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At least 703 records · Page 39

Technology Development and Infusion by NASA's Entry Systems Modeling Project

This paper describes recent development of modeling and simulation technologies for entry systems and their infusion into NASA's exploration missions. Technology development is organized and prioritized using a system-level perspective, resulting in four broad technical areas of investment: (1) Thermal protection material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. The paper will highlight key contributions from each of these areas, their impacts from a spacecraft and mission design perspective, and discuss planned future investment. Aspects of each technical area are only briefly summarized here. Thermal protection material modeling is geared toward high-fidelity, predictive models capable of optimizing design performance, post-flight reconstruction, and quantifying thermal protection system reliability. New computational tools and experimental techniques have been applied to Orion, MSL/Mars 2020, Mars InSight, and Mars Sample Return missions. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. In both cases, substantial improvements in model uncertainty have directly impacted the development of mission margin policies, flight instrumentation design and analysis (Orion and Mars 2020), and have even revealed the importance of neglected phenomena like mid-wave infrared radiation of CO2. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics affecting Orion, Commercial Crew, and Mars programs; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate augmentation of aerothermal environments at Mars during dust storms; and studies of roughness-induced heating augmentation relevant to tiled (Orion, Mars 2020) and woven (Mars Sample Return) thermal protection systems. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent, with precision landing requirements driven by Mars human exploration goals.

Barnhardt, Michael D.↗

An Ontology-Based Archive Information Model for the Planetary Science Community

The Planetary Data System (PDS) information model is a mature but complex model that has been used to capture over 30 years of planetary science data for the PDS archive. As the de-facto information model for the planetary science data archive, it is being adopted by the International Planetary Data Alliance (IPDA) as their archive data standard. However, after seventeen years of evolutionary change the model needs refinement. First a formal specification is needed to explicitly capture the model in a commonly accepted data engineering notation. Second, the core and essential elements of the model need to be identified to help simplify the overall archive process. A team of PDS technical staff members have captured the PDS information model in an ontology modeling tool. Using the resulting knowledge-base, work continues to identify the core elements, identify problems and issues, and then test proposed modifications to the model. The final deliverables of this work will include specifications for the next generation PDS information model and the initial set of IPDA archive data standards. Having the information model captured in an ontology modeling tool also makes the model suitable for use by Semantic Web applications.

Information Model↗

End-Use Load Profiles for the U.S. Building Stock

This presentation summarizes the items discussed during the End-Use Load Profiles for the U.S. Building Stock: Technical Advisory Group Meeting #4 on September 20, 2019.

30 DIRECT ENERGY CONVERSION↗

Synthetic data generation for machine learning model training for energy theft scenarios using cosimulation

Abstract Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Methods to Automate Assessing the Outage Risk and Technical Specification Compliance for Planned Work and Current Plant Conditions. Light Water Reactor Sustainability Program report

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and the extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages. This is done through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and out of service equipment would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment necessary to meet the requirements of the nuclear safety plan. In addition, the operations and outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently during outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This particular report will provide a demonstration of the capabilities in the development of a predictive software platform for improving configuration control and accessing the plant risks associated with outage work protocols and illustrate how the software assists in strategies to minimize these interactions. In addition to maintaining nuclear safety, there are numerous administrative requirements that must be complied with during an outage. This report will discuss the use of logic modelling to monitor planned work against technical specification requirements for given plant conditions and to integrate these requirements with shutdown risk models, clearance order requirements and other plant condition requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗

System Advisor Model (SAM) General Description (Version 2017.9.5)

This document describes the capabilities of the System Advisor Model (SAM) developed and distributed by the U.S. Department of Energy's National Renewable Energy Laboratory. The document is for potential users and others wanting to learn about the model's capabilities. SAM is a techno-economic computer model that calculates performance and financial metrics of renewable energy projects. Project developers, policy makers, equipment manufacturers, and researchers use graphs and tables of SAM results in the process of evaluating financial, technology, and incentive options for renewable energy projects. SAM simulates the performance of photovoltaic, concentrating solar power, solar water heating, wind, geothermal, biomass, and conventional power systems. The financial models are for projects that either buy and sell electricity at retail rates (residential and commercial) or sell electricity at a price determined in a power purchase agreement (PPA). SAM's simulation tools facilitate parametric and sensitivity analyses, Monte Carlo simulation and weather variability (P50/P90) studies. SAM can also read input variables from Microsoft Excel worksheets. For software developers, the SAM software development kit (SDK) makes it possible to use SAM simulation modules in their applications written in C/C plus plus, C sharp, Java, Python, MATLAB, and other languages. NREL provides both SAM and the SDK as free downloads at https://sam.nrel.gov. SAM is an open source project, so its source code is available to the public. Researchers can study the code to understand the model algorithms, and software programmers can contribute their own models and enhancements to the project. Technical support and more information about the software are available on the website.

47 OTHER INSTRUMENTATION↗

The Gulf Nuclear Energy Infrastructure Institute (GNEII): Origins, Objectives, and Operations—A Joint Report

The Gulf Nuclear Energy Infrastructure Institute (GNEII—pronounced "genie") seeks to develop expertise among future leaders of Gulf-region nuclear power programs in global standards, norms and best practices in nuclear energy programs. More specifically, the institute aims to contribute to the enhancement of nuclear security, safety, and safeguards (the so-called nuclear "3S") by providing an avenue for regional nuclear interaction, technical collaboration, lessons-learned discussions, and best-practices sharing. It is a multidisciplinary human capacity development institute offering education, research and technical services to support responsible nuclear energy programs in the Gulf and Middle East regions. In this Joint Report, Chapter 2 discusses GNEII's origins (including drivers, milestones, and design principles), Chapter 3 discusses GNEII's objectives (including goals, mission, and vision), Chapter 4 discusses GNEII's operations (including education, research, and technical service pillars), Chapter 5 discusses major insights and next steps, and Chapter 6 provides a list of publications offering additional depictions and details of GNEII's evolution. Though only one piece of a multi-faceted, multi-national effort to develop human infrastructure needs for nascent nuclear energy programs, GNEII offers a model that addresses the socio-technical attributes of nuclear 3S that can be replicated globally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mixed-element USM3D Contributions to the 4th AIAA High-Lift Prediction Workshop

This paper discusses results of the mixed-element USM3D (USM3D-ME) simulations performed for the 4th AIAA High-Lift Prediction Workshop. The workshop was separated into six Technical Focus Groups to investigate the impact of geometry modeling, grid, and computational methods for predicting high lift flows. This work was performed under the Fixed Grid RANS Technical Focus Group. The primary geometry selected for the workshop was the High-Lift Common Research Model. The performed simulations included a flap deflection study and both a grid refinement study and pitch sweep for the nominal flap deflection configuration. The results show that USM3D-ME RANS solutions, generally, tends to underpredict the lift coefficient and to predict a less negative pitching moment relative to the experimental data. The predicted drag coefficient values agree better with experiment for smaller angles of attack but were observed to be larger than experiment for the largest angle of attack simulated. The results of the grid refinement study demonstrated a lack of grid convergence for the provided grid family. The results of the grid refinement study are consistent with the submissions to the Fixed Grid and Mesh Adaptation Technical Focus Groups. Grid convergence for the provided grid family remains elusive for the international community. A 2D Multielement Airfoil configuration was included to enable a turbulence model verification study, which illustrated favorable agreement between USM3D-ME and the solutions provided by other flow solvers.

CFD↗

Mixed-Element USM3D Contributions to the 4th AIAA High-Lift Prediction Workshop

This paper discusses results of the mixed-element USM3D (USM3D-ME) simulations performed for the 4th AIAA High-Lift Prediction Workshop. The workshop was separated into six Technical Focus Groups to investigate the impact of geometry modeling, grid, and computational methods for predicting high lift flows. This work was performed under the Fixed Grid RANS Technical Focus Group. The primary geometry selected for the workshop was the High-Lift Common Research Model. The performed simulations included a flap deflection study and both a grid refinement study and pitch sweep for the nominal flap deflection configuration. The results show that USM3D-ME RANS solutions, generally, tends to underpredict the lift coefficient and to predict a less negative pitching moment relative to the experimental data. The predicted drag coefficient values agree better with experiment for smaller angles of attack but were observed to be larger than experiment for the largest angle of attack simulated. The results of the grid refinement study demonstrated a lack of grid convergence for the provided grid family. The results of the grid refinement study are consistent with the submissions to the Fixed Grid and Mesh Adaptation Technical Focus Groups. Grid convergence for the provided grid family remains elusive for the international community. A 2D Multielement Airfoil configuration was included to enable a turbulence model verification study, which illustrated favorable agreement between USM3D-ME and the solutions provided by other flow solvers.

CFD↗

A Low-Enriched Uranium (LEU) option for the conversion of FRM II

The Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) is Germany’s most powerful research reactor and uses Highly Enriched Uranium (HEU) fuel enriched at 93 %. The Technical University of Munich (TUM) operates the reactor and has been mandated to convert the FRM II to a lower-enrichment fuel. In preparation for the lower-enrichment fuel downselection, planned for 2023, TUM is evaluating multiple conversion scenarios. In this paper, it is demonstrated that a conversion of FRM II to Low-Enriched Uranium (LEU) is scientifically possible when using the novel monolithic U-10Mo fuel system, which is currently in the qualification process. As a research reactor, safety criteria, neutron flux distribution and cycle length are key metrics. To begin, neutronic and thermal-hydraulic models were created based on current technical drawings and relevant material properties. Specifically tailored computational methods and coupling schemes have also been developed to properly evaluate all relevant characteristics for the conversion of the FRM II reactor. Using these models and methods, a systematic parameter study was performed to explore the defined design space. The results of that study indicate that many LEU designs using monolithic U-10Mo appear to be viable to convert FRM II to LEU. One example of an LEU solution for the FRM II reactor that fulfills the stated safety, compatibility and scientific performance requirements is discussed in more detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

AeroPropulsoServoElasticity: Dynamic Modeling of the Variable Cycle Propulsion System

This presentation was made at the 2012 Fundamental Aeronautics Program Technical Conference and it covers research work for the Dynamic Modeling of the Variable cycle Propulsion System that was done under the Supersonics Project, in the area of AeroPropulsoServoElasticity. The presentation covers the objective for the propulsion system dynamic modeling work, followed by the work that has been done so far to model the variable Cycle Engine, modeling of the inlet, the nozzle, the modeling that has been done to model the affects of flow distortion, and finally presenting some concluding remarks and future plans.

Kopasakis, George↗

Studies on Vapor Adsorption Systems

The project consisted of performing experiments on single and dual bed vapor adsorption systems, thermodynamic cycle optimization, and thermal modeling. The work was described in a technical paper that appeared in conference proceedings and a Master's thesis, which were previously submitted to NASA. The present report describes some additional thermal modeling work done subsequently, and includes listings of computer codes developed during the project. Recommendations for future work are provided.

Shamsundar, N.↗

Concepts for a NASA Applied Spaceflight Environments Office

The National Aeronautics and Space Administration (NASA) is launching a bold and ambitious new space initiative. A significant part of this new initiative includes exploration of new worlds, the development of more innovative technologies, and expansion our presence in the solar system. A common theme to this initiative is the exploration of space beyond Low Earth Orbit (LEO). As currently organized, NASA does not have an Agency-level office that provides coordination of space environment research and development. This has contributed to the formation of a gap between spaceflight environments knowledge and the application of this knowledge for multi-program use. This paper outlines a concept to establish a NASA-level Applied Spaceflight Environments (ASE) office that will provide coordination and funding for sustained multi-program support in three technical areas that have demonstrated these needs through customer requests. These technical areas are natural environments characterization and modeling, materials and systems analysis and test, and operational space environments modeling and prediction. This paper will establish the need for the ASE, discuss a concept for organizational structure and outline the scope in the three technical areas

Edwards, David L.↗

Numerical simulation of the hot-tail runaway electron production mechanism using CQL3D and comparison with Smith–Verwichte analytical model

Abstract The hot-tail mechanism of runaway electron (RE) production (Harvey et al 2000 Phys. Plasmas 7 4590) is the primary source of RE in the case of rapidly cooling tokamak plasma. Quantifying this mechanism is very important as it can provide most of the post-thermal-quench (TQ) current, or a seed current for the secondary source of RE through the avalanche mechanism. An analytic model which omits pitch-angle scattering is often used in literature for estimating the hot-tail RE density (Smith and Verwichte 2008 Phys. Plasmas 15 072502). In the present study, we use the CQL3D bounce-averaged Fokker–Planck code (Harvey and McCoy 1992 Proc. IAEA Technical Committee Meeting on Advances in Simulation and Modeling of Thermonuclear Plasmas p 527) to test the limits of validity of the model. In particular, we examine the cases of Z = 1 and Z = 18 ions, for sets of different initial temperature, density, electric field and the characteristic time of temperature decay. We show that for Z = 1 plasma, the ratio of RE density computed by CQL3D to that estimated from the model is within 0.6–6.0 in studied cases. For the Z = 18 case, this factor is systematically a much smaller number, typically 0.02–0.6. We suggest a simple correction to the model that narrows down the range of this ratio to 0.3–3.8 in all of the cases, including Z = 1 and Z = 18 plasmas.

Physics↗