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NASA NTRS1993

SATCOP mission planning software package

As the CDSLR Network grows into the 1990's, it is undergoing many changes in both its capabilities and requirements. On the one hand, great progress has been made in terms of increasing the SLR systems' performance. Upgrades to the onsite computer and improved laser ranging hardware have greatly increased the number of satellite passes which can be acquired during an operating shift by reducing the amount of time needed for operations other than actual ranging. On the other hand, more requirements have been placed on the systems. Many more satellites have become available, with more scheduled for launch, thus, increasing the likelihood of simultaneous satellite visibility. In addition, the possible scenarios required for ranging these many satellites are changing frequently, with conflicting priorities and needs. It became apparent that some tools needed to be developed to assist the planners in determining Network ranging priorities. Such tools have been developed at Bendix under the direction of NASA's Dynamics of the Solid Earth Project (DOSE) for both long range planning and routine operations to maximize the amount of data collected. This paper reviews some of these tools and describe their uses.

Bucey, Steve↗

NASA NTRS2011

Enhancements to TetrUSS for NASA Constellation Program

The NASA Constellation program is utilizing Computational Fluid Dynamics (CFD) predictions for generating aerodynamic databases and design loads for the Ares I, Ares I-X, and Ares V launch vehicles and for aerodynamic databases for the Orion crew exploration vehicle and its launch abort system configuration. This effort presents several challenges to applied aerodynamicists due to complex geometries and flow physics, as well as from the juxtaposition of short schedule program requirements with high fidelity CFD simulations. NASA TetrUSS codes (GridTool/VGRID/USM3D) have been making extensive contributions in this effort. This paper will provide an overview of several enhancements made to the various elements of TetrUSS suite of codes. Representative TetrUSS solutions for selected Constellation program elements will be shown. Best practices guidelines and scripting developed for generating TetrUSS solutions in a production environment will also be described.

Pandya, Mohagna J.↗

NASA NTRS2015

CPAS Preflight Drop Test Analysis Process

Throughout the Capsule Parachute Assembly System (CPAS) drop test program, the CPAS Analysis Team has developed a simulation and analysis process to support drop test planning and execution. This process includes multiple phases focused on developing test simulations and communicating results to all groups involved in the drop test. CPAS Engineering Development Unit (EDU) series drop test planning begins with the development of a basic operational concept for each test. Trajectory simulation tools include the Flight Analysis and Simulation Tool (FAST) for single bodies, and the Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulation for the mated vehicle. Results are communicated to the team at the Test Configuration Review (TCR) and Test Readiness Review (TRR), as well as at Analysis Integrated Product Team (IPT) meetings in earlier and intermediate phases of the pre-test planning. The ability to plan and communicate efficiently with rapidly changing objectives and tight schedule constraints is a necessity for safe and successful drop tests.

Englert, Megan E.↗

DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

A Cooperative Multi-Agent Deep Reinforcement Learning Framework for Real-Time Residential Load Scheduling

Internet-of-Things (IoT) enabled monitoring and control capabilities are enabling increasing numbers of household users with controllable loads to actively participate in smart grid energy management. Realizing an efficient real-time energy management system that takes advantage of these developments requires novel techniques for managing the increased complexity of the control action space in resolving multiple challenges such as the uncertainty in energy prices and renewable energy output along with the need to satisy physical grid constraints such as transformer capacity. Addressing these challenges, we develop a multi-household energy management framework for residential units connected to the same transformer and containing DERs such as PV, ESS and controllable loads. The goal of our framework is to schedule controllable household appliances and ESS such that the cost of procuring electricity from the utility over a horizon is minimized while physical grid constraints are satisfied at each scheduling step. Traditional energy management frameworks either perform global optimization to satisfy grid constraints but suffer from high computational complexity (for example Integer Program, Mixed Integer Programming frameworks and centralized reinforcement learning) or perform decentralized real-time energy management without satisfying global grid constraints (for example multi-agent reinforcement learning with no cooperation). In contrast, we propose a cooperative multiagent reinforcement learning (MARL) framework that i) operates in real-time, and ii) performs explicit collaboration to satisfy global grid constraints. The novelty in our framework is two fold. Firstly, our framework trains multiple independent learners (IL) for each household in parallel using historical data and performs real-time inferencing of control actions using the most recent system state. Secondly, our framework contains a low complexity knapsack based cooperation agent which combines the outputs of ILs to minimize cost while satisfying grid constraints. Simulation results show that our cooperative MARL approach achieves significant cost improvement over centralized reinforcement learning and day-ahead planning baselines. Moreover, our approach strictly satisfies physical constraints with no apriori knowledge of system dynamics while the baseline approaches have occasional violations. We also measure the training and inference time by ranging the number of households from 1 to 25. Results show that our cooperative MARL approach scales best among various approaches.

14 SOLAR ENERGY↗

DOE OSTI2019

A Transactive Network Template for Decentralized Coordination of Electricity Provision and Value

Transactive energy systems facilitate and plan for an allocation of electricity based on distributed, value-based negotiations. They are currently extending the usage of market-based principles and transactions from wholesale electricity markets where they exist today downward into distribution systems. While many interesting transactive energy systems have been proposed, few fully decentralize price discovery and price-responsive control. Even fewer plan for extensibility that will be needed for the ultimate growth of transactive networks and for the inclusion of additional and new objectives and new flexible, responsive assets. This paper introduces a transactive network template from which an agent may be configured at its network node to negotiate for electricity with other neighboring network agents, manage a set of locally-owned supply and demand assets, and induce local power balance through price discovery. A set of base object classes defines the template and may be extended. Three important basic computational responsibilities are allocated among the base object classes—scheduling, balancing, and network coordination. These several basic classes and responsibilities may be used to represent the perspective of large and small devices and regions anywhere in the electric power grid because they are based on the self-similarity of these objects and responsibilities. Agents in a transactive network are not at all unique in these basic responsibilities. So far, these following dynamic values have been addressed by extension of the base classes: energy value, demand charges, transport losses, and impacts of distributed renewable resources. The template is designed to be further extended to address and monetize still other valuable objectives.

Transactive, Transactive network, Transactive netw↗

NASA NTRS1977

Analytic investigation of the AEM-A/HCMM attitude control system performance

The Heat Capacity Mapping Mission (HCMM), scheduled for launch in 1978, will be three-axis stabilized relative to the earth in a 600-kilometer altitude, polar orbit. The autonomous attitude control system consists of three torquing coils and a momentum wheel driven in response to error signals computed from data received from an infrared horizon sensor and a magnetometer. This paper presents a simple model of the attitude dynamics and derives the equations that determine the stability of the system during both attitude acquisition (acquisition-mode) and mission operations (mission-mode). Modifications to the proposed mission-mode control laws which speed the system's response to transient attitude errors and reduce the steady-state attitude errors are suggested. Numerical simulations are performed to validate the results obtained with the simple model.

Lerner, G. M.↗

NASA NTRS1984

STS 41-D Solar Array Flight Experiment

The Solar Array Flight Experiment (SAFE) developed under the direction of the Marshall Space Flight Center, scheduled for launch on STS 41-D, will demonstrate a lightweight solar array technology which offers a factor of 3 improvement in weight and a factor of 10 improvement in specific volume over solar array systems currently in use in the space program. The experiment, which will include multiple deployment and retraction demonstration, verification of electrical and thermal performance, and verification of structural dynamic math models is 15 feet by 105 feet in size and, if completely covered with solar cells, would produce approximately 12.5 kW of electrical power. The unit has now been developed, tested, and is at Kennedy Space Center (KSC) being prepared for launch.

Turner, G. F.↗

NASA NTRS1990

Attitude control/momentum management of the Space Station Freedom for large angle torque-equilibrium-attitude configurations

An attitude-control and momentum-management (ACMM) system for the Space Station in a large-angle torque-equilibrium-attitude (TEA) configuration is developed analytically and demonstrated by means of numerical simulations. The equations of motion for a rigid-body Space Station model are outlined; linearized equations for an arbitrary TEA (resulting from misalignment of control and body axes) are derived; the general requirements for an ACMM are summarized; and a pole-placement linear-quadratic regulator solution based on scheduled gains is proposed. Results are presented in graphs for (1) simulations based on configuration MB3 (showing the importance of accounting for the cross-inertia terms in the TEA estimate) and (2) simulations of a stepwise change from configuration MB3 to the 'assembly complete' stage over 130 orbits (indicating that the present ACCM scheme maintains sufficient control over slowly varying Space Station dynamics).

Parlos, Alexander G.↗

NASA NTRS2008

Spitzer IRS Spectra of Basaltic Asteroids: Preliminary Results

We present preliminary results of a Spitzer program to observe the 5.2--38 micron spectra of small basaltic asteroids using the Spitzer IRS (Infrared Spectrograph). Our targets include members of the dynamical family of the unique large differentiated asteroid 4 Vesta ("Vestoids"), four outer-main-belt basaltic asteroids whose orbits exclude them from originating on 4 Vesta, and the basaltic near-Earth asteroid (NEA) 4055 Magellan. We will compare the compositions and thermophysical properties of the non-Vestoid objects with those of the dynamical vestoids to provide insight on the extent of metal-silicate differentiation on planetsimals during the epoch of planet formation in the early Solar System. As of this writing, spectra of asteroids 10537 (1991 RY16) and 2763 Jeans have been returned. Analysis of these data are ongolng. Observations of 956 Elisa, 2653 Principia, 4215 Kamo, 7472 Kumakiri, and 1459 Magnya have been scheduled and are expected to be available by the time of the DPS meeting. NIR spectra and lightcurves o f the target asteroids are also being observed in support of this program.

Lim, Lucy F.↗

DOE OSTI2016

Modelling Accident Tolerant Fuel Concepts

The catastrophic events that occurred at the Fukushima-Daiichi nuclear power plant in 2011 have led to widespread interest in research of alternative fuels and claddings that are proposed to be accident tolerant. The United States Department of Energy (DOE) through its Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded an Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The ATF HIP is a three-year project to perform research on two accident tolerant concepts. The final outcome of the ATF HIP will be an in-depth report to the DOE Advanced Fuels Campaign (AFC) giving a recommendation on whether either of the two concepts should be included in their lead test assembly scheduled for placement into a commercial reactor in 2022. The two ATF concepts under investigation in the HIP are uranium silicide fuel and iron-chromium-aluminum (FeCrAl) alloy cladding. Utilizing the expertise of three national laboratory participants (Idaho National Laboratory, Los Alamos National Laboratory, and Argonne National Laboratory), a comprehensive multiscale approach to modeling is being used that includes atomistic modeling, molecular dynamics, rate theory, phase-field, and fuel performance simulations. Model development and fuel performance analysis are critical since a full suite of experimental studies will not be complete before AFC must prioritize concepts for focused development. In this paper, we present simulations of the two proposed accident tolerance fuel systems: U3Si2 fuel with Zircaloy-4 cladding, and UO2 fuel with FeCrAl cladding. Sensitivity analyses are completed using Sandia National Laboratories’ Dakota software to determine which input parameters (e.g., fuel specific heat) have the greatest influence on the output metrics of interest (e.g., fuel centerline temperature). We also outline the multiscale modelling approach being employed. Considerable additional work is required prior to preparing the recommendation report for the Advanced Fuels Campaign.

Accident Tolerant Fuel↗

DOE OSTI2020

Failure analysis of a cooling pump using modal and vibration analysis

Four pumps redundantly supply cooling water to a system. All four pumps underwent maintenance during a recently scheduled downtime. During preliminary evaluation following maintenance, one pump, the subject of this document, exhibited higher vibration levels compared to the other three pumps. The pump underwent further performance testing to rule out potential damage resulting from the higher vibration. Vibration analysis and modal analysis including steady state spectrum, operational deflection shape, run up transients, and modal impact have been utilized to identify dynamic characteristics that could contribute to the increased vibration levels. This article will cover the testing setup, methodology, analysis results, and recommendations.

42 ENGINEERING↗

DOE OSTI2022

Production Agency Quality Assurance Management Execution Strategy [Thesis]

There are multiple federal directives that Los Alamos National Laboratory (LANL) must follow for the proper implementation of quality assurance, strategic planning, and execution of manufacturing and surveillance operations. Recent assessments identified that manufacturing in all processing areas is dynamic due to influencing scope changes, design modifications, funding adjustments, and staff attrition. In response, this project was started to develop a comprehensive PAQ execution strategy to support the success of LANL’s manufacturing mission. This project’s method for developing an updated architecture was to create an integrated, flexible, reliable, and agile strategic process. The execution plan has five deliverables: 1) an integrated schedule view of PAQ work scope, 2) a resource management plan that aligns with the required scope, 3) a metrics monitoring dashboard, 4) a project management plan for sustaining NAP 401.1A implementation, and 5) a risk management plan. The research design is a mixed-method approach focused on data collection for each deliverable. The methodology entails qualitative and quantitative research, metrics monitoring, data analysis, and the creation of a dashboard. The qualitative methods used include literature reviews and interviews. The quantitative methods include resource, financial, schedule and survey data analysis. Preliminary and final results were peer reviewed by subject matter experts both within the ALDWP organization and deployed support.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1990

Behavioral networks as a model for intelligent agents

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

Sliwa, Nancy E.↗

NASA NTRS2016

Large Observatory for X-ray Timing (LOFT-P): A Probe-Class Mission Concept Study

LOFT-P is a mission concept for a NASA Astrophysics Probe-Class (less than $1B) X-ray timing mission, based on the LOFT M-class concept originally proposed to ESA's M3 and M4 calls. LOFT-P requires very large collecting area, high time resolution, good spectral resolution, broadband spectral coverage (2-30 keV), highly flexible scheduling, and an ability to detect and respond promptly to time-critical targets of opportunity. Many of LOFTP's targets are bright, rapidly varying sources, so these measurements are synergistic to imaging and high-resolution spectroscopy instruments, addressing much smaller distance scales than are possible without very long baseline X-ray interferometry, and using complementary techniques to address the geometry and dynamics of emission regions. LOFT-P was presented as an example mission to the head of NASA's Astrophysics Division, to demonstrate the strong community support for creation of a probe-class, for missions costing between $500M and $1B. We submitted a white paper4 in response to NASA PhysPAG's call for white papers: Probe-class Mission Concepts, describing LOFT-P science and a simple extrapolation from the ESA study costs. The next step for probe-class missions will be input into the NASA Astrophysics Decadal Survey to encourage the creation of a probe-class opportunity. We report on a 2016 study by MSFC's Advanced Concepts Office of LOFT-P, a US-led probe-class LOFT concept.

x-ray↗

DOE OSTI2018

Final Report from The University of Texas at Austin for DEGAS: Dynamic Global Address Space programming environments

The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability: Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

The NASP Program - An update

The NASP Program has made substantial technical progress and undergone significant change since the last report to the Society in 1987. This paper will focus on the technical progress that has been made in the areas of propulsion, materials, computational fluid dynamics (CFD) validation, and overall design of the X-30. The impact that the flight test community has had on the approach to the development and test of the X-30 will also be included. A short discussion of the transition to a new management and program execution process through use of a National Contractor Team will also be presented along with the new revised schedule for the overall program.

Wierzbanowski, Ted↗

NASA NTRS2000

Sliding Mode Control of the X-33 with an Engine Failure

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Shtessel, Yuri B.↗