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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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Simultaneous robot path planning and path following is shown to be achievable in the presence of motor saturation and obstacle avoidance requirements. The discrete time algorithm derived performs one step ahead mean square optimization of commanded joint accelerations, subject to present actuator force or torque constraints and N step ahead prediction of configuration constraints.
This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.
We propose to develop efficient algorithms and software for the SCOPF problem. We will employ an iterative approach that will: a) use linear subproblems and other active set filtering techniques to identify the most important contingencies and drastically reduce the SCOPF model size; b) solve SOCP relaxations of the reduced SCOPF to converge to the neighborhood of the global optimal solution and establish a lower bound on the solution, and; c) use a non-convex, nonlinear interior-point solver, Artelys Knitro, to converge quickly to the optimal solution. To identify the most effective approach, we will experiment with several techniques to identify the tradeoffs between contingency subproblem complexity and fast solvability.
SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability
Experiments in materials and fluids processing have been conducted, or are planned, that take advantage of the low-g environment offered by space-based platforms. While the specific goals of the experiments vary, a common objective is to see improved results from the processes over those that would be obtained from similar ground-based experiments. While the space-based processing environment does offer a low-g environment, it is not disturbance free. Results of experiments already conducted, particularly those in manned vehicles, show that spacecraft induced disturbances still limit what can be achieved in materials processing. The duration of actual micro-g level environments is shorter than desired and periods of milli-g activity levels are not uncommon. While small scale experiments can be configured to overcome some of the vehicle disturbance sources, larger scale processing devices and commercial activities will require alternative methods to reduce the influences of spacecraft vibrations. Applied Technology Associates, Inc., (ATA), in cooperation with NASA Lewis Research Center, is developing hardware to provide a sustained micro-g experiment environment. This work is being sponsored under a Small Business Innovation Research (SBIR) program, which is currently in the Phase 2 development stage. ATA's approach is based on an inertial actuator, which when used as part of a closed-loop stabilization system, rejects unwanted disturbances to the experiment package. A prototype of the actuator has been fabricated and used in a laboratory demonstration to prove the principle of operation. ATA's presentation emphasized the development and testing of the Digital Materials Processing Experiment (DAMPER) inertial actuator. Physical and performance characteristics of the device are presented. Technical issues, including further optimization of the actuator's performance and plans for additional laboratory experiments, are also covered.
An optimal control formulation of the problem of collision avoidance of mobile robots in environments containing moving obstacles is presented. Collision avoidance is guaranteed if the minimum distance between the robot and the objects is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Furthermore, time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. Simulation results verify the value of the proposed strategy.
There are two important aspects of the Moon and its materials which must be addressed in preparation for a manned return to the Moon and establishment of a lunar base. These involve its geologic science and resource utilization. Knowledge of the Moon forms the basis for interpretations of the planetary science of the terrestrial planets and their satellites; and there are numerous exciting explorations into the geologic science of the Moon to be conducted using orbiter and lander missions. In addition, the rocks and minerals and soils of the Moon will be the basic raw materials for a lunar outpost; and the In-Situ Resource Utilization (ISRU) of lunar materials must be considered in detail before any manned return to the Moon. Both of these fields -- planetary science and resource assessment -- will necessitate the collection of considerable amounts of new data, only obtainable from lunar-orbit remote sensing and robotic landers. For over fifteen years, there have been a considerable number of workshops, meetings, etc. with their subsequent 'white papers' which have detailed plans for a return to the Moon. The Lunar Observer mission, although grandiose, seems to have been too expensive for the austere budgets of the last several years. However, the tens of thousands of man-hours that have gone into 'brainstorming' and production of plans and reports have provided the precursor material for today's missions. It has been only since last year (1991) that realistic optimism for lunar orbiters and soft landers has come forth. Plans are for 1995 and 1996 'Early Robotic Missions' to the Moon, with the collection of data necessary for answering several of the major problems in lunar science, as well as for resource and site evaluation, in preparation for soft landers and a manned-presence on the Moon.
Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.
The loss of the Space Shuttle Columbia as a result of impact damage from foam debris during ascent has led NASA to investigate the feasibility of on-board impact detection technologies. AE sensing has been utilized to monitor a wide variety of impact conditions on Space Shuttle components ranging from insulating foam and ablator materials, and ice at ascent velocities to simulated hypervelocity micrometeoroid and orbital debris impacts. Impact testing has been performed on both reinforced carbon composite leading edge materials as well as Shuttle tile materials on representative aluminum wing structures. Results of these impact tests will be presented with a focus on the acoustic emission sensor responses to these impact conditions. These tests have demonstrated the potential of employing an on-board Shuttle impact detection system. We will describe the present plans for implementation of an initial, very low frequency acoustic impact sensing system using pre-existing flight qualified hardware. The details of an accompanying flight measurement system to assess the Shuttle s acoustic background noise environment as a function of frequency will be described. The background noise assessment is being performed to optimize the frequency range of sensing for a planned future upgrade to the initial impact sensing system.
The Geostationary Operational Environmental Satellite (GOES)-I/M station acquisition sequence consists nominally of three in-plane/out-of-plane maneuvers at apogee on the line of relative nodes and a small in-plane maneuver at perigee. Existing software to determine maneuver attitude, ignition time, and burn duration required modification to optimize the out-of-plane parts and admit the noninertial, three-axis stabilized attitude. The Modified Multiple Impulse Station Acquisition Maneuver Planning Program (SENARIO2) was developed from its predecessor, SCENARIO, to optimize the out-of-plane components of the impulsive delta-V vectors. Additional new features include commputation of short term J sub 2 perturbations and output of all premaneuver and postmaneuver orbit elements, coarse maneuver attitudes, propellant usage, spacecraft antenna aspect angles, and ground station coverage. The output data are intended to be used in the launch window computation and by the maneuver targeting computation (General Maneuver (GMAN) Program) software. The maneuver targeting computation in GMAN was modified to admit the GOES-I/M maneuver attitude. Appropriate combinations of ignition time, burn duration, and attitude enable any reasonable target orbit to be achieved.
Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.
The National Spherical Torus Experiment Upgrade (NSTX-U) is preparing to resume operation, representing a crucial step toward realizing compact, cost-effective fusion pilot plants. In advance of this, extensive modeling and data analysis have been conducted to advance the physics basis for low-aspect-ratio, high-performance plasma regimes, focusing on three core objectives: confinement and stability, power and particle handling, and steady-state operation. Significant progress has been made in understanding the electron temperature flattening in high-β plasmas, which is shown to be driven by a complex interplay of magnetohydrodynamic instabilities (e.g. non-resonant infernal modes), fast-ion-driven Alfvén eigenmodes, and electron and ion-scale micro-instabilities, particularly Kinetic Ballooning Modes (KBMs), whose destabilization is strongly dependent on parallel magnetic field fluctuations (δB ∥ ). Furthermore, a new gyrokinetic critical pedestal model was developed, accurately predicting pedestal structure by identifying KBMs as the primary stability limit, offering a critical constraint for future high-confinement scenarios. To address the challenge of high heat flux, novel liquid lithium plasma-facing components were modeled. The analysis confirmed that lithium vapor shielding is a self-regulating mechanism for heat mitigation, while also emphasizing that strong main ion parallel flow is essential to minimize core lithium contamination. Finally, progress toward steady-state operation was anchored by developing the required physics basis and control tools. This includes predictive modeling for reversed magnetic shear sustainment, demonstrating that magnetic island-induced bootstrap current reduction is negligible in STs, and advancing real-time control and disruption avoidance capabilities. The development of high-speed surrogate models (e.g. MMMNet) provides computationally efficient tools vital for non-inductive scenario optimization and integrated, low-disruptivity operations planned for NSTX-U.
This paper summarizes the presentations and panel discussion held at Plenary Session 1 of the 16th IRPA International Congress/69th Health Physics Society Annual Meeting, in Orlando, FL, in July 2024. Plenary Session 1 discussed the basics of the systems of radiological protection (RP) for ionizing radiation (IR) and non-ionizing radiation (NIR) and included five presentations and a panel discussion. Rodney Croft, Chair of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), delivered the first presentation. Croft introduced the System of RP for NIR and provided an overview of ICNIRP’s coverage and current areas of work. Werner Rühm, Chair of the International Commission on Radiological Protection (ICRP), delivered the second presentation. He gave an overview of the System of RP for IR and covered the key principles of justification, optimization, and dose limitation, including the current plans of ICRP toward the envisaged revision of the System of RP. The third speaker, Sigurður Magnús Magnússon, from the International Radiation Protection Association (IRPA), provided the perspective of the RP professionals on the development of the Systems of RP for IR and NIR. Emilie van Deventer, from the World Health Organization (WHO), presented WHO’s views of both Systems of RP and discussed the relevant current activities of WHO with regard to IR and NIR. Kathryn Higley, President of the National Council on Radiation Protection and Measurements (NCRP), delivered the final presentation. Higley outlined the history of NCRP, the differences between ICRP and NCRP, and discussed the role of the NCRP in the System of RP, including NCRP’s role to analyze mechanisms of interaction of NIR with biological systems, including humans. The session concluded with a fruitful panel discussion, where the audience had the opportunity to ask the five invited speakers questions.
Mission simulation mathematical modeling technology developed for optimization of experiment program management and operational planning for manned space station missions
In the face of numerically superior hostile forces, deployment of individual vehicles to the right place, at the right time, and the ability to plan missions with less conservatism, will become significant force multipliers. Far-field mission planning is one of the enabling technologies that will facilitate force coordination through management of mission timeline, vehicle survivability and fuel constraints. On-board replanning is required to deal responsively with departures from nominal plan execution that result from imperfect knowledge of and temporal variability in the mission environment. The far-field planning problem is posed as a constrained optimization problem and algorithms and structural organization are proposed for the solution.
A trade study reviewing the primary operational parameters concerning the deployment of imaging assets in support of the Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project was undertaken. The objective was to determine key variables and constraints for obtaining thermal images of the Space Shuttle orbiter during reentry. The trade study investigated the performance characteristics and operating environment of optical instrumentation that may be deployed during a HYTHIRM data collection mission, and specified contributions to the Point Spread Function. It also investigated the constraints that have to be considered in order to optimize deployment through the use of mission planning tools. These tools simulate the radiance modeling of the vehicle as well as the expected spatial resolution based on the Orbiter trajectory and placement of land based or airborne optical sensors for given Mach numbers. Lastly, this report focused on the tools and methodology that have to be in place for real-time mission planning in order to handle the myriad of variables such as trajectory ground track, weather, and instrumentation availability that may only be known in the hours prior to landing.
Method and system for evaluating and implementing air traffic management tools and approaches for managing and avoiding an air traffic incident before the incident occurs. The invention provides flight plan routing and direct routing or wind optimal routing, using great circle navigation and spherical Earth geometry. The invention provides for aircraft dynamics effects, such as wind effects at each altitude, altitude changes, airspeed changes and aircraft turns to provide predictions of aircraft trajectory (and, optionally, aircraft fuel use). A second system provides several aviation applications using the first system. These applications include conflict detection and resolution, miles-in trail or minutes-in-trail aircraft separation, flight arrival management, flight re-routing, weather prediction and analysis and interpolation of weather variables based upon sparse measurements.
Introduction: The presence of water ice in permanently shadowed regions on the lunar surface [1] may enable a sustained human presence on the Moon with minimal need for consumables. However, in order to develop a long term utilization plan that includes the usage of in-situ water we must first understand the abundance, stratigraphy and distribution of this re-source. Multiple space agencies currently have plans for lunar water prospecting missions. The Optimized Volatile Extraction Node (OVEN) was designed for water prospecting missions that require samples to be weighed, sealed, and heated as the means of determining water concentration. This method of water quantification necessitates a fair amount of automation, so a rigorous environmental test program was performed in order to build confidence in the performance of the OVEN design. The work presented here describes the OVEN environmental test program as well as ongoing efforts to improve on the design. Vibration: The OVEN participated in two rounds of random vibration tests. The first test was a stand-alone test performed at the Energy Systems Test Area of the Johnson Space Center. The second test was an integrated test with the mobile platform developed for the Resource Prospector project. The OVEN survived both tests without damage, but the tests did provide valuable lessons learned with regards to specific operations. Thermal Vacuum: The OVEN was successfully demonstrated at a temperature range of -50 to 75 C in a thermal vacuum chamber. The need to heat motor gearboxes at lower temperatures was predetermined so this test program was completed by implementing a method of gearbox heating that used the existing circuitry within the motors. Dust: A custom dynamometer was built in order to determine the torque required to move the various mechanisms within the OVEN at a range of temperatures. The OVEN system was coated with lunar dust simulant in order to determine mechanism torques under a worst-case operating condition. Sublimation: Sublimation losses within the OVEN were quantified through a series of test configurations, including an integrated test in a thermal vacuum chamber at Glenn Research Center [2]. Current Work: The OVEN subsystem is currently not a component of any existing prospecting missions, but work continues that will take the lessons learned from previous environmental tests and improve on the design in order to be considered for future prospecting opportunities. References: [1] Colaprete, A., Schultz, P., Heldmann, J., Wooden, D., Shirley, M., Ennico, K., ... & Sollitt, L. (2010). Detection of water in the LCROSS ejecta plume. science, 330(6003), 463-468. [2] Kleinhenz, J., Smith, J., Roush, T., Colaprete, A., Zacny, K., Paulsen, G., ... & Paz, A. (2018). Volatiles Loss from water bearing regolith simulant at Lunar Environments. In Earth and Space 2018: Engineering for Extreme Environments (pp. 454-466). Reston, VA: American Society of Civil Engineers.