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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Guaranteeing synchronous message deadlines with the timed token medium access control protocol

We study the problem of guaranteeing synchronous message deadlines in token ring networks where the timed token medium access control protocol is employed. Synchronous capacity, defined as the maximum time for which a node can transmit its synchronous messages every time it receives the token, is a key parameter in the control of synchronous message transmission. To ensure the transmission of synchronous messages before their deadlines, synchronous capacities must be properly allocated to individual nodes. We address the issue of appropriate allocation of the synchronous capacities. Several synchronous capacity allocation schemes are analyzed in terms of their ability to satisfy deadline constraints of synchronous messages. We show that an inappropriate allocation of the synchronous capacities could cause message deadlines to be missed even if the synchronous traffic is extremely low. We propose a scheme called the normalized proportional allocation scheme which can guarantee the synchronous message deadlines for synchronous traffic of up to 33 percent of available utilization. To date, no other synchronous capacity allocation scheme has been reported to achieve such substantial performance. Another major contribution of this paper is an extension to the previous work on the bounded token rotation time. We prove that the time elapsed between any consecutive visits to a particular node is bounded by upsilon TTRT, where TTRT is the target token rotation time set up at system initialization time. The previous result by Johnson and Sevcik is a special case where upsilon = 2. We use this result in the analysis of various synchronous allocation schemes. It can also be applied in other similar studies.

Agrawal, Gopal↗
NASA NTRS2000

Dependence of Photosynthetic Capacity, Photosynthetic Pigment Allocation, and Carbon Storage on Nitrogen Levels in Foliage of Aspen Stands

The role of foliar nitrogen (N) in the seasonal dynamics and vertical canopy distribution of photosynthetic pigments, photosynthetic capacity, and carbon (C) storage was investigated in boreal broadleaved species. The study was conducted at two different aged stands (60 y and 15 y) in 1994 and 1996 in Saskatchewan, Canada as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). Foliage in upper and lower strata was examined for aspen (Populus tremuloides Michx.) and its associated hazelnut shrub (Corylus americana Walt.). We determined that C accumulation, expressed as dry mass per unit leaf area (mg C cm (exp -2)), was linearly dependent on N content (approximately 0.3- 3.5 mg N cm (exp -2))(r (exp 2) = 0.93, n=383, P less than 0.001) when eleven foliage groups were defined according to species, site, and developmental stage. C assembly was greatest in the upper aspen strata of both sites (seasonal average, 40.1 plus or minus 0.6 mg C cm (exp -2)), intermediate in the lower aspen strata (32.7 plus or minus 0.6), and considerably lower, and similar, in the hazelnut shrub layers (23.7 plus or minus 0.6) and in expanding aspen leaves (23.8 plus or minus 0.5); the lowest C assembly per unit N occurred in the two youngest, emerging leaf groups (17.1 plus or minus 0.6). Other relationships among physiological and biochemical variables were typically non-linear and were confounded by inclusion of the three groups of young (i.e., emerging or expanding) leaves, unless these were separately identified. Net C uptake, measured as photosynthetic capacity (A (sub max), micromole CO2 m (exp -2) s (exp -1)), was greater in aspen throughout the season, and optimal in mid-summer at a C:N ratio of approximately 18 (approximately 2.3 %N). When young leaves were excluded and logarithms of both variables were used, A (sub max) was approximately linearly dependent on N (mg N cm (exp-2) (r (exp 2) = 0.85, n= 193, P less than 0.001), attributed to incorporation of N into photosynthetic complexes and enzymes. In mature leaves, differences in pigment content vs. N among canopy strata were accentuated when N was expressed per unit leaf area (Mg cm (exp -2)) . However, the simplest log-linear relationship between a pigment variable and N was obtained for a ratio describing the relative allocation of photosynthetic pigment to Chl a (Chl a/[Chl b + carotenoids], microgram cm (exp -2)/ microgram cm-2) vs. %N (r (exp 2) = 0.90, n=343, P less than 0.001). Attainment of comparable A (sub max) Chl a content and relative Chl a allocation per unit N (mg cm (exp -2)) was achieved at different foliar N levels per canopy group: the lowest N requirement was for hazelnut leaves in the lowest, shaded stratum at the older, closed canopy site; the highest N requirement was in aspen leaves of the upper-most stratum at the younger, more open canopy site. These results highlight the differences in physiological responses between young and fully expanded leaves and show that sustaining those foliar constituents and processes important to C balance may require higher foliar N levels in leaves of establishing vs. mature aspen stands. There may be implications for remote-sensing assessments made for carbon balance in springtime, or over a landscape mosaic comprised of different aged stands.

Middleton, Elizabeth M.↗
DOE OSTI2026

Optimizing Transportation Networks for E-Waste Reverse Logistics: A Multi-Modal Cost Allocation and Pricing Strategy

The exponential growth of electronic waste (e-waste) poses critical challenges for sustainable reverse logistics and transportation network optimization. This study develops a dual-channel transportation framework for e-waste logistics that integrates dynamic freight pricing, cost allocation mechanisms, and game-theoretic coordination. The model captures interactions between centralized hubs and distributed processing networks, accounting for freight rate elasticity, volume allocation, and capacity constraints. Using Stackelberg game theory and cost-sharing strategies, the framework optimizes transportation efficiency and profit distribution across logistics channels. Numerical simulations show that the dual-channel structure increases centralized hub profit by 226.8% compared to baseline single-channel operations, while boosting total transported volume by 1.2% and nearly doubling freight collector profit under cost-sharing. Scenario analyses across regional infrastructures reveal that network density, policy incentives, and logistics costs shape routing efficiency and profit allocation. These findings suggest that coordinated strategies combining dynamic pricing, targeted infrastructure investment, and strategic cost allocation are needed to design efficient, resilient, and regionally adaptable e-waste transportation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗
DOE OSTI2024

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

A model for analysis of TDA budget allocation

There is an ever-increasing need to achieve greater efficiency in the operation of the Deep Space Network (DSN), i.e., increased productivity at reduced cost. One of the tools used in the course of a planning workshop on this subject was a methodology for budget allocation applicable to long-range planning. This article presents a model for analysis of the TDA budget allocation. For the 1994 through 1999 period, the percentage of the total TDA budget allocated to capacity and capability is being cut in half, whereas the percentage spent on efficiency of delivery will be increasing.

Remer, D. S.↗
NASA NTRS1992

Optimal routing and buffer allocation for a class of finite capacity queueing systems

The problem of routing jobs to K parallel queues with identical exponential servers and unequal finite buffer capacities is considered. Routing decisions are taken by a controller which has buffering space available to it and may delay routing of a customer to a queue. Using ideas from weak majorization, it is shown that the shorter nonfull queue delayed (SNQD) policy minimizes both the total number of customers in the system at any time and the number of customers that are rejected by that time. The SNQD policy always delays routing decisions as long as all servers are busy. Only when all the buffers at the controller are occupied is a customer routed to the queue with the shortest queue length that is not at capacity. Moreover, it is shown that, if a fixed number of buffers is to be distributed among the K queues, then the optimal allocation scheme is the one in which the difference between the maximum and minimum queue capacities is minimized, i.e., becomes either 0 or 1.

Towsley, Don↗
NASA NTRS1987

Concurrent communication among multi-transceiver stations over shared media

In order to increase a local-area network's throughput beyond a single bus data rate without using dedicated switching nodes, multiple buses and multitransceiver stations are required. The design space of single-hop interconnections is explored among such stations. Interconnections are presented whose throughput can grow quadratically with the number of transmitters and receivers per station. These are referred to as selective broadcast interconnections (SBIs). The performance of various SBIs are studied. A spread-spectrum channel can accommodate several current successful transmission, and a single-transceiver node can thus utilize only a small fraction of the channel capacity. In order to allocate the appropriate fraction of capacity to a busy node, it is proposed to equip it with several transmitters and receivers, thereby turning it into a supernode. Several architectures and operation policies for supernodes are suggested and compared. It is shown that a supernode can significantly outperform a collection of independent conventional nodes with the same total numbers of transmitters and receivers. Packet-radio networks with half-duplex nodes, as well as networks with full-duplex nodes, are considered.

Birk, Yitzhak↗
NASA NTRS2006

Steps Toward Optimal Competitive Scheduling

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum of users preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, se@sh preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource. This problem arises in many institutional settings where, e.g., different departments, agencies, or personal, compete for a single resource. We are particularly motivated by the problem of scheduling NASA's Deep Space Satellite Network (DSN) among different users within NASA. Access to DSN is needed for transmitting data from various space missions to Earth. Each mission has different needs for DSN time, depending on satellite and planetary orbits. Typically, the DSN is over-subscribed, in that not all missions will be allocated as much time as they want. This leads to various inefficiencies - missions spend much time and resource lobbying for their time, often exaggerating their needs. NASA, on the other hand, would like to make optimal use of this resource, ensuring that the good for NASA is maximized. This raises the thorny problem of how to measure the utility to NASA of each allocation. In the typical case, it is difficult for the central agency, NASA in our case, to assess the value of each interval to each user - this is really only known to the users who understand their needs. Thus, our problem is more precisely formulated as follows: find an allocation schedule for the resource that maximizes the sum ofsers preferences, when the preference values are private information of the users. We bypass this problem by making the assumptions that one can assign money to customers. This assumption is reasonable; a committee is usually in charge of deciding the priority of each mission competing for access to the DSN within a time period while scheduling. Instead, we can assume that the committee assigns a budget to each mission.

Frank, Jeremy↗
DOE OSTI2023

Distribution Network Capacity Market Design: Marginal Distribution Capacity Pricing Mechanism for Efficient Investment and Cost Allocation

As electricity markets begin to shift from reliance on large, centralized power plants and towards distributed energy resources (DERs), there is a growing acknowledgement that more efficient planning, operations, and oversight is needed in the distribution system. This paper addresses one step in that direction by proposing an auction mechanism that uses a detailed distribution system planning model that allocates permits to end-used customers who request capacity to install new devices at their location and network upgrade contracts to utilities or 3rd-party companies who offer to upgrade system components. The resulting plan maximizes market surplus, that is, maximizes the total benefit to consumers minus the cost of network upgrades. We apply a marginal pricing scheme to the auction’s results such that the cost of each permits or contracts is differentiated by time and location, based on the Lagrangian multipliers of binding network constraints. These prices are shown to be no greater than the bid price of any awarded contract and no less than the offered cost of any awarded upgrade contract. Furthermore, the nonlinearity of power flows in the planning model result in an additional surplus that would be collected by the entity that hosts the auction, which could then be refunded to market participants or used to cover overhead costs of running the market. We provide four example auction results in a simple three-node distribution feeder to demonstrate the properties of the design. Results suggest that larger or more realistic case studies could be a promising next step.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2000

Consequences of Slot Transactions on Airport Congestion and Environmental Protection

Recent trends in the liberalization of market access by many commercial airlines have opened the skies to virtually unlimited flights between many countries. However, this liberalization is stultified by the lack of airport capacity to accommodate the many flights that are generated by demand for capacity. Accordingly, the allocation of slots for open skies airlines remain dependent on the expansion and effective management of airport capacity. This article examines the ramifications of slot allocation on traffic peaking at airports and environmental concerns, which may emerge with this activity.

Abeyratne, Ruwantissa I.R.↗
DOE OSTI2021

Adaptive Protection of Scientific Backbone Networks Using Machine Learning

In this article, we propose a new protection scheme for backbone networks to guarantee high service availability. The presented scheme does not require any reconfiguration immediately after the failure (i.e., it is proactive). At the same time, it does not require any reserved backup network resources either. To achieve these seemingly contradictory goals, we utilize the recent advancements in Machine Learning (ML) to implement a network intelligence that periodically re-allocates the unused capacity as protection bandwidth to meet the service availability requirements of each connection. Our goal is achieved by two components (1) predicting the traffic for the next period on each link, and (2) intelligently selecting the best fit dedicated protection scheme for the next period depending on the estimated unused (spare) bandwidth and the previous service availability violations. Note that re-allocating protection bandwidth affects neither the operational connections nor the current best practice of operators to over-provision network bandwidth to support elephant flows. Finally, we provide a case study on the real traffic from Energy Sciences Network (ESnet), a high-speed, international scientific backbone network. The key benefit of our framework is that adaptively utilizing the over-provisioned bandwidth for spare capacity is sufficient to improve the availability from three-nines to five-nines (in ESnet for the 30 examined connections). The drawback is negligible bandwidth limitations; the user perceives a minor and very temporal bandwidth limitation in less than 0.1% of the time.

42 ENGINEERING↗
NASA NTRS2005

Playing Games with Optimal Competitive Scheduling

This paper is concerned with the problem of allocating a unit capacity resource to multiple users within a pre-defined time period. The resource is indivisible, so that at most one user can use it at each time instance. However, different users may use it at different times. The users have independent, selfish preferences for when and for how long they are allocated this resource. Thus, they value different resource access durations differently, and they value different time slots differently. We seek an optimal allocation schedule for this resource.

Frank, Jeremy↗
DOE OSTI2024

Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)

Plant and microbial nitrogen (N) dynamics and N availability regulate the photosynthetic capacity and capture, allocation, and turnover of carbon (C) in terrestrial ecosystems. Studies have shown that a wide divergence in representations of N dynamics in land surface models leads to large uncertainties in the biogeochemical cycle of terrestrial ecosystems and then in climate simulations as well as the projections of future trajectories. In this study, a plant C–N interface coupling framework is developed and implemented in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0). The main concept and structure of this plant C–N framework and its coupling strategy are presented in this study. This framework takes more plant N-related processes into account. The dynamic ratio (CNR) for each plant functional type (PFT) is introduced to consider plant resistance and adaptation to N availability to better evaluate the plant response to N limitation. Furthermore, when available N is less than plant N demand, plant growth is restricted by a lower maximum carboxylation capacity of RuBisCO (V c,max ), reducing gross primary productivity (GPP). In addition, a module for plant respiration rates is introduced by adjusting the respiration with different rates for different plant components at the same N concentration. Since insufficient N can potentially give rise to lags in plant phenology, the phenological scheme is also adjusted in response to N availability. All these considerations ensure a more comprehensive incorporation of N regulations to plant growth and C cycling. This new approach has been tested systematically to assess the effects of this coupling framework and N limitation on the terrestrial carbon cycle. Long-term measurements from flux tower sites with different PFTs and global satellite-derived products are employed as references to assess these effects. The results show a general improvement with the new plant C–N coupling framework, with more consistent emergent properties, such as GPP and leaf area index (LAI), compared to the observations. The main improvements occur in tropical Africa and boreal regions, accompanied by a decrease in the bias in global GPP and LAI by 16.3 % and 27.1 %, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Unlocking the Path to Decarbonized Building Thermal Systems: Strategies for Designers and Contractors: Preprint

The design and construction community plays a pivotal role in facilitating the transition to decarbonized thermal systems that maintain human comfort while reducing building emissions. Through the U.S. Department of Energy Better Buildings initiative's Design and Construction Allies, a cohort of leading architecture, engineering, and construction firms have identified top ranked barriers that designers and contractors face when implementing solutions for building owners. These barriers to decarbonizing thermal - especially heating - systems include equipment availability; electrical capacity constraints; space allocations; complex system configurations; and lack of experience in designing, installing, and maintaining heat pumps. These impediments significantly amplify the risk and financial burden associated with the adoption of decarbonized solutions. The barriers also decrease the likelihood that designers, contractors, and owners will adopt decarbonization strategies without clear plans and guidance on how to implement these solutions, mitigate risk, and overcome the identified barriers. The National Renewable Energy Laboratory, the Design and Construction Allies, and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers have developed "how to" thermal decarbonization guidance based on best practices. The subjects covered range from the role of energy efficiency in facilitating decarbonized heating solutions to strategies for decarbonizing new and existing heating, ventilating, and air-conditioning systems. The focus is on overcoming barriers so that energy-efficient, electrified buildings - both new and retrofit - become the industry standard. This paper outlines 1) the method used to collect and organize this guidance, 2) industry barriers to decarbonization, and 3) decarbonization techniques that have broad market applicability.

building heating↗
NASA NTRSDate not supplied

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗