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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

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.

Acheson, Michael J.↗
NASA NTRSDate not supplied

A Comparison of Control Allocation Methods in the Presence of Parametric Model Uncertainty

When allocating redundant effectors to virtual control commands, linear (generalized inverse) allocators have historically been used on aircraft and spacecraft. While simple to implement, generalized inverses are unable to realize a significant portion of the attainable moments. To address this drawback, the control allocation problem can also be formulated as a linear programming or quadratic programming problem and solved using convex optimization based solvers. These approaches have been shown to access a larger set of attainable moments, however, little work has been done to understand the performance of convex optimization-based control allocation in the presence of parametric model uncertainty. This paper seeks to compare the performance of several control allocation approaches, including two forms of generalized inverse allocators, the pseudo inverse and minimum-variance, and the linear programming and quadratic programming approach in the presence of parametric model uncertainty. The performance of these four allocators were tested on an aircraft model in the presence of realistic parametric model uncertainty and the convex optimization approaches were shown to outperform the generalized inverses.

Luke J Miller↗
DOE OSTI2023

Climate change increases carbon allocation to leaves in early leaf green-up

Global greening, characterized by an increase in leaf area index (LAI), implies an increase in foliar carbon (C). Whether this increase in foliar C under climate change is due to higher photosynthesis or to higher allocation of C to leaves remains unknown. Here, we explored the trends in foliar C accumulation and allocation during leaf green-up from 2000 to 2017 using satellite-derived LAI and solar-induced chlorophyll fluorescence (SIF) across the Northern Hemisphere. The accumulation of foliar C accelerated in the early green-up period due to both increased photosynthesis and higher foliar C allocation driven by climate change. In the late stage of green-up, however, we detected decreasing trends in foliar C accumulation and foliar C allocation. Such stage-dependent trends in the accumulation and allocation of foliar C are not represented in current terrestrial biosphere models. Further, our results highlight that a better representation of C allocation should be incorporated into models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Lessons Learned for Transmission Cost Allocation in U.S. Regional Markets

Expanding electric transmission can facilitate generator interconnection and improve grid reliability. Assigning costs for new transmission infrastructure is highly contentious because these costs can have a direct impact on energy prices and ratepayer bills. In this report, we evaluate what factors influence successful transmission cost allocation agreements. Through a review of legal disputes, existing cost allocation practices, and regional case studies, we identify potential strategies to minimize cost allocation disputes for future projects. The report also highlights the processes by which regions can update their cost allocation methods. While we do not consider cost allocation methods currently under development for compliance with FERC Order 1920, the trends and lessons learned identified in this report can inform discussions on effective cost allocation methods to reduce barriers for transmission development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity

Abstract Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO 2 fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO 2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.

Trugman, Anna T.↗
NASA NTRS1986

Dynamic resource allocation in a hierarchical multiprocessor system: A preliminary study

An integrated system approach to dynamic resource allocation is proposed. Some of the problems in dynamic resource allocation and the relationship of these problems to system structures are examined. A general dynamic resource allocation scheme is presented. A hierarchial system architecture which dynamically maps between processor structure and programs at multiple levels of instantiations is described. Simulation experiments were conducted to study dynamic resource allocation on the proposed system. Preliminary evaluation based on simple dynamic resource allocation algorithms indicates that with the proposed system approach, the complexity of dynamic resource management could be significantly reduced while achieving reasonable effective dynamic resource allocation.

Ngai, Tin-Fook↗
DOE OSTI2019

Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Efficient water allocation is one of the most prominent issues in water resources management. In this research, a two-stage interval-parameter stochastic fuzzy programming with type 2 membership functions was used to allocate water resources optimally to different users under uncertainty. This method can handle uncertainties expressed as probability distributions, discrete intervals, and fuzzy sets. The model considers treated wastewater as an allocable water resource in a scenario, in addition to water that is extracted from wellheads, springs, and qanats. Moreover, the loss rate of water during distribution, surplus water in the reservoir in the previous and the next period, and treated wastewater parameters have been incorporated into the model. This model was applied to a case study of water resources allocation within a multi-user and multi-reservoir context in the Zarand region of Kerman, Iran. The results indicate that reasonable solutions have been generated, in the form of interval and fuzzy information under different scenarios that could help managers provide optimal water resources allocation plans. The results also demonstrate that establishing a wastewater treatment station increases the system net benefits, surplus water in wellheads for the next period, and system reliability (level of satisfying the fuzzy goal and constraints), and decreases encountering water shortages.

58 GEOSCIENCES↗
DOE OSTI2022

Resource Allocation for Single Carrier Massive MIMO Systems

Resource allocation in orthogonal frequency division multiplexing (OFDM) systems is performed through allocating blocks of subcarriers to each user. Even though OFDM is the primary waveform for 5G NR systems, research reports have noted that single carrier modulation (SCM) offers several advantages over OFDM in massive multiple input multiple output (MIMO) systems, making it a preferred candidate for some future applications such as massive machine type communications (mMTC). This paper presents a method for SCM resource allocation and the relevant information recovery algorithms at the receiver. Our emphasis is on cyclic prefixed SCM, where highly flexible and efficient frequency domain detection algorithms enable the operation of many simultaneous users in a massive MIMO uplink scenario. The proposed resource allocation method allows the number of users to exceed the number of antennas at the base station (BS). Each single carrier transmission is partitioned into L interleaved streams, and each user is allocated a number of such streams. One major benefit of SCM is that each data symbol is spread over the entire bandwidth. As such, the receiver performance is dictated by the average channel gain across the transmission band rather than the channel gain at a given frequency bin or a small group of frequencies. In the proposed setup, each stream may be thought of as a resource block in SCM, analogous to resource blocks in OFDM. Hence, in the context of this paper, the terms resource blocks and streams may be used interchangeably.

5G and Beyond Communications↗
DOE OSTI2023

Transactive Emergency Power Allocation

The devastating impacts of extreme weather events, many of which are climate-change related, are increasingly evident through the frequency and duration of outages on power grids, especially the distribution systems. One of the major modern-day concerns of utilities is dealing with such extreme supply outages where operators have used rolling blackouts as a contingency plan balance supply and demand while serving critical loads. Such events have significant repercussions social and economic costs. Such blackouts practices are a blunt instrument, depriving customers with low-capacity high-priority loads (i.e. refrigeration, water, telecommunication, etc.) that provide high marginal amenity. Our contribution presented in this work is a transactive emergency allocation mechanism that would provide some minimum level of service to all of the customers while enabling preference-based trading of this initial allocation. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on a prototypical distribution system experiencing 12-hour scarcity-based emergency event due to extreme operating conditions. Simulation results clearly demonstrate the capability of the proposed transactive emergency allocation mechanism in effectively utilizing the available energy and providing some level of service to all customers to operate their high-priority loads throughout the extreme scarcity event while being economically efficient in allowing trading of allocation based on customer preferences.

transactive energy, power system economics, emerge↗
DOE OSTI2024

Altering plant carbon allocation to stems has distinct effects on rhizosphere soil microbiome assembly, interactions, and potential functions in sorghum

Abstract Altering plant carbon allocation from leaves to stems is key to improve biomass for forage, fuel, and renewable chemicals. The sorghum dry stalk ( D ) locus controls a quantitative trait for sugar accumulation, with enhanced carbon allocation in the stems of juicy green ( dd ) sorghum but reduced carbon allocation in that of dry white ( DD ) sorghum. However, it remains unclear whether altering sorghum sugar accumulation in stem affects below‐ground microbiome. Here we investigated sorghum rhizosphere soil microbiome in near isogenic lines with different magnitude of carbon allocations and accumulation in the stems. Results showed that enhanced carbon accumulation in stems of juicy green sorghum results in stronger selection in rhizosphere microbiome assembly. The rhizosphere soil microbial communities selected in juicy green sorghum tended to be fast‐growing microbial taxa which possessed potential functions that would promote higher potential capacity to use chemically labile carbon sources and potentially result in higher potential decomposition rates. We found the rhizosphere microbes selected by juicy green sorghum form weaker interactions than dry white sorghum. This is the first comprehensive study revealing how the different magnitude of carbon allocations to stems regulates microbial community assembly, microbial interaction, and microbial functions. This study indicates that future plant modification for bioenergy crops should also consider the impacts on belowground microbial community without compromising the sustainability.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2016

Evolving Reliability and Maintainability Allocations for NASA Ground Systems

This paper describes the methodology that was developed to allocate reliability and maintainability requirements for the NASA Ground Systems Development and Operations (GSDO) program's subsystems. As systems progressed through their design life cycle and hardware data became available, it became necessary to reexamine the previously derived allocations. Allocating is an iterative process; as systems moved beyond their conceptual and preliminary design phases this provided an opportunity for the reliability engineering team to reevaluate allocations based on updated designs and maintainability characteristics of the components. Trade-offs in reliability and maintainability were essential to ensuring the integrity of the reliability and maintainability analysis. This paper will discuss the value of modifying reliability and maintainability allocations made for the GSDO subsystems as the program nears the end of its design phase.

allocations↗
NASA NTRSDate not supplied

Minimum-Variance Control Allocation Considering Parametric Model Uncertainty

The control allocation problem was investigated for linear dynamical systems with known parametric uncertainty. Minimizing a cost function that penalizes the variance of the error in achieving commanded forces and moments on the vehicle resulted in a special case of the weighted pseudo-inverse allocator. Rather than an engineer designing the weighting matrix, it is computed from the covariances of the control effectiveness parameters. This minimum-variance allocator balances the effectiveness of the control inputs against the corresponding levels of uncertainty. The approach was demonstrated using simulations of aircraft with realistic uncertainty levels operating in open-loop and closed-loop configurations. Results showed that when model uncertainty is known, significant, and unevenly distributed amongst the controls, the minimum-variance allocator more often achieves the intended forces and moments on the vehicle in comparison to other allocators, which can lead to increased performance, reliability, and safety during flight tests. The cost for this robustness is a diminished achievable moment space for the vehicle.

Control allocation↗
DOE OSTI2024

Belowground plant allocation regulates rice methane emissions from degraded peat soils

Carbon-rich peat soils have been drained and used extensively for agriculture throughout human history, leading to significant losses of their soil carbon. One solution for rewetting degraded peat is wet crop cultivation. Crops such as rice, which can grow in water-saturated conditions, could enable agricultural production to be maintained whilst reducing CO 2 and N 2 O emissions from peat. However, wet rice cultivation can release considerable methane (CH 4 ). Water table and soil management strategies may enhance rice yield and minimize CH 4 emissions, but they also influence plant biomass allocation strategies. It remains unclear how water and soil management influences rice allocation strategies and how changing plant allocation and associated traits, particularly belowground, influence CH 4 -related processes. We examined belowground biomass (BGB), aboveground biomass (AGB), belowground:aboveground ratio (BGB:ABG), and a range of root traits (root length, root diameter, root volume, root area, and specific root length) under different soil and water treatments; and evaluated plant trait linkages to CH 4 . Rice (Oryza sativa L.) was grown for six months in field mesocosms under high (saturated) or low water table treatments, and in either degraded peat soil or degraded peat covered with mineral soil. We found that BGB and BGB:AGB were lowest in water saturated conditions where mineral soil had been added to the peat, and highest in low-water table peat soils. Furthermore, CH 4 and BGB were positively related, with BGB explaining 60% of the variation in CH 4 but only under low water table conditions. Our results suggest that a mix of low water table and mineral soil addition could minimize belowground plant allocation in rice, which could further lower CH 4 likely because root-derived carbon is a key substrate for methanogenesis. Minimizing root allocation, in conjunction with water and soil management, could be explored as a strategy for lowering CH 4 emissions from wet rice cultivation in degraded peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Asynchronous nitrogen supply and demand produce nonlinear plant allocation responses to warming and elevated CO 2

Terrestrial ecosystem responses to climate change are mediated by complex plant–soil feedbacks that are poorly understood, but often driven by the balance of nutrient supply and demand. We actively increased aboveground plant-surface temperature, belowground soil temperature, and atmospheric CO 2 in a brackish marsh and found nonlinear and nonadditive feedbacks in plant responses. Changes in root-to-shoot allocation by sedges were nonlinear, with peak belowground allocation occurring at +1.7 °C in both years. Above 1.7 °C, allocation to root versus shoot production decreased with increasing warming such that there were no differences in root biomass between ambient and +5.1 °C plots in either year. Elevated CO 2 altered this response when crossed with +5.1 °C, increasing root-to-shoot allocation due to increased plant nitrogen demand and, consequently, root production. We suggest these nonlinear responses to warming are caused by asynchrony between the thresholds that trigger increased plant nitrogen (N) demand versus increased N mineralization rates. The resulting shifts in biomass allocation between roots and shoots have important consequences for forecasting terrestrial ecosystem responses to climate change and understanding global trends.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Location-allocation and public transit: An update on UCL student teacher placements

Location-allocation is a key application of GIS, with many varied applications. We present further development of a location-allocation tool for a real-world case study with UCL using public transport. The location of UCL in Greater London (UK) means that the inclusion of public transport is vital for this case study. The location-allocation is implemented as a capacitated p-median location-allocation model, using spopt, a library in the Python Spatial Analysis Library (PySAL) ecosystem. The initial results of this work are promising, with calculation times reduced by up to 60%, and the majority of students allocated shorter journey times, with further testing ongoing.

Bearman, Nick [University College London (UCL), UK↗
NASA NTRS1987

Task allocation in a distributed computing system

A conceptual framework is examined for task allocation in distributed systems. Application and computing system parameters critical to task allocation decision processes are discussed. Task allocation techniques are addressed which focus on achieving a balance in the load distribution among the system's processors. Equalization of computing load among the processing elements is the goal. Examples of system performance are presented for specific applications. Both static and dynamic allocation of tasks are considered and system performance is evaluated using different task allocation methodologies.

Seward, Walter D.↗
NASA NTRS1987

Dynamic task allocation for a man-machine symbiotic system

This report presents a methodological approach to the dynamic allocation of tasks in a man-machine symbiotic system in the context of dexterous manipulation and teleoperation. This report addresses a symbiotic system containing two symbiotic partners which work toward controlling a single manipulator arm for the execution of a series of sequential manipulation tasks. It is proposed that an automated task allocator use knowledge about the constraints/criteria of the problem, the available resources, the tasks to be performed, and the environment to dynamically allocate task recommendations for the man and the machine. The presentation of the methodology includes discussions concerning the interaction of the knowledge areas, the flow of control, the necessary communication links, and the replanning of the task allocation. Examples of task allocation are presented to illustrate the results of this methodolgy.

Parker, L. E.↗
NASA NTRS1992

Frequency allocations for a new satellite service - Digital audio broadcasting

The allocation in the range 500-3000 MHz for digital audio broadcasting (DAB) is described in terms of key issues such as the transmission-system architectures. Attention is given to the optimal amount of spectrum for allocation and the technological considerations relevant to downlink bands for satellite and terrestrial transmissions. Proposals for DAB allocations are compared, and reference is made to factors impinging on the provision of ground/satellite feeder links. The allocation proposals describe the implementation of 50-60-MHz bandwidths for broadcasting in the ranges near 800 MHz, below 1525 MHz, near 2350 MHz, and near 2600 MHz. Three specific proposals are examined in terms of characteristics such as service areas, coverage/beam, channels/satellite beam, and FCC license status. Several existing problems are identified including existing services crowded with systems, the need for new bands in the 1000-3000-MHz range, and variations in the nature and intensity of implementations of existing allocations that vary from country to country.

Reinhart, Edward E.↗