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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Allocation of Functions in a Far-Term Air Traffic Control Environment

A human-in-the-loop exploration of a ground-based automated separation assurance concept was conducted that involved the allocation of certain functions between humans and automation. This exploration included operations that were sustained for prolonged periods of time with high levels of traffic in the presence of convective weather and scheduling constraints. An investigation into the acceptability of the defined roles and performance of tasks was conducted where it was found that the participants rated the concept and allocation of functions with a high level of acceptability. However, issues were encountered with the automation related to the detection of and response to tactical conflicts. Lower ratings were given on account of these concerns, and it was found that a key contributor to the underlying problems was transitioning aircraft and the uncertainty of their trajectories. Stemming from those results, participants responded that they would rather have direct control over aircraft transitions as well as more control over the tactical conflict resolution automation. In contrast, participants responded that they would rather have the automation place aircraft back on trajectory, and perform weather avoidance and scheduling tasks.

Homola, Jeffrey↗
NASA NTRS1967

The Allocation of Federal Expenditures Among States

This study explores factors associated with the allocation offederal expenditures by states and examines the implications of theseexpenditures on the state by state distribution of incomes. Theallocation of federal expenditures is functionally oriented toward theobjectives for which various government programs are set up. Thegeographical distribution of federal expenditures, therefore, washistorically considered to be a problem incidental to governmentactivity. Because of this, relatively little attention was given tothe question of why some states receive more federal allocation thanothers. In addition, the implications of this pattern of allocationamong the several states have not been intensively investigated.

Lee, Maw Lin↗
NASA NTRS2016

Capturing Safety Requirements to Enable Effective Task Allocation Between Humans and Automaton in Increasingly Autonomous Systems

There is a current drive towards enabling the deployment of increasingly autonomous systems in the National Airspace System (NAS). However, shifting the traditional roles and responsibilities between humans and automation for safety critical tasks must be managed carefully, otherwise the current emergent safety properties of the NAS may be disrupted. In this paper, a verification activity to assess the emergent safety properties of a clearly defined, safety critical, operational scenario that possesses tasks that can be fluidly allocated between human and automated agents is conducted. Task allocation role sets were proposed for a human-automation team performing a contingency maneuver in a reduced crew context. A safety critical contingency procedure (engine out on takeoff) was modeled in the Soar cognitive architecture, then translated into the Hybrid Input Output formalism. Verification activities were then performed to determine whether or not the safety properties held over the increasingly autonomous system. The verification activities lead to the development of several key insights regarding the implicit assumptions on agent capability. It subsequently illustrated the usefulness of task annotations associated with specialized requirements (e.g., communication, timing etc.), and demonstrated the feasibility of this approach.

Neogi, Natasha A.↗
NASA NTRS2016

Function Allocation between Automation and Human Pilot for Airborne Separation Assurance

Maintaining safe separation between aircraft is a key determinant of the airspace capacity to handle air transportation. With the advent of satellite-based surveillance, aircraft equipped with the needed technologies are now capable of maintaining awareness of their location in the airspace and sharing it with their surrounding traffic. As a result, concepts and cockpit automation are emerging to enable delegating the responsibility of maintaining safe separation from traffic to the pilot; thus increasing the airspace capacity by alleviating the limitation of the current non-scalable centralized ground-based system. In this paper, an analysis of allocating separation assurance functions to the human pilot and cockpit automation is presented to support the design of these concepts and technologies. A task analysis was conducted with the help of Petri nets to identify the main separation assurance functions and their interactions. Each function was characterized by three behavior levels that may be needed to perform the task: skill, rule and knowledge based levels. Then recommendations are made for allocating each function to an automation scale based on their behavior level characterization and with the help of Subject matter experts.

Idris, Husni↗
NASA NTRS2016

A Review of Function Allocation and En Route Separation Assurance

Today's air traffic control system has reached a limit to the number of aircraft that can be safely managed at the same time. This air traffic capacity bottleneck is a critical problem along the path to modernization for air transportation. The design of the next separation assurance system to address this problem is a cornerstone of air traffic management research today. This report reviews recent work by NASA and others in the areas of function allocation and en route separation assurance. This includes: separation assurance algorithms and technology prototypes; concepts of operations and designs for advanced separation assurance systems; and specific investigations into air-ground and human-automation function allocation.

Lewis, Timothy A.↗
NASA NTRS2018

Predicting Crew Time Allocations for Lunar Orbital Missions Based on Historical ISS Operational Activities

As the National Aeronautics and Space Administration continues to define candidate architectures for the planned lunar “Gateway”, it will be necessary to have a detailed understanding of how the crew will inhabit, operate, and maintain the spacecraft. The nature of the Gateway vehicle systems configuration and operations will have a direct impact on the scope of work activities required of the crew. Crew work schedules are sensitive to variations in spacecraft architecture, visiting vehicle activities, and logistics operations – particularly within short duration missions as initially planned for the lunar Gateway. These system and operational configurations must be taken into account when planning for crew time availability to conduct science activities on Gateway missions. This paper presents a methodology that is used to predict crew time distributions for lunar Gateway missions, as applied in NASA’s Exploration Crew Time Model (ECTM). The process utilized for evaluating crew time distributions is based on the categorization of all crew activities into a standardized ontology. Historical ISS daily crew timeline data from July 20, 2011 (post STS retirement) to present day was captured via the Operational Planning Timeline Integration System (OPTimIS) database and characterized according to the standardized ontology. This process enabled correlation and statistical analysis of the ISS data according to common mission parameters such as crew size, ECLSS system design, vehicle traffic operations, and logistics delivery operations. The results of the statistical analysis are a set of crew time distributions for each activity category. These distributions are then utilized within the ECTM to examine crew time allocations based on mission parameter inputs, which serve to characterize the Gateway mission configurations. Results for predicted crew time allocations for representative short duration Gateway missions are presented. These results can be used to evaluate crew schedule availability for science and utilization activities. Variations in expected mission architectures and mission operations are accounted for to correct crew time predictions. The analysis is being leveraged to plan utilization capability objectives that are achievable on the Gateway missions, as well as inform the viability of various mission architecture options.

Stromgren, Chel↗
NASA NTRS2020

Modeling Uncertainty in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. This study introduces a novel numerical method to solve large-scale dynamic stochastic natural resource allocation problems that cannot be addressed by conventional methods. The method is illustrated with an application focusing on the allocation of global land resource use under stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters, the range of land conversion is considerably smaller for the dynamic stochastic model as compared to deterministic scenario analysis. The scenario analysis can thus significantly overstate the magnitude of expected land conversion under uncertain crop yields.

Cai, Yongyang↗
NASA NTRS2018

Human-Automation Allocations for Current Robotic Space Operations: Space Station Remote Manipulator System

NASA’s Human Research Program’s Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) delineates the uncertainty surrounding crew work with automation and robotics in spaceflight. HARI is concerned with detrimental effects of ineffective user interfaces, system designs and/or functional task allocation on crew performance, potentially compromising mission success and safety. This risk arises because of limited experience with complex automation and robotics in spaceflight. One key knowledge gap within the HARI risk is related to function allocation.

Chang, Mai Lee↗
NASA NTRSDate not supplied

Multiple-Effector Control Allocation: Theory and Practice

Redundant controls are ubiquitous in many aerospace domains, including aircraft, spacecraft, and launch vehicles. Multiple control effectors having different capabilities (e.g., reaction controls, aerosurfaces, and vectored engines) must be optimally allocated to achieve high-performance and robust vehicle control, while considering different constraints, cost, or performance metrics associated with various control mixing schemes. These can include force or deflection limits, rate limits, propellant usage or drag penalties, cross-axis coupling, uncertainties, or even servoelastic interactions. This presentation introduces the fundamentals of control allocation theory, based on linear algebra and convex sets, using a handful of examples taken from the air and space vehicle domains. It is shown that even simple methods can provide verifiable and quantifiable performance benefits over ad-hoc approaches, and can support enhanced functions like fault tolerance and control reconfiguration.

Bill Benson↗
NASA NTRSDate not supplied

Joint Communication Resource Allocation and Velocity Selection in Urban Air Mobility via Multi-agent Reinforcement Learning

With traffic congestion problems becoming more severe in urban areas, the National Aeronautics and Space Administration promotes the Urban Air Mobility (UAM) concept, which envisages a safe and efficient air transportation system. However, the increased communication demands in UAM can exacerbate the spectrum scarcity. Therefore, a new communication resource allocation solution is necessary. In this paper, we focus on uplink UAM communications, where multiple aerial vehicles (AV) perform cargo/passenger delivery tasks. With predefined flight paths, AVs make decisions on communication resource allocation and velocity selection to complete their missions under safety constraints. Accordingly, we formulate a joint optimization problem to minimize the weighted sum of the total travel time and communication outage time. We first model the optimization problem as a Markov game and propose a multi-agent reinforcement learning based solution. Simulation results corroborate the effectiveness of the proposed solution.

Ruixuan Han↗
DOE OSTI2026

The Myth of Fungible FTE: A Quantitative Assessment of Matrixed Resource Allocation

Matrix organizations allow scientific facilities to share specialized personnel across projects, operations, maintenance, and strategic initiatives. Nominal staffing allocations, however, may not capture the schedule consequences of fragmented individual commitments, limited access to specialist groups, and intermittent availability of key decision makers. We developed a stochas- tic, daily-time-step simulation of a hypothetical medium-sized accelerator-facility project com- prising sequential phases and parallel tasks. Each task requires role-specific work measured in FTE-days. Ordinary personnel may be unavailable because they contribute concurrently to other institutional activities, while designated key roles have independently specified daily un- availability probabilities. An organization-wide priority factor scales the number of people from each functional group who can effectively contribute to the project. It is interpreted as a composite proxy for project access and workforce fragmentation across competing commit- ments. We examined project completion time as a function of this factor and Project Lead unavailability using 100 Monte Carlo runs per condition. Increasing priority factor from 0.1 to 1.0 reduced median completion time from 1708.5 days (interquartile range 1681.5–1735.25) to 390 days (interquartile range 379–399). At priority factor = 0.1, increasing Project Lead unavailability from 0.5 to 0.9 increased median completion time from 1713.5 days (interquartile range 1691–1733.25) to 4,417 days (interquartile range 4271.75–4550.5). The model quantifies the commonly expected sensitivity of project schedules to fragmented resource commitments and limited coordination availability. Within this model, the results also indicate a possible threshold regime in which small increases in workforce availability yield only modest sched- ule improvements until sufficient capacity becomes accessible, after which project performance improves sharply. With further validation and calibration, this quantitative framework could support resource-allocation decisions during initial project planning and subsequent schedule rebaselining.

Bai, Mei [SLAC National Accelerator Laboratory (SL↗
DOE OSTI2025

Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm setting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Resolving Mixtures of Soot Characterized by SP-AMS Spectra Using a Latent Dirichlet Allocation Model

Soot produced by detonation or combustion events exhibits different chemical properties depending on the fuel, device construction, and environmental conditions in which the event occurs. These properties can be useful for defining relevant signatures for probabilistically identifying the different types of events that occurred, based on the soot that is produced from these events. However, it is rare to observe samples of soot from a detonation or combustion that are not contaminated by outside particles. In this paper, we present a method for resolving mixtures of soot to determine the contributions of sources that may be present in samples of recovered soot. We use Latent Dirichlet Allocation to describe the generative process for a sample of recovered soot, and use Variational Bayesian Inference to learn about the parameters associated with the generative model. We demonstrate the utility of this method by considering real samples of mixtures of soot under various frameworks to show that the model is able to identify the different components present in a sample of soot as well as their mixing proportions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Policy and Cost Allocation Considerations for Large Electric Load Interconnections: Emerging Policy Trends in Rate Structures, Interconnection, and Cost Impacts on Other System Users

Load growth in the United States is rapidly increasing: load from data centers alone has tripled over the past decade, and this growth is forecasted to continue accelerating. These and other large electric loads (LELs) promise economic benefits at the state and local level, but their deployment has also led to increasing concerns about grid impacts and potential cost shifts onto other ratepayers. Legislators, regulators, and other stakeholders are increasingly proposing and enacting policies in effort to balance these and other considerations. This white paper reviews state-level legislation, selected utility rate cases, and relevant federal orders in an effort to describe and categorize relevant trends in policies related to LEL cost allocation, interconnection, and deployment. Policy categories identified through this review include tax incentives, rate actions, and requirements related to interconnection, permitting, and reporting. By offering a taxonomy of policies, this white paper aims to offer a resource to policymakers and other stakeholders navigating this transformative moment for the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2002

The JPL Resource Allocation Planning and Scheduling Office (RAPSO) process

The Jet Propulsion Laboratory's Resource Allocation Planning and Scheduling Office is chartered to divide the limited amount of tracking hours of the Deep Space Network amongst the various missions in as equitable allotment as can be achieved. To best deal with this division of assets and time, an interactive process has evolved that promotes discussion with agreement by consensus between all of the customers that use the Deep Space Network (DSN). Aided by a suite of tools, the task of division of asset time is then performed in three stages of granularity. Using this approach, DSN loads are either forecasted or scheduled throughout a moving 10-year window.

RAPSO Resource Allocation Planning and Scheduling ↗
NASA NTRSDate not supplied

Examination of Unified Control Incorporating Generalized Control Allocation

Hybrid vehicles which combine vertical take off and landing with cruise configurations pose a unique challenge for control design and implementation. For this class of vehicle, successful control designs have historically broken the flight envelope into phases of flight and modified the control approach for each phase. This research approaches control in a unified way across the entire envelope utilizing a robust optimal design which provides effect or weighting then implemented in a generalized Affine Generalized Inverse control allocation algorithm. System performance for a Lift plus Cruise class vehicle is presented.

Unified Control,Control Allocation↗
NASA NTRSDate not supplied

Examination of Unified Control Approaches Incorporating Generalized Control Allocation

Transition vehicles which combine vertical take off and landing with cruise configurations pose a unique challenge for control design and implementation. For this class of vehicle, successful control designs have historically broken the flight envelope into phases and modified the control approach for each phase. This research approaches control in a unified way across the entire envelope using a robust optimal design which provides effector weighting then implemented in a generalized Affine Generalized Inverse control allocation algorithm. System performance for a Lift plus Cruise transition vehicle is presented.

unified control, robust control, optimal control, ↗