and requires little power to operate enabling it to be used in various environments. Los Alamos researcher have developed a working prototype of the air intake system and are seeking licensees for the current air intake, validation outside the lab, or further development to integrate biosensors as desired.

47 OTHER INSTRUMENTATION↗

Demonstration of CFD to support the coupled analysis of a reactor pressure vessel subjected to pressurized thermal shock

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended duration or under accident condition. As one of the most significant components of a reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Aging degradation mechanisms (e.g. thermo-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The prediction of the temperature field is achieved by using computational fluid dynamics (CFD) simulation. In this report, a demonstration CFD standalone simulation is performed to support coupled analysis for Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS). The study use a simplified computational domain to represents a real RPV. The purpose of the study is to demonstrate the transient temperature response of RPV to ECC injection. The CFD model is built in a robust and efficient way for further coupled calculation. The next steps of this work, including the coupled thermal and tensor mechanics capabilities using Cardinal are expected to be complete by the end of FY21 for the demo problem. After this, into FY22, the capability will be demonstrated for a realistic RPV.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Influence of Business Models on PV-Battery Dispatch Decisions and Market Value

PV-battery hybrid projects dominate interconnection queues in some regions in the United States, but few projects have been operational long enough to assess how the hybrid capabilities may be used in practice. We interview plant operators and analyze empirical dispatch data for eleven large-scale PV-battery hybrids in three organized wholesale markets in the United States. We use the dispatch data and wholesale market prices to estimate the market value of our sample hybrids in 2020. The empirical increase in market value of a PV-battery hybrid relative to a standalone PV plant varies by project and ranges from $\$$1 to $\$$48/MWhsolar. The premium is driven by market, location, technical characteristics of the PV and battery asset, and battery dispatch strategies. In contrast to the widespread assumptions in the PV-battery hybrid modeling literature, only three of the eleven project operators optimize battery usage for wholesale market revenue as merchant plants. Instead, the majority of operators in the sample have alternate objectives. For example, load-serving entities target peak load reductions, incentive program participants focus on compliance with program requirements, and large energy consumers prioritize resiliency and utility bill minimization. Understanding prevalent dispatch signals and the degree of alignment with system-wide grid needs can increase the market value of PV-battery hybrids.

14 SOLAR ENERGY↗

Software Requirements for a Sample Check-in application in CBRNResponder

In 2021, functional area drills were held that focused on field sample collection and custody transfer at the sample control hotline for the Radiological Assistance Program (RAP) Consequence Management (CM) program. The overarching goal of these drills were to evaluate the current CM processes using the CBRNResponder mobile and web-based applications. There were several needs identified to improve CM processes and to stream/transfer data across multiple devices with and without internet: (1) A sample check-in process is needed to streamline current processes to reduce errors and create efficiencies, (2) the sample check-in application needs to be deployed as a mobile application and on the browser versions when on-line, and (3) the sample check-in process needs to function in an environment with internet connections and also in a standalone mode when internet is not available.

61 RADIATION PROTECTION AND DOSIMETRY↗

LANL’s Digital Supply Chain Transformation with Ariba Part 2 [Slides]

LANL’s budget continues to increase. Our annual procurement spend has increased from approximately 750 million two years ago to 1.4 Billion in FY21. Procurement for LANL is a mix of indirect and direct but had limited managed spend – more standalone orders vs master contracts. The level of transformation we were looking to achieve required a comprehensive approach, encompassing people, processes and software solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Carbon Intensities of Refining Products in Petroleum Refineries with Co-Processed Biofeedstocks

Petroleum refineries increasingly seek to generate fuels with lower carbon intensities (CIs; a measure of life cycle greenhouse gas [GHG] emissions per unit of energy of fuel; well-to-wheel [WTW]) to meet growing demand. Co-processing refers to a process that adds biomass-derived feedstocks to the fossil-based feedstocks of existing petroleum refinery process units. With the use of biofeedstocks, it is expected that co-processed fuels would have lower CIs than their petroleum counterparts without requiring changes in the existing infrastructure for producing, transporting, and using fuels. To quantify the GHG emissions reduction benefits of co-processing, this study uses a linear programming model to simulate petroleum refinery conditions with and without co-processing. The co-processing cases include three biofeedstocks (soy oil, tallow, and used cooking oil or UCO) used as 10 vol.% of the feedstock to a hydrotreater or hydrocracker since these lipid-based feedstocks have favorable properties to be treated in a hydrotreater or hydrocracker. In addition, we considered pyrolysis oil used as 10 vol.% of the feedstock to a fluid catalytic cracking (FCC) unit in the modeled refinery due to its higher oxygen content compared to other lipid-based feedstocks. Life cycle analysis (LCA) using two distinct approaches—process-level energy allocation and a refinery-level marginal approach—has been conducted for each case. The LCA results using process-level allocation show that there are no noticeable changes in emissions or energy use impacts at the facility level. The life cycle GHG emission reductions of co-processing cases are mainly related to the fraction of biogenic carbon embedded in each fuel product. For example, co-processed jet fuels (a mixture of fossil and biogenic fuels) made via hydrotreating or hydrocracking have higher biogenic carbon, which results in jet fuel CI reductions of 3.9%–8.6% compared to the CI of baseline petroleum jet fuels on a WTW basis. However, analysis of co-processed pyrolysis oil in an FCC shows that a higher fraction of biofeedstocks (29%) becomes process emissions (i.e., CO and CO 2 ), mainly due to the oxygenates in pyrolysis oil, and so it generates less renewable fuel than biofeedstocks co-processed via hydrotreating or hydrocracking. Using the refinery-level marginal approach, the changes in energy use and emissions of co-processing cases compared to the petroleum-only baseline case are allocated to the changes in fuel production (assuming renewable fuels). This approach generates the life cycle GHG emission values of co-processed renewable fuels, which are comparable to the CIs of standalone biofuel production pathways. However, as this approach relies on a rough assumption that product yields and emissions from co-processing units on fossil feedstocks remain the same with and without biofeedstock inputs, co-processing cases like FCC pyrolysis oil may generate quite skewed results.

02 PETROLEUM↗