SEARCH · Search NASA
Results for “ALLOCATIONS”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 2: Resource allocation and smoothing model, programmer's manual
Appendixes are presented that provide model input requirements, a sample case, flow charts, and a program listing. At the beginning of each appendix, descriptive details and technical comments are provided to indicate any special instructions applicable to the use of that appendix. In addition, the program listing includes comment cards that state the purpose of each subroutine in the complete program and describe operations performed within that subroutine. The input requirements includes details on the many options that adapt the program to the specific needs of the analyst for a particular problem.
Human-Automation Allocations for Current Robotic Space Operations
Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.
Applicability and Limitations of Reliability Allocation Methods
Reliability allocation process may be described as the process of assigning reliability requirements to individual components within a system to attain the specified system reliability. For large systems, the allocation process is often performed at different stages of system design. The allocation process often begins at the conceptual stage. As the system design develops, more information about components and the operating environment becomes available, different allocation methods can be considered. Reliability allocation methods are usually divided into two categories: weighting factors and optimal reliability allocation. When properly applied, these methods can produce reasonable approximations. Reliability allocation techniques have limitations and implied assumptions that need to be understood by system engineers. Applying reliability allocation techniques without understanding their limitations and assumptions can produce unrealistic results. This report addresses weighting factors, optimal reliability allocation techniques, and identifies the applicability and limitations of each reliability allocation technique.
Evolutionary Game and Simulation Research of Blockchain-Based Co-Governance of Emergency Supply Allocation
Recently, with the spread of COVID-19 pandemic, emergency supply allocation system is drawing more and more social attention. Emergency supply allocation system is an important part of emergency governance system. It reflects social organizations’ credibility, public safety, and the modernization level of social governance. However, emergency supply allocation system still has some problems, such as information asymmetry, different desires of participants, unreasonable allocation, and so on. At present, it is widely accepted that the advantage of blockchain in co-governance could be of great help in solving above problems. And in order to distinguish the effect of blockchain to the emergency supply allocation, the paper builds a tripartite evolutionary game model among the government, social organizations, and the public to analyse the impact of blockchain platform on emergency supply allocation. The simulation analysis shows the following: (1) The strategy choices of the government have a crucial impact on the evolution and stability of social organizations’ strategies. It needs a long-term process to guide social organizations practicing active allocation, and the government should accelerate to build the blockchain platform to promote this process. (2) With the help of blockchain platform, the increment of penalty intensity of the government is conductive to increasing the probabilities that social organizations practice active allocation and the government practices strict supervision. (3) Blockchain platform has a significant impact on social organizations’ choice for active allocation in many aspects, such as the positive and negative effects of social organizations, effect’s increasing multiple, and the cost of the public informing. In the end, some suggestions are presented to improve the co-governance of emergency supply allocation.
Nonlinear burn control in ITER using adaptive allocation of actuators with uncertain dynamics
Abstract ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabilizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excursions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma–wall interactions). The controller regulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma electrons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an actuator allocation module that optimally maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). Two different actuator allocators are presented in this work. The first actuator allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. It is nonadaptive and assumes that the mapping between the commanded control efforts and the allocated actuators (i.e. the effector model) contains no uncertainties. The second actuator allocation module has an adaptive estimator to handle uncertainties in the effector model. This uncertainty includes actuator efficiencies, the fractions of neutral beam heating that are deposited into the plasma electrons and ions, and the tritium concentration of the fueling pellets. Furthermore, the adaptive allocator considers actuator dynamics (actuation lag) that contain uncertainty. This adaptive allocation algorithm is more computationally efficient than the aforementioned nonadaptive allocator because it is computed using dynamic update laws so that finding the solution to a static optimization problem is not required at every time step. A simulation study assesses the performance of the proposed adaptive burn controller augmented with each of the actuator allocation modules.
An intelligent allocation algorithm for parallel processing
The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.
Task allocation among multiple intelligent robots
Researchers describe the design of a decentralized mechanism for allocating assembly tasks in a multiple robot assembly workstation. Currently, the approach focuses on distributed allocation to explore its feasibility and its potential for adaptability to changing circumstances, rather than for optimizing throughput. Individual greedy robots make their own local allocation decisions using both dynamic allocation policies which propagate through a network of allocation goals, and local static and dynamic constraints describing which robots are elibible for which assembly tasks. Global coherence is achieved by proper weighting of allocation pressures propagating through the assembly plan. Deadlock avoidance and synchronization is achieved using periodic reassessments of local allocation decisions, ageing of allocation goals, and short-term allocation locks on goals.
Soil nutrients affect biomass allocation at the individual tree level in Populus_deltoides
The allocation of carbon (C) to tree roots has implication for forest productivity and soil C storage. Here, we elucidated the factors affecting absolute and relative production of resource-acquiring absorptive fine roots (AFR) and other tree organs. We assessed soil properties, leaf (Leaves), stem and branch (Stem-Br), coarse root (CR), transport fine root (TFR), and AFR biomass, production, and allocation and leaf litterfall and AFR and TFR turnover for 12 trees in a youngPopulus deltoides plantation. On a biomass basis, standing crop of AFRs was significantly related to that of TFRs, but both were independent of biomass of leaves, CRs and Stem-Brs. Production (standing crop + turnover) as a proportion of total biomass (allocation) highlighted significant relationships between AFR%, TFR%, and tree and soil characteristics. AFR% and TFR% were negatively correlated with Stem-Br%, Leaf%, and total tree production. Spatial variation in soil nutrient gradients altered allocation withinP. deltoides.AFR% and TFR% were negatively correlated with CEC, N, and Ca but positively correlated with soil P, Fe, and Na. Stem-Br% was positively correlated with CEC and soil N but negatively correlated with P. AFR and TFR growth and death are tightly coupled at the individual tree level. AFR allocation, but not standing biomass, is highly correlated with allocation to leaves, suggesting tight regulation of the growth of these two resource-acquiring organs. Lower soil N and Ca increased allocation to AFRs at the cost of leaves, whereas allocation to AFRs and leaves increased with soil P. Such changes in response to soil P may control whole-tree production in the current study.
Effects of nitrogen enrichment on tree carbon allocation: A global synthesis
Aim: Increased atmospheric nitrogen deposition may have profound effects on tree carbon allocation dynamics. However, a comprehensive understanding of how nitro-gen (N) enrichment influences carbon (C) allocation across plant functional processes and tree organs in individual trees remains elusive. Location: Global forest ecosystems. Time period: 1990–2018. Major taxa studied: Trees. Methods: We compiled data from 75 N addition experiments and conducted a meta-analysis to evaluate the responses of C source (photosynthesis), sinks (growth and respiration) and storage (non-structural carbohydrate concentrations) in different tree organs (foliage, above-ground wood and roots) to N enrichment. Results: N enrichment significantly enhanced C supply via photosynthesis (+39.6%, n = 128). C allocation to growth (biomass increment/production) significantly in-creased in foliage (+15.9%, n = 68) and above-ground wood (+31.8%, n = 64; bole, branch, stem and/or twig) with increasing N availability, but not in roots, whereas allocation increased in roots via increasing fine root turnover rate (+22.6%, n = 11). N fertilization significantly increased C allocation to respiration in above-ground wood (+46.6%, n = 12) and roots (+5.5%, n = 57), but not in foliage. N addition decreased non-structural carbohydrate (NSC) concentrations in foliage (-5.4%, n = 16) and roots (-5.0%, n = 21), but increased NSC in above-ground wood (+6.1%, n = 22). In addition, N enrichment effects were strongly affected by moderator variables. Main conclusions: Our results demonstrate that N addition increased C allocation to growth and respiration more strongly than C allocation to NSC storage, and increased C allocation to above-ground parts more strongly than to below-ground parts. Our results are useful for better understanding the response of tree functional processes at organ level to N enrichment. The existing data also reveal that more long-term ex-perimental studies on mature trees in tropical and boreal forests are urgently needed to provide a basis for forecasting tree responses to N enrichment at the global scale.
Spectrum allocations above 40 GHz
The 1979 World Administrative Radio Conference (WARC-79) revised the International Table of Frequency Allocations to reflect increased interest and activity in the region of the EM spectrum above 40 GHz. The total width of the spectrum allocated (235 GHz) in the region above 40 GHz indicates the extent of this new spectrum resource, made accessible by advances in the state-of-the-art of telecommunications equipment. There are some striking differences between the approach to allocation above and below 40 GHz. For example, there are not bands allocated exclusively. This reflects the characteristics of propagation and the small antenna beamwidths achievable at these frequencies. Attention is given to atmospheric window and absorption band limits, allocations to satellite services, allocations to scientific services, allocations to terrestrial services, the future refinement of the radio regulations above 40 GHz, and allocations of WARC-79 and frequency management.
Methodology to Support Dynamic Function Allocation Policies Between Humans and Flight Deck Automation
Function allocation assigns work functions to all agents in a team, both human and automation. Efforts to guide function allocation systematically have been studied in many fields such as engineering, human factors, team and organization design, management science, cognitive systems engineering. Each field focuses on certain aspects of function allocation, but not all; thus, an independent discussion of each does not address all necessary aspects of function allocation. Four distinctive perspectives have emerged from this comprehensive review of literature on those fields: the technology-centered, human-centered, team-oriented, and work-oriented perspectives. Each perspective focuses on different aspects of function allocation: capabilities and characteristics of agents (automation or human), structure and strategy of a team, and work structure and environment. This report offers eight issues with function allocation that can be used to assess the extent to which each of issues exist on a given function allocation. A modeling framework using formal models and simulation was developed to model work as described by the environment, agents, their inherent dynamics, and relationships among them. Finally, to validate the framework and metrics, a case study modeled four different function allocations between a pilot and flight deck automation during the arrival and approach phases of flight.
Developing capacitated p-median location-allocation model in the spopt library to allow UCL student teacher placements using public transport
Location-allocation is a key tool within the GIS and network analysis toolbox. In this paper we discuss the real world application of a location-allocation case study (approx 800 students, 500 schools) from UCL using public transport. The use of public transportation is key for this case study, as many location-allocation approaches only make use of drive-time or walking-time distances, but the location of UCL in Greater London, UK makes the inclusion of public transport vital for this case study. The location-allocation is implemented as a capacitated p-median location-allocation model, using the spopt library, part of the Python Spatial Analysis Library (PySAL). The capacitated variation of the p-median location-allocation problem is a new addition to the spopt library, which this work will present. The results from the initial version of the capacitated p-median location-allocation problem has shown a marked improvement on public transport travel time, with public transport travel time reduced by 891 minutes overall for an initial sample of 93 students (9.58 minutes per student). Results will be presented below and plans for further improvement shared.
Patch Network for Power Allocation and Distribution in Smart Materials
The power allocation and distribution (PAD) circuitry is capable of allocating and distributing a single or multiple sources of power over multi-elements of a power user grid system. The purpose of this invention is to allocate and distribute power that is collected by individual patch rectennas to a region of specific power-user devices, such as actuators. The patch rectenna converts microwave power into DC power. Then this DC power is used to drive actuator devices. However, the power from patch rectennas is not sufficient to drive actuators unless all the collected power is effectively used to drive another group by allocation and distribution. The power allocation and distribution (PAD) circuitry solves the shortfall of power for devices in a large array. The PAD concept is based on the networked power control in which power collected over the whole array of rectennas is allocated to a sub domain where a group of devices is required to be activated for operation. Then the allocated power is distributed to individual element of power-devices in the sub domain according to a selected run-mode.
Proposal Drafted for Allocating Space-to-Space Frequencies in the GPS Spectrum Bands
Radionavigation Satellite Service (RNSS) systems such as the U.S. Global Positioning System (GPS) and the Russian Global Navigation Satellite System (GLONASS) are primarily being used today in the space-to-Earth direction (i.e., from GPS satellite to Earth user) for a broad range of applications such as geological surveying; aircraft, automobile, and maritime navigation; hiking and mountain climbing; and precision farming and mining. However, these navigation systems are being used increasingly in space. Beginning with the launch of the TOPEX/Poseidon remote-sensing mission in 1992, over 90 GPS receivers have flown onboard spacecraft for such applications as real-time spacecraft navigation, three-axis attitude control, precise time synchronization, precision orbit determination, and atmospheric profiling. In addition to use onboard many science spacecraft, GPS has been used or is planned to be used onboard the shuttles, the International Space Station, the International Space Station Emergency Crew Return Vehicle, and many commercial satellite systems such as Orbcomm, Globalstar, and Teledesic. From a frequency spectrum standpoint, however, one important difference between the space and terrestrial uses of GPS is that it is being used in space with no interference protection. This is because there is no frequency allocation for the space-to-space use of GPS (i.e., from GPS satellite to user spacecraft) in the International Telecommunications Union (ITU) regulatory table of frequency allocations. If another space-based or groundbased radio system interferes with a spaceborne GPS user, the spaceborne user presently has no recourse other than to accept the interference. Consequently, for the past year and a half, the NASA Glenn Research Center at Lewis Field and other Government agencies have been working within ITU toward obtaining a GPS space-to-space allocation at the next World Radio Conference in the year 2000 (WRC 2000). Numerous interference studies have been conducted in support of a primary space-tospace allocation in the 1215- to 1260-MHz and 1559- to 1610-MHz RNSS bands. Most of these studies and analyses were performed by Glenn and submitted as U.S. input documents to the international Working Party 8D meetings in Geneva, Switzerland. In the structure of the ITU, Working Party 8D is responsible for frequency spectrum issues in the RNSS and the mobile satellite service (MSS). The full texts of the studies are available from the ITU web site under Working Party 8D contributions. Note that because spaceborne RNSS receivers operate in a receive-only mode with navigation signals already being broadcast toward the Earth, the addition of a space-tospace allocation will not result in interference with other systems. A space-based RNSS receiver, however, could experience interference from systems of other services, including intraservice interference from other RNSS systems. The interference scenarios examined in the studies can be inferred from the following frequency allocation charts. In these charts, services labeled in all capital letters (e.g., "ARNS") have primary status, whereas those labeled with sentence-style capitalization (e.g., "Amateur radio") have secondary status (i.e., a service with secondary status cannot claim interference protection from or cause harmful interference to a service with primary status). Charts showing the ITU frequency allocations in the 960 to 1350 MHZ range and the 1525-1660 MHZ range are discussed and presented.
Probabilistic resource allocation system with self-adaptive capability
A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.
Probabilistic resource allocation system with self-adaptive capability
A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.
Affine Generalized Inverse for Optimal Control Allocation
This research is a follow on to the "Optimal Control Prediction Method for Control Allocation" paper in which the Prediction Method iterative algorithm was introduced. Previously, the Prediction Method was shown to provide optimal control allocation solutions over the entire Attainable Moment Set for the Moore-Penrose and the generalized (weighted) inverse. As an extension to the Prediction Method, this paper introduces a family of Moore Penrose Affine Generalized Inverses, applicable for all moments, which compute control allocation solutions using a constant matrix and fixed null-space vector. The Moore-Penrose Affine Generalized Inverse is proven to yield equivalent solutions to those of the Prediction Method and therefore is guaranteed to yield Moore-Penrose optimal control allocation solutions. While the Prediction Method is applicable for any moment along an a priori specified moment direction, the Affine Generalized Inverse is shown to yield optimal control allocation solutions in a neighborhood of the given moment which is not restricted to a specified moment direction. Furthermore, the Affine Generalized Inverse is shown to provide the time derivative of optimal control allocation solutions and to facilitate maintaining solutions within control effector rate limitations. The Moore-Penrose Affine Generalized Inverse is broadened to encompass any arbitrary (weighted) Affine Generalized Inverse. Finally, a method of creating a moment lookup table is outlined to utilize the Affine Generalized Inverse as an offline control allocation solution for all moments in the Attainable Moment Set.