A Comparison of Cordinated Planning Methods for Cooperating Rovers
This paper describes and evaluates three methods for coordinating mutiple agents.
planning scheduling artificial intelligence distri↗
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Results for “distribution planning”
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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Colorado Ecological Forecasting: Monitoring Post-Fire Cheatgrass (Bromus Tectorum) Distribution to Inform Management Planning
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Alix Bakke↗
Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning
Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.
DEVELOP Tech Paper↗
Collective Intelligence and Three Aspects of Planning in Organizations: A NASA Example
For many complex sociotechnical systems, planning seems to require explicit coordination; certainly, in executing a plan the activities of different actors must be tightly coupled. However, distributing the needed planning information can be very burdensome and error prone, because different groups need different collections of information, updated or kept current on different time cycles. Further, the information needed to form successful plans is often highly distributed, and while feedback about the success of prior plans may exist, it may not be available to those in a position of using this to improve plans or to detect and resolve other problems in the system (Weick, 1995). Tools to support various aspects of planning have been developed, and can provide a huge benefit to the individuals working on that aspect. To be tractable, most solutions address a quite bounded slice of work, isolating it from the larger context. Prospective planning takes place over multiple, nested cycles of decision making. This builds a plan that specifies activities of different granularity. "Subplans" may specify multiple parallel activities by different groups and individuals, as well as sequential, nested actions by a single actor. Planning produces valuable, sharable, external, representations: in addition to prospective use, plans support retrospective assessment and also action in the present. Viewing planning in a larger context - both temporal and organizational -- enables noticing what one does not know and generating more systemic and effective solutions. Viewing a problem as one of collective intelligence invites thinking about the larger organizational context. Many approaches to supporting collective intelligence do not support execution of highly contingent actions, distributed across many players, and hence provide incomplete support for planning. However, CI technology maybe helpful in managing the processes of gathering information for decision making in planning and of distributing plan information to various actors, needed on various time cycles.
Billman, Dorrit↗
Supersonic Wave Drag of Sweptback Tapered Wings at Zero Lift
On the basis of a recently developed theory for sweptback wings at supersonic velocities, equations are derived for the wave drag of sweptback tapered wings with thin symmetrical double-wedge sections at zero lift. Calculations of section wave-drag distributions and wing wave drag are presented for families of tapered plan forms. Distributions of section wave drag along the span of tapered wings are, in general, very similar in shape to those of untapered plan forms. For a given taper ratio and aspect ratio, an appreciable reduction in wing wave-drag coefficient with increased sweepback is noted for the entire range of Mach number considered. For a given sweep and taper ratio, higher aspect ratios reduce the wing wave-drag coefficient at substantially subcritical supersonic Mach numbers. At Mach numbers approaching the critical value, that is, a value equal to the secant of the sweepback angle, the plan forms of low aspect ratio have lower drag coefficients. Calculations for wings of equal root bending stress (and hence different aspect ratio) indicate that tapering the wing reduces the wing wave-drag coefficient at Mach numbers considerably less than the critical value but increases the drag coefficient at Mach numbers near the critical values. Comparisons on the basis of constant aspect ratio, however, indicate an increase of the wing wave-drag coefficient with taper at Mach numbers considerably less than the critical value and a decrease of the drag coefficient with taper at Mach numbers near the critical value.
WINGS - SWEEPBACK↗
Supersonic Wave Drag of Sweptback Tapered Wings at Zero Lift
On the basis of a recently developed theory for sweptback wings at supersonic velocities, equations are derived for the wave drag of sweptback tapered wings with thin symmetrical double-wedge sections at zero lift. Calculations of section wave-drag distributions and wing wave drag are presented for families of tapered plan forms. Distributions of section wave drag along the span of tapered wings are, in general, very similar in shape to those of untapered plan forms. For a given taper ratio and aspect ratio, an appreciable reduction in wing wave-drag coefficient with increased sweepback is noted for the entire range of Mach number considered. For a given sweep and taper ratio, higher aspect ratios reduce the wing wave-drag coefficient at substantially subcritical supersonic Mach numbers. At Mach numbers approaching the critical value, that is, a value equal to the secant of the sweepback angle, the plan forms of low aspect ratio have lower drag coefficients. Calculations for wings of equal root bending stress (and hence different aspect ratio) indicate that tapering the wing reduces the wing wave-drag coefficient at Mach numbers considerably less than the critical value and a decrease of the drag coefficient with taper at Mach numbers near the critical value.
Margolis, Kenneth↗
A Planning Revolution
The traditional centralized planning and scheduling of complex fast moving projects are value-added activites. However, centralized scheduling has some severe deficiencies that have plagued managers since the Polaris project when PERT analysis was invented.
planning project control receivables delivarables ↗
Autonomy technology at JPL
This paper and exhibit describes the on-going research activities, plans and products of the Autonomy Technology program at NASA Jet Propulsion Laboratory. In this paper, we briefly describe the areas of Mission Planning and Execution, Distributed Autonomous Systems, Science Data Understanding, and Autonomous Guidance and Control.
autonomous rovers distributed systems planning con↗
Technical Assistance for Guam Power Authority
Through the Energy Technology Innovation Partnership Project (ETIPP), Guam Power Authority learned approaches to evaluate existing infrastructure to maximize distributed local energy generation without damaging existing system components.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Powered By CADET
The Capacity Expansion Decision Support for Distribution Networks (CADET) is a Python-based library and framework for creating electrical distribution system capacity planning tools for cost-effective, reliable power delivery. It enables the creation of modular, scalable, and extensible distribution capacity planning tools by providing a high-level optimization interface, parameter and options data managers, optimization constraint and objective libraries, generalized nomenclature, a system for tracking and modifying distribution network changes, optimization solution validation, and other capabilities. This webinar will describe 1) the motivation for creating CADET, 2) key designs, and 3) several use cases.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Wave-Plan Analysis of Unsteady Flow
An analytical method for computing unsteady flow conditions in liquid-filled flow systems is developed. The method which is called the wave plan incorporates distributed parameter and nonlinear effects including the effects of viscous resistance. The wave plan is essentially a solution synthesized from the effects of incremental step pressure pulses. The pressure pulses are generated because of incremental flow-rate changes that originate in a hydraulic system from a variety of sources, including the mechanical motion of the system structure. The pressure pulses propagate throughout the system at sonic velocity and are partially transmitted and reflected at each discontinuity. The velocity change caused by each pressure pulse is obtained from the Joukowski relation. Pressure and velocity time histories at any point in the system are obtained by a timewise summation of the contributions of the incremental pressure pulses passing that point. The analysis is presented in a form general enough to be applied to a variety of hydraulic systems. To illustrate the application of the method to a specific system, the response of a straight hydraulic line to a sinusoidal orifice-area variation of an upstream valve is computed. Both a constant-cross- section line and a tapered line are analyzed in the examples, and various nonlinear effects evaluated. Comparisons are carried out with experimental data obtained for the constant-diameter line and good agreement is shown to exist.
UNSTEADY FLOW↗
Joint operations planning for space surveillance missions on the MSX satellite
The Midcourse Space Experiment (MSX) satellite, sponsored by BMDO, is intended to gather broad-band phenomenology data on missiles, plumes, naturally occurring earthlimb backgrounds and deep space backgrounds. In addition the MSX will be used to conduct functional demonstrations of space-based space surveillance. The JHU/Applied Physics Laboratory (APL), located in Laurel, MD, is the integrator and operator of the MSX satellite. APL will conduct all operations related to the MSX and is charged with the detailed operations planning required to implement all of the experiments run on the MSX except the space surveillance experiments. The non-surveillance operations are generally amenable to being defined months ahead of time and being scheduled on a monthly basis. Lincoln Laboratory, Massachusetts Institute of Technology (LL), located in Lexington, MA, is the provider of one of the principle MSX instruments, the Space-Based Visible (SBV) sensor, and the agency charged with implementing the space surveillance demonstrations on the MSX. The planning timelines for the space surveillance demonstrations are fundamentally different from those for the other experiments. They are generally amenable to being scheduled on a monthly basis, but the specific experiment sequence and pointing must be refined shortly before execution. This allocation of responsibilities to different organizations implies the need for a joint mission planning system for conducting space surveillance demonstrations. This paper details the iterative, joint planning system, based on passing responsibility for generating MSX commands for surveillance operations from APL to LL for specific scheduled operations. The joint planning system, including the generation of a budget for spacecraft resources to be used for surveillance events, has been successfully demonstrated during ground testing of the MSX and is being validated for MSX launch within the year. The planning system developed for the MSX forms a model possibly applicable to developing distributed mission planning systems for other multi-use satellites.
Stokes, Grant↗
Advanced Load Forecasting
This presentation presents information about electric utility load forecasting in the U.S. It provides an overview of load forecasting and describes the current state of the industry. Current load forecasting challenges, opportunities, and interests are presented, including feedback from a 2024 workshop on Integrated Distribution System Planning. The presentation also describes a variety of NREL tools and capabilities that support utility load forecasting efforts. This was presented as part of NREL's Utility Planning Resources for Energy Transition Webinar Series.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study
National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Implementing Distributed Operations: A Comparison of Two Deep Space Missions
Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.
Cassini Mission↗
Roadmap and Benchmarking: Privacy in Federated Load Forecasting
Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.
Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗
Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods
The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.
Green, Lawrence L.↗
Documentation for Python Automation in CYME for DER Hosting Capacity Analysis of Different Feeder Configurations
This file provides the documentation for several Python scripts that were developed by Sandia National Laboratories to enhance the automation and customization capabilities for performing various distribution system planning and analysis tasks in CYME. Specifically, these scripts (.py files detailed in Figure 1) enable the user to evaluate different distribution system configurations and the resulting impacts on hosting capacity results and other metrics. In general, these scripts—and the accompanying documentation—provide the foundation upon which future customized tools can be created. For example, the scripts show how to extract and modify parameters of various circuit components, set up and run analyses using built-in CYME tools (iteratively), and export reports for further evaluations and comparisons. Thus, the capabilities and syntaxes used in the scripts can be adapted and leveraged for countless other objectives.
97 MATHEMATICS AND COMPUTING↗