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Results for “Complex Constraints”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Optimal aeroassisted orbital transfer with plane change using collocation and nonlinear programming

The fuel optimal control problem arising in the non-planar orbital transfer employing aeroassisted technology is addressed. The mission involves the transfer from high energy orbit (HEO) to low energy orbit (LEO) with orbital plane change. The basic strategy here is to employ a combination of propulsive maneuvers in space and aerodynamic maneuvers in the atmosphere. The basic sequence of events for the aeroassisted HEO to LEO transfer consists of three phases. In the first phase, the orbital transfer begins with a deorbit impulse at HEO which injects the vehicle into an elliptic transfer orbit with perigee inside the atmosphere. In the second phase, the vehicle is optimally controlled by lift and bank angle modulations to perform the desired orbital plane change and to satisfy heating constraints. Because of the energy loss during the turn, an impulse is required to initiate the third phase to boost the vehicle back to the desired LEO orbital altitude. The third impulse is then used to circularize the orbit at LEO. The problem is solved by a direct optimization technique which uses piecewise polynomial representation for the state and control variables and collocation to satisfy the differential equations. This technique converts the optimal control problem into a nonlinear programming problem which is solved numerically. Solutions were obtained for cases with and without heat constraints and for cases of different orbital inclination changes. The method appears to be more powerful and robust than other optimization methods. In addition, the method can handle complex dynamical constraints.

Shi, Yun. Y.↗
NASA NTRS2004

Software for Autonomous Spacecraft Maneuvers

The AutoCon computer programs facilitate and accelerate the planning and execution of orbital control maneuvers of spacecraft while analyzing and resolving mission constraints. AutoCon-F is executed aboard spacecraft, enabling the spacecraft to plan and execute maneuvers autonomously; AutoCon-G is designed for use on the ground. The AutoCon programs utilize advanced techniques of artificial intelligence, including those of fuzzy logic and natural-language scripting, to resolve multiple conflicting constraints and automatically plan maneuvers. These programs can be used to satisfy requirements for missions that involve orbits around the Earth, the Moon, or any planet, and are especially useful for missions in which there are requirements for frequent maneuvers and for resolution of complex conflicting constraints. During operations, the software targets new trajectories, places and sizes maneuvers, and controls spacecraft burns. AutoCon-G provides a userfriendly graphical interface, and can be used effectively by an analyst with minimal training. AutoCon-F reduces latency and supports multiple-spacecraft and formation-flying missions. The AutoCon architecture supports distributive processing, which can be critical for formation- control missions. AutoCon is completely object-oriented and can easily be enhanced by adding new objects and events. AutoCon-F was flight demonstrated onboard GSFC's EO-1 spacecraft flying in formation with Landsat-7.

Bristow, John↗
NASA NTRS1991

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Gabrielian, Armen↗
NASA NTRS2003

Scheduling Earth Observing Satellites with Evolutionary Algorithms

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

Globus, Al↗
NASA NTRS2004

Operational Experiences in Planning and Reconstructing Aqua Inclination Maneuvers

As the lead satellite in NASA's growing Earth Observing System (EOS) PM constellation, it is increasingly critical that Aqua maintain its various orbit requirements. The two of interest for this paper are maintaining an orbit inclination that provides for a consistent mean local time and a semi-major Axis (SMA) that allows for ground track repeatability. Maneuvers to adjust the orbit inclination involve several flight dynamics constraints and complexities which make planning such maneuvers challenging. In particular, coupling between the orbital and attitude degrees of freedom lead to changes in SMA when changes in inclination are effected. A long term mission mean local time trend analysis was performed in order to determine the size and placement of the required inclination maneuvers. Following this analysis, detailed modeling of each burn and its Various segments was performed to determine its effects on the immediate orbit state. Data gathered from an inclination slew test of the spacecraft and first inclination maneuver uncovered discrepancies in the modeling method that were investigated and resolved. The new modeling techniques were applied and validated during the second spacecraft inclination maneuver. These improvements should position Aqua to successfully complete a series of inclination maneuvers in the fall of 2004. The following paper presents the events and results related

Rand, David↗
NASA NTRS2006

Radio Frequency (RF) Attenuation Measurements of the Space Shuttle Vehicle

Following the loss of Columbia, the Columbia Accident Investigation Board (CAIB) provided recommendations to be addressed prior to Return To Flight (RTF). As a part of CAIB Recommendation 3.4.1 - Ground Based Imagery, new C-band and X-band radars were added to the array of ground-based radars and cameras already in-situ at Kennedy Space Center. Because of higher power density considerations and new operating frequencies, the team of Subject Matter Experts (SMEs) assembled to investigate the technical details of introducing the new radars recommended a series of radio frequency (RF) attenuation tests be performed on the Space Shuttle vehicle to establish the attenuation of the vehicle outer mold line structure with respect to its external RF environment. Because of time and complex logistical constraints, it was decided to split the test into two separate efforts. The first of these would be accomplished with the assistance of the Air Force Research Laboratory (AFRL), performing RF attenuation measurements on the aft section of OV-103 (Discovery) while in-situ in Orbiter Processing Facility (OPF) 3, located at Kennedy Space Center. The second would be accomplished with the assistance of the National Institute of Standards and Technology (NIST) and the electromagnetic interference (EMI) laboratory out of the Naval Air Warfare Center, Patuxent River, Maryland (PAX River), performing RF attenuation measurements on OV-105 (Endeavour) in-situ inside the Space Shuttle Landing Facility (SLF) hangar, also located at Kennedy Space Center. This paper provides a summary description of these efforts and their results.

Scully, R. C.↗
DOE OSTI2026

CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery

Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but existing methods rely on scalar rewards that provide limited information about why candidate solutions fail, leading agents to repeatedly explore invalid regions. We introduce Certification-Driven Reinforcement Learning (CDRL), a framework that leverages structured feedback from symbolic reasoning tools. When a candidate violates domain constraints, these tools produce certificates identifying the actions responsible for failure. CDRL converts these certificates into reusable constraints that eliminate classes of invalid solutions and guide exploration toward valid regions. We evaluate CDRL on neutrino flavor model discovery in theoretical particle physics, where the hypothesis space exceeds $10^{26}$ possible models, and compare it with the state-of-the-art RL approach previously used for this task. Across three theory spaces, CDRL achieves up to 1.95$\times$ higher valid model rates and up to 6.33$\times$ higher neutrino model rates while evaluating up to 4$\times$ fewer candidates. We further extract 40 interpretable rules from search trajectories using a post-hoc decision-tree framework and show that reusing them as soft constraints yields gains of up to 2$\times$ in valid model rates and 3$\times$ in neutrino model discovery across all three theory spaces. These results suggest that CDRL uncovers reusable structure in combinatorial search spaces and provides a general framework for scientific model discovery.

Jha, Piyush [Georgia Tech., Atlanta; Georgia Tech]↗
NASA NTRS1983

Information display and interaction in real-time environments

The available information bandwidth as a funcion of system's complexity and time constraints in a real time control environment were examined. Modern interactive graphics techniques provide very high bandwidth data displays. In real time control environments, effective information interaction rates are a function not only of machine data technologies but of human information processing capabilities and the four dimensional resolution of available interaction techniques. The available information bandwidth as a function of system's complexity and time constraints in a real time control environment were examined.

Bocast, A. K.↗
NASA NTRS2017

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Englander, Arnold C.↗
NASA NTRS2017

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

Englander, Arnold C.↗
NASA NTRS1986

Development of sensor augmented robotic weld systems for aerospace propulsion system fabrication

In order to meet stringent performance goals for power and reuseability, the Space Shuttle Main Engine was designed with many complex, difficult welded joints that provide maximum strength and minimum weight. To this end, the SSME requires 370 meters of welded joints. Automation of some welds has improved welding productivity significantly over manual welding. Application has previously been limited by accessibility constraints, requirements for complex process control, low production volumes, high part variability, and stringent quality requirements. Development of robots for welding in this application requires that a unique set of constraints be addressed. This paper shows how robotic welding can enhance production of aerospace components by addressing their specific requirements. A development program at the Marshall Space Flight Center combining industrial robots with state-of-the-art sensor systems and computer simulation is providing technology for the automation of welds in Space Shuttle Main Engine production.

Jones, C. S.↗
NASA NTRS2011

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗
NASA NTRS1993

Crystal-chemistry and partitioning of REE in whitlockite

Partitioning of Rare Earth Elements (REE) in whitlockite is complicated by the fact that two or more charge-balancing substitutions are involved and by the fact that concentrations of REE in natural whitlockites are sufficiently high such that simple partition coefficients are not expected to be constant even if mixing in the system is completely ideal. The present study combines preexisting REE partitioning data in whitlockites with new experiments in the same compositional system and at the same temperature (approximately 1030 C) to place additional constraints on the complex variations of REE partition coefficients and to test theoretical models for how REE partitioning should vary with REE concentration and other compositional variables. With this data set, and by combining crystallographic and thermochemical constraints with a SAS simultaneous-equation best-fitting routine, it is possible to infer answers to the following questions: what is the speciation on the individual sites Ca(B), Mg, and Ca(IIA) (where the ideal structural formula is Ca(B)18 Mg2Ca(IIA)2P14O56); how are REE's charge-balanced in the crystal; and is mixing of REE in whitlockite ideal or non-ideal. This understanding is necessary in order to extrapolate derived partition coefficients to other compositional systems and provides a broadened understanding of the crystal chemistry of whitlockite.

Colson, R. O.↗
NASA NTRS1988

Interactive orbital proximity operations planning system

An interactive graphical proximity operations planning system was developed, which allows on-site design of efficient, complex, multiburn maneuvers in a dynamic multispacecraft environment. Maneuvering takes place in and out of the orbital plane. The difficulty in planning such missions results from the unusual and counterintuitive character of orbital dynamics and complex time-varying operational constraints. This difficulty is greatly overcome by visualizing the relative trajectories and the relevant constraints in an easily interpretable graphical format, which provides the operator with immediate feedback on design actions. The display shows a perspective bird's-eye view of a Space Station and co-orbiting spacecraft on the background of the Station's orbital plane. The operator has control over the two modes of operation: a viewing system mode, which enables the exporation of the spatial situation about the Space Station and thus the ability to choose and zoom in on areas of interest; and a trajectory design mode, which allows the interactive editing of a series of way points and maneuvering burns to obtain a trajectory that complies with all operational constraints. A first version of this display was completed. An experimental program is planned in which operators will carry out a series of design missions which vary in complexity and constraints.

Grunwald, Arthur J.↗
NASA NTRS2020

Evaluation of Packing_3D Code for Design of Variable-Depth, Bent-Chamber Acoustic Liners

Increases in the bypass ratio for commercial aircraft engines have caused the broadband fan noise component to become dominant. As a result, there is a need to develop improved acoustic liners suitable for absorption of this fan noise over a wide frequency range, preferably up to at least two octaves. Variable depth liners with bent chambers and three-dimensional geometries present one way to achieve this goal, however, they can be difficult and time-consuming to design due to their complexity and volume constraints. A packing code, called Packing3D, has been developed that automatically designs the chamber configurations of such liners once the chamber dimensions and volume constraints are known. The code uses a randomized trial and error approach to place each chamber in a representation of the liner sample, then returns a colored diagram and sufficient information for the liner sample to be fabricated. For evaluation, the code is used to design four liner samples of varying levels of complexity. These samples are tested with and without a mesh facesheet in the NASA Langley Normal Incidence Tube, and the results are compared to predictions computed in COMSOL. The results indicate that the packing code is able to quickly design samples that are predictable, achieve the desired absorption spectrum, fit the given constraints, and are able to be built. This code is flexible, lends itself to optimization, and allows samples to be designed quickly, accurately, and efficiently.

Marinova, Miroslava M.↗
NASA NTRS2026

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona↗
DOE OSTI2026

Simply Fabricatable Reference Electrode for Studying Li Metal Interfaces Operando

Reference electrodes are essential for studying Li metal interfaces, yet their integration into coin cells remains challenging due to geometric constraints and assembly complexity. Here, we present a simple three-electrode coin cell design in which a thin Cu film is evaporated directly onto a trilayer PP/PE/PP separator, forming a conductive and flexible in situ current collector. The microporous Cu preserves separator porosity and pressure uniformity, avoiding artifacts introduced by wire- or mesh-type references. It is easily activated by Li plating and provides stable potentials for over 10 days in ether-based electrolytes without affecting Coulombic efficiency (>99%) or Li deposition morphology. Operando measurements using this design reveal electrode-specific impedance evolution and voltage responses otherwise obscured in two-electrode setups, uncovering a correlation between the SEI resistance and electrolyte ionic conductivity. This microporous Cu reference electrode offers a robust and accessible platform for characterizing reactive interfaces under realistic cycling conditions.

Sacci, Robert [ORNL] (ORCID:0000000200735221)↗
NASA NTRS1983

Bringing AI up to the space challenge

The state of the art in automated systems for working in environments hostile to humans is assessed, together with the technological advancements necessary to meet NASA goals. Since completely automated operations are not possible with the current level of artificial intelligence (AI), the operator must have access to remote television access and interactive computerized controls. A proximal system exists when the teleoperated mechanism is close enough so that negligible time passes between operator and servocontrolled activation and feedback. An additional constraint is the complexity of the signal. Further development areas have been identified as limiting the necessary communication, compensating for technical limitations of communication with remote systems, such as bandwidth, error rate, and equipment response time, and to build-in fault tolerance, self-diagnosis, and self-maintenance capabilities. An AI expert system is being developed at JPL to provide an expert knowledge base and a decision-making capability. It is suggested that only thorough questioning of mission and spacecraft experts, as well as searching the large volume of project documentations, will provide the necessary data for establishing an expert data base for AI implementation.

Heer, E.↗