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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 361 records · Page 20

Intelligent Planning and Scheduling for Controlled Life Support Systems

Planning in Controlled Ecological Life Support Systems (CELSS) requires special look ahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The results suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main characteristics of CELSS from the planning and scheduling perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main characteristics of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paradigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CELSS.

Leon, V. Jorge↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗

SPRINT: Scheduling Planning Routing Intersatellite Network Tool

The Scheduling Planning Routing Intersatellite Network Tool (SPRINT) software system plans and schedules the operations (observations, inter-satellite crosslink communications, and ground communications) of Earth observation (EO) constellations of hundreds of resource-constrained small satellites to enable global, near real-time science. Historically, most CubeSats have flown radios only for direct-to-ground downlink of data; as a result, data availability is delayed by as long as it takes for the capturing satellite to pass over a ground station, typically hours. Current Planning and Scheduling (P&S) systems for constellations cannot handle data routing through a large, dynamic network topology, and all planning is handled on the ground without .the ability to autonomously prioritize important observations, or respond to unexpected changes in communication window or bandwidth. SPRINT directly handles both data routing for low latency bulk observation data downlink and replanning onboard to deal with dynamic priorities and fault response, maximizing the utility of downlinked data.

Kerri Cahoy↗

Development of a Digital Twin for Electrified Aircraft Powertrain Health Management

The augmentation of aircraft powertrains with electrical power systems is a promising path to reducing aircraft fuel consumption, emissions, and noise. Like conventional propulsion systems, electrified aircraft propulsion (EAP) systems will be subject to wear and tear throughout their lifecycles. System health management for EAP will enable efficient flight and maintenance scheduling, realizing economic, safety, and reliability benefits. A digital twin is, broadly, a dynamically updated virtual representation of an individual physical asset. This paper presents a Kalman filter-based approach for the development of a digital twin for an electrified powertrain and applies the approach to an EAP controls testbed. Measurements from nominal testbed operations are used to update a nonlinear model of the testbed. A Kalman filter is then created and used to identify and isolate anomalous testbed behavior based on measurements from off- nominal operations. Results show that the Kalman filter-based digital twin can monitor individual powertrain components’ health for degradation or other changes in performance. The applicability of the presented digital twin approach to any hybrid- or fully-electrified powertrain is emphasized.

Electrified Aircraft Propulsion↗

Simulation of the photogrammetric appendage structural dynamics experiment

The Photogrammetric Appendage Structural Dynamics Experiment (PASDE) uses six video cameras in the Space Shuttle cargo bay to measure vibration of the Russian Mir space station Kvant-ll solar array. It occurs on Shuttle/Mir docking mission STS-74 scheduled for launch in November 1995. The objective of PASDE is to demonstrate photogrammetric technology for measuring 'untargeted' spacecraft appendage structural dynamics. This paper discusses a pre-flight simulation test conducted in July 1995, focusing on the image processing aspects. The flight camera system recorded vibrations of a full-scale structural test article having grids of white lines on black background, similar in appearance to the Mir solar array. Using image correlation analysis, line intersections on the structure are tracked in the video recordings to resolutions of less than 0.1 pixel. Calibration and merging of multiple camera views generated 3-dimensional displacements from which structural modal parameters are then obtained.

Pappa, Richard S.↗

Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources

The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Post-Disturbance Dynamic Distribution System Restoration with DGs and Mobile Resources

Distributed generations (DGs) can act as emergency power supplies when distribution systems suffer from outages. However, the generation capabilities of DGs are generally limited by a number of factors including weather conditions, fuel limitations, etc. In this context, mobile resources that are able to reallocate resources to desired locations are regarded as important complements to conventional fixed DGs in assisting distribution system restoration. In this paper, a distribution system restoration model with DGs and mobile resources is proposed. Firstly, the dispatch and allocation of mobile resources are modeled with respect to the characteristics of the traffic network. Then the developed mobile resource models are integrated into the distribution system restoration model to co-optimize the scheduling of DGs and mobile resources. Uncertainty factors are managed by a model predictive control approach so that system operators can dynamically adjust the restoration strategy with the up-to-date information. The effectiveness of the proposed method is validated through an IEEE 13-bus test system.

distributed generations (DGs)↗

Buildings.Occupants : A Modelica package for modelling occupant behaviour in buildings

Energy-related occupant behaviour is crucial to design and operation of energy and control systems in buildings. Occupant behaviours are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on co-simulation approaches or customized source code changes to building simulation programmes. This paper presents Buildings. Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviours of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviours. Furthermore, the major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviours in buildings and to develop an open-source Occupants package in the Modelica language.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nightshade Prototype Experiments (Silverleaf)

The Red Sage campaign is a series of subcritical dynamic plutonium experiments designed to measure ejecta. Nightshade, the first experiments in Red Sage scheduled for fiscal year 2019, will measure the amount of ejecta emission into vacuum from a double-­shocked plutonium surface. To address the major technical risks in Nightshade, a Level 2 milestone was developed for fiscal year 2016. Silverleaf, a series of four experiments, was executed at the Los Alamos National Laboratory in July and August 2016 to demonstrate a prototype of the Nightshade package and to satisfy this Level 2 milestone. This report is documentation that Red Sage Level 2 milestone requirements were successfully met.

42 ENGINEERING↗

Human controller modeling in environments that include non-control tasks

In complex environments where the human operator is a supervisor, he must allocate his attention between different kinds of tasks for optimum overall performance. When a portion of the future reference trajectory for the control task is available for preview, scheduling various activities is possible. A model has been developed for this situation using dynamic programming to solve an optimal control problem. An experiment was conducted where subjects controlled an airplane symbol over a map, shown a fixed distance into the future. Discrete, non-control tasks were introduced as number entry tasks. Results from the model are compared with experimental results.

Govindaraj, T.↗

Simulation study of an automatic trim system for reducing the control forces on a light twin after an engine failure

An automatic trim system for reducing the control forces after an engine failure on a light twin has been investigated on the Langley General Aviation Simulator. The system schedules open-loop trim tab deflections as a function of differential propeller slipstream dynamic pressure and freestream dynamic pressure. The system is described and the airplane-system static and dynamic characteristics are documented. Three NASA research pilots evaluated the effectiveness of the system for takeoff and landing maneuvers. A variety of off-nominal system characteristics were studied. The system was judged to be generally beneficial, providing a 2 to 3 point improvement in pilot rating for the tasks used in the evaluations.

Stewart, E. C.↗

Integrated flight/propulsion control design for a STOVL aircraft using H-infinity control design techniques

Results are presented from an application of H-infinity control design methodology to a centralized integrated flight propulsion control (IFPC) system design for a supersonic Short Takeoff and Vertical Landing (STOVL) fighter aircraft in transition flight. The emphasis is on formulating the H-infinity control design problem such that the resulting controller provides robustness to modeling uncertainties and model parameter variations with flight condition. Experience gained from a preliminary H-infinity based IFPC design study performed earlier is used as the basis to formulate the robust H-infinity control design problem and improve upon the previous design. Detailed evaluation results are presented for a reduced order controller obtained from the improved H-infinity control design showing that the control design meets the specified nominal performance objectives as well as provides stability robustness for variations in plant system dynamics with changes in aircraft trim speed within the transition flight envelope. A controller scheduling technique which accounts for changes in plant control effectiveness with variation in trim conditions is developed and off design model performance results are presented.

Garg, Sanjay↗

Estimation of Cometary Rotation Parameters Based on Camera Images

The purpose of the Rosetta mission is the in situ analysis of a cometary nucleus using both remote sensing equipment and scientific instruments delivered to the comet surface by a lander and transmitting measurement data to the comet-orbiting probe. Following a tour of planets including one Mars swing-by and three Earth swing-bys, the Rosetta probe is scheduled to rendezvous with comet 67P/Churyumov-Gerasimenko in May 2014. The mission poses various flight dynamics challenges, both in terms of parameter estimation and maneuver planning. Along with spacecraft parameters, the comet's position, velocity, attitude, angular velocity, inertia tensor and gravitatonal field need to be estimated. The measurements on which the estimation process is based are ground-based measurements (range and Doppler) yielding information on the heliocentric spacecraft state and images taken by an on-board camera yielding informaton on the comet state relative to the spacecraft. The image-based navigation depends on te identification of cometary landmarks (whose body coordinates also need to be estimated in the process). The paper will describe the estimation process involved, focusing on the phase when, after orbit insertion, the task arises to estimate the cometary rotational motion from camera images on which individual landmarks begin to become identifiable.

Spindler, Karlheinz↗

Agent-Based Simulations for Project Management

Currently, the most common approach used in project planning tools is the Critical Path Method (CPM). While this method was a great improvement over the basic Gantt chart technique being used at the time, it now suffers from three primary flaws: (1) task duration is an input, (2) productivity impacts are not considered , and (3) management corrective actions are not included. Today, computers have exceptional computational power to handle complex simulations of task e)(eculion and project management activities (e.g ., dynamically changing the number of resources assigned to a task when it is behind schedule). Through research under a Department of Defense contract, the author and the ViaSim team have developed a project simulation tool that enables more realistic cost and schedule estimates by using a resource-based model that literally turns the current duration-based CPM approach "on its head." The approach represents a fundamental paradigm shift in estimating projects, managing schedules, and reducing risk through innovative predictive techniques.

White, J. Chris↗

Dynamic Routing for Delay-Tolerant Networking in Space Flight Operations

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology composed of scheduled, bounded communication contacts in a network built on the Delay-Tolerant Networking (DTN) architecture. It is designed to support operations in a space network based on DTN, but it also could be used in terrestrial applications where operation according to a predefined schedule is preferable to opportunistic communication, as in a low-power sensor network. This paper will describe the operation of the CGR system and explain how it can enable data delivery over scheduled transmission opportunities, fully utilizing the available transmission capacity, without knowing the current state of any bundle protocol node (other than the local node itself) and without exhausting processing resources at any bundle router.

CGR↗

Formal Specification and Parametric Verification of the ICAROUS Distributed Merging Protocol for Autonomous Aircraft Systems

ICAROUS is a software architecture that provides highly assured core software modules for building safety-centric autonomous unmanned aircraft applications. One of its core components is the ICAROUS distributed merging (IDM) protocol, which allows for decentralized merging of autonomous aircrafts through a designated intersection. This report presents initial results on formal specification and parametric verification of the IDM protocol. We present the development of a formal, discrete-time specification of the ICAROUS distributed merging protocol in TLA+. The developed TLA+ specification includes an abstracted model of the physical aircraft dynamics, the consensus machinery for leader election and coordination, and the computation of merging schedules. In addition, we present details on a command line tool we developed verimerge, that utilizes the TLC model checker for doing bounded, parametric verification and allows for plotting of these results in 2D parameter spaces. The tool also provides functionality for visualization of concrete protocol behaviors, to aid debugging and understanding. We present preliminary, bounded time verification results for a finite number of aircraft. Limitations of the current techniques and possible future extensions of this work are also discussed.

ICAROUS↗

ALTRIOS - Advanced Locomotive Technology and Rail Infrastructure Optimization System

The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool to evaluate strategies for deploying advanced locomotive technologies and associated infrastructure for cost-effective decarbonization. ALTRIOS simulates energy conversion and storage dynamics, locomotive and train dynamics, meet-pass planning (detailed train timetabling), and freight-demand-driven train scheduling in a Pareto optimization. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward tradeoffs of different technology rollout strategies. An open, integrated simulation tool will be invaluable for identifying future research needs and making decisions on technology development, routes, and train selection. ALTRIOS development is a collaboration between NREL, the University of Illinois Urbana-Champaign (UIUC) RailTEC, Southwest Research Institute (SwRI), and BNSF.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗