SEARCH · Engineering Papers

Results for “policy solutions”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS2010

NASA UAS Update

Last year may prove to be a pivotal year for the National Aeronautics and Space Administration (NASA) in the Unmanned Aircraft Systems (UAS) arena, especially in relation to routine UAS access to airspace as NASA accepted an invitation to join the UAS Executive Committee (UAS ExCom). The UAS ExCom is a multi-agency, Federal executive-level committee comprised of the Federal Aviation Administration (FAA), Department of Defense (DoD), Department of Homeland Security (DHS), and NASA with the goals to: 1) Coordinate and align efforts between key Federal Government agencies to achieve routine safe federal public UAS operations in the National Airspace System (NAS); 2) Coordinate and prioritize technical, procedural, regulatory, and policy solutions needed to deliver incremental capabilities; 3) Develop a plan to accommodate the larger stakeholder community at the appropriate time; and 4) Resolve conflicts between Federal Government agencies (FAA, DoD, DHS, and NASA), related to the above goals. The committee was formed in recognition of the need of UAS operated by these agencies to access to the National Airspace System (NAS) to support operational, training, development and research requirements. In order to meet that need, technical, procedural, regulatory, and policy solutions are required to deliver incremental capabilities leading to routine access. The formation of the UAS ExCom is significant in that it represents a tangible commitment by FAA senior leadership to address the UAS access challenge. While the focus of the ExCom is government owned and operated UAS, civil UAS operations are bound to benefit by the progress made in achieving routine access for government UAS. As the UAS ExCom was forming, NASA's Aeronautics Research Mission Directorate began to show renewed interest in UAS, particularly in relation to the future state of the air transportation system under the Next Generation Air Transportation System (NextGen). NASA made funding from the American Recovery and Revitalization Act available in order to continue addressing the issue of routine civil UAS access.

Bauer, Jeffrey Ervin↗

NASA NTRS2022

Lunar Landing and Operations Policy Analysis

Just within the next four years, we expect to see at least 22 lunar surface missions. Half of these missions will occur in the Moon’s south polar region. Due to this upcoming proliferation of actors and activities at or near the lunar south pole, and due to the potential close proximity of operations, NASA and other operators will face challenges never faced before. NASA’s Deputy Administrator and Associate Administrator of the Science Mission Directorate (SMD) tasked the Office of Technology, Policy, and Strategy (OTPS) with answering two questions related to the Artemis campaign: (1) what technical and policy considerations should NASA take into account in the selection of lunar landing and operations sites, and (2) what technical and policy considerations should NASA take into account when implementing tools such as safety zones in order to protect these operations and U.S. interests? In addition to the challenges inherent in lunar operations, NASA subject-matter experts (SMEs) are concerned about certain challenges to NASA operations that may require policy solutions. The goal of this report is to provide options and recommendations to NASA leadership and program planners so that they can consider policy measures to respond to those challenges. This report also describes options for transparency, coordination, and implementation to increase the effectiveness of these measures.

lunar policy↗

NASA NTRS2021

Finding and Fixing Food System Emissions: The Double Helix of Science and Policy

Improving estimates of greenhouse gas (GHG) emissions from food production, supply, consumption, and disposal is fundamental to identifying effective policy solutions. Through broader awareness of the food-climate nexus, climate mitigation as well as resilience can be enhanced. However, work is needed to address knowledge gaps, promote better policies and improve public understanding of issues related to the food system and climate change. The intention of this paper is not only to highlight the need for better scientific understanding of the processes through which GHGs are emitted—from production to processing, from supply chains and retail to food preparation and waste (figure 1)—but also to integrate science and policy in order to scale up impact on climate change action.

food systems↗

NASA NTRSDate not supplied

Exploring the Low-Thrust Transfer Design Space in an Ephemeris Model via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective reinforcement learning algorithm used to train multiple policies to uncover solutions within a multi-objective solution space. MRPPO is used in this paper to train policies to construct low-thrust transfers for a SmallSat from the vicinity of !2 to an !5 short period orbit in the Sun-Earth-Moon system. First, the policies are trained in this scenario in the circular restricted three-body problem. This information is used to initialize the policies before training in a higher-fidelity ephemeris model; a process known as transfer learning. The recovered segments of the solution space will be compared to fundamental dynamical structures to both examine the results of MRPPO in this complex design scenario and explore the effectiveness of transfer learning.

Christopher J Sullivan↗

NASA NTRSDate not supplied

Exploring the Low-Thrust Transfer Design Space in an Ephemeris Model via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective reinforcement learning algorithm used to train multiple policies to uncover solutions within a multi-objective solution space. MRPPO is used in this paper to train policies to construct low-thrust transfers for a SmallSat from the vicinity of L2 to an L5 short period orbit in the Sun-Earth-Moon system. First, the policies are trained in this scenario in the circular restricted three-body problem. This information is used to initialize the policies before training in a higher-fidelity ephemeris model; a process known as transfer learning. The recovered segments of the solution space will be compared to fundamental dynamical structures to both examine the results of MRPPO in this complex design scenario and explore the effectiveness of transfer learning.

Christopher J. Sullivan↗

NASA NTRS2022

Exploring the Low-Thrust Transfer Design Space in an Ephemeris Model via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization (MRPPO) is a multi-objective reinforcement learning algorithm used to train multiple policies to uncover solutions within a multi-objective solution space. MRPPO is used in this paper to train policies to construct low-thrust transfers for a SmallSat from the vicinity of 𝐿2 to an 𝐿5 short period orbit in the Sun-Earth-Moon system. First, the policies are trained in this scenario in the circular restricted three-body problem. This information is used to initialize the policies before training in a higher-fidelity ephemeris model; a process known as transfer learning. The recovered segments of the solution space will be compared to fundamental dynamical structures to both examine the results of MRPPO in this complex design scenario and explore the effectiveness of transfer learning.

Mashiku, Alinda K.↗

NASA NTRS1987

Control-System Design Program

Control-theory design package, Optimal Regulator Algorithms for Control of Linear Systems (ORACLS), developed to aid in design of controllers and optimal filters for systems modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, Linear-Quadratic-Gaussian (LQG) problem, most widely accepted method of determining optimal control policy. Provides for solution to time-in-variant continuous or discrete LQG problems. Attractive to control-system designer providing rigorous tool for dealing with multi-input and multi-output dynamic systems in continuous and discrete form. CDO version written in FORTRAN IV. VAX version written in FORTRAN 77.

Frisch, Harold P.↗

NASA NTRSDate not supplied

106 Co-Signatories of the Planetary Science and Astrobiology Decadal Survey 2023-2032 White Paper

The field of exoplanetary science has emerged over the past two decades, rising up alongside traditional solar system planetary science. Both fields focus on understanding the processes which form and sculpt planets through time, yet there has been less scientific exchange between the two communities than is ideal. I will report on our white paper which explores some of the institutional and cultural barriers impeding cross-discipline collaborations. Our suggestions for fostering greater collaboration between the disciplines will be described. Some solutions require structural or policy changes within NASA itself, while others are directed towards other institutions, including academic publishers, that can also facilitate greater interdisciplinarity.

M. Marley↗

NASA NTRS2011

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Marshall Space Flight Center (MSFC) Engineering Directorate, total lifecycle costs are important variables for critical decision-making. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful concept to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This briefing will demonstrate how the MSFC Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions and how that strategy aligns with the Agency and Center systems engineering policies and processes. Sustainable space exploration solutions demand that all lifecycle phases be optimized, and engineering the next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. Adopting PLM, which has been used by the aerospace and automotive industry for many years, for spacecraft applications provides a foundation for strong, disciplined systems engineering and accountable return on investment. PLM enables better solutions using fewer resources by making lifecycle considerations in an integrative decision-making process.

Caruso, Pamela W.↗

NASA NTRS1978

Optimal analytic rendezvous using Clohessy-Wiltshire equations

The optimal solution time that minimizes the sum of the two applied impulses necessary to rendezvous is obtained analytically for the Clohessy-Wiltshire equations with a linear gravity model assumption. A plume impingement inequality constraint on the solution is examined, and an optimal policy is developed. Numerical tests are conducted to verify the analysis and to illustrate the optimal solution algorithm.

Jezewski, D. J.↗

NASA NTRS1979

An analytic approach to optimal rendezvous using Clohessy-Wiltshire equations

An analytic approach is used to obtain the optimal solution time that minimizes the sum of the two applied impulses necessary to rendezvous for the Clohessy-Wiltshire equations. A plume impingement inequality constraint on the solution is examined, and an optimal policy is developed. Numerical tests are conducted to verify the analysis and to illustrate the optimal solution algorithm.

Jezewski, D. J.↗

NASA NTRS2016

Considerations in Managing the Fill Rate of the Grand Ethiopian Renaissance Dam Reservoir Using a System Dynamics Approach.

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8-15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

system dynamics↗

NASA NTRSDate not supplied

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.

Zhe Wang↗

NASA NTRSDate not supplied

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

Zhe Wang↗

NASA NTRS1983

Optimal design and use of retry in fault tolerant real-time computer systems

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Lee, Y. H.↗

NASA NTRSDate not supplied

Identifying Outside Influences as Latent Factors to Risk in Human Performance

During the Acquisition Life Cycle for a program, there are several opportunities for the system in design to be adjusted in accordance with its changing landscape as it is being shaped by evolving policy and organizational culture. Human Systems Integration is integral to identifying these opportunities of change as there are a set number of activities that may account for altered operational states, human performance deviations, and overall component engagement if HSI is enacted early enough in the life cycle. Some changes that occur in the operational environment may not be accounted for since the organizational culture and practices are not currently a part of the HSI focus. Likewise, policy changes themselves from a top-to-bottom analysis may not have the appearance of effecting human performance until having gone through a trail-and-error period. Workarounds to adjust for unforeseen policy affects become the system's solution that usually includes changes in the training and education of the operators, maintainers, and support personnel. A system full of workarounds and off-normal practices, that cause operators to disregard the purpose of the design, coupled with the false notion that these activities are proven for successful system operation, is the very definition of “an accident waiting to happen”. Unforeseen changes in policies and practices that cause new and unusual activities to successfully and keep the system running, should be considered latent factors that may cause a potential mishap, and not part of the resilience that humans provide to the successful operation of the system. This presentation will explore how latent factors may find their way into system operations and how they can be identified and addressed.

Human Systems Integration↗

NASA NTRS1989

Guidance analysis of the aeroglide plane change maneuver as a turning point problem

The development of guidance approximations for the atmospheric (aeroglide) portion of the minimum fuel, orbital plane change, trajectory optimization problem is described. Asymptotic methods are used to reduce the two point, boundary value, optimization problem to a turning point problem from the bank angle control. The turning point problem solution, which yields an approximate optimal control policy, is given in terms of parabolic cylinder functions, which are tabulated, and integral expressions, which must be numerically computed. Comparisons of the former, over their region of validity, with optimal control solutions show good qualitative agreement. Additional work and analysis is needed to compute the guidance approximation work.

Gracey, Christopher↗

NASA NTRS2005

Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast U.S.

We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.

Paudel, Krishna P.↗