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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Using Financial Contracts to Facilitate Informal Leases Within a Western United States Water Market Based on Prior Appropriation

The ability to reallocate water to higher-value uses during drought is an increasingly important “soft-path” tool for managing water resources in an uncertain future. In most of the Western United States, state-level water market institutions that enable reallocation also impose substantial transaction costs on market participants related to regulatory approval and litigation. These transaction costs can be prohibitive for many participants in terms of both costs and lengthy approval periods, limiting transfers and reducing allocation efficiency, particularly during drought crises periods. This manuscript describes a mechanism to reduce transaction costs by adapting an existing form of informal leases to facilitate quicker and less expensive transfers among market participants. Instead of navigating the formal approval process to lease a water right, informal leases are financial contracts for conservation that enable more junior holders of existing rights to divert water during drought, thereby allowing the formal transfer approval process to be bypassed. The informal leasing approach is tested in the Upper Colorado River Basin, where drought and institutional barriers to transfers lead to frequent shortages for urban rights holders along Colorado's Front Range. Informal leases are facilitated via option contracts that include adaptive triggers and that define volumes of additional, compensatory, releases designed to mitigate impacts to instream flows and third parties. Results suggest that more rapid reallocation of water via informal leases could have resulted in up to $222 million in additional benefits for urban rights holders during the historical period 1950–2013.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1977

Integrating Shuttle payloads

The paper discusses the relationships that will develop among experimenters, mission managers, and operators when satellites, using equipment transported by the Space Shuttle, are constructed in space. Since these satellites do not have to be lifted and guided from the earth's surface, and since they are more accessible for maintenance, future hardware will be built to less demanding standards, which will permit a greater variety of research and more of it in terms of costs. Present and future interrelationships among management authority, interface documentation, accommodations allocation, experiment autonomy, and assembly and checkout are analyzed, so that less costly payload-integration procedures can be developed.

Jean, O. C.↗
NASA NTRS1989

Ka-band study: 1988

The Ka-band study team was chartered in late 1987 to bring together all the planning elements for establishing 32 GHz (Ka-band) as the primary downlink frequency for deep-space operation, and to provide a stable baseline from which to pursue that development. This article summarizes the results of that study at its conclusion in mid-1988, and corresponds to material presented to NASA's Office of Space Operations on July 14, 1988. For a variety of reasons, Ka-band is the right next major step in deep-space communications. It offers improved radio metric accuracy through reduced plasma sensitivity and increased bandwidth. Because of these improvements, it offers the opportunity to reduce costs in the flight radio system or in the DSN by allocating part of the overall benefits of Ka-band to this cost reduction. A mission scenario is being planned that can drive at least two and possibly all three of the DSN subnets to provide a Ka-band downlink capability by the turn of the century. The implementation scenario devised by the study team is believed to be feasible within reasonable resource expectations, and capable of providing the needed upgrade as a natural follow-on to the technology development which is already underway.

Layland, J. W.↗
DOE OSTI2026

Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Artificial-intelligence-driven shot reduction in quantum measurement

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware requires repeated measurements (shots), incurring significant costs as accuracy increases. Optimizing shot allocation is thus critical for improving the efficiency of VQE. Current strategies rely heavily on hand-crafted heuristics requiring extensive expert knowledge. This paper proposes a reinforcement learning (RL)-based approach that automatically learns shot assignment policies to minimize total measurement shots while achieving convergence to the minimum of the energy expectation in VQE. The RL agent assigns measurement shots across VQE optimization iterations based on the progress of the optimization. This approach reduces VQE's dependence on static heuristics and human expertise. When the RL-enabled VQE is applied to a small molecule, a shot reduction policy is learned. The policy demonstrates transferability across systems and compatibility with other wavefunction Ansätze. In addition to these specific findings, this work highlights the potential of RL for automatically discovering efficient and scalable quantum optimization strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Assignment Of Finite Elements To Parallel Processors

Elements assigned approximately optimally to subdomains. Mapping algorithm based on simulated-annealing concept used to minimize approximate time required to perform finite-element computation on hypercube computer or other network of parallel data processors. Mapping algorithm needed when shape of domain complicated or otherwise not obvious what allocation of elements to subdomains minimizes cost of computation.

Salama, Moktar A.↗
NASA NTRS2016

Options for Staging Orbits in Cis-Lunar Space

NASA has been studying options to conduct missions beyond Low Earth Orbit, but within the Earth‐Moon system, in preparation for deep space exploration including human missions to Mars. Referred to as the Proving Ground, this arena of exploration activities will enable the development of human spaceflight systems and operations to satisfy future exploration objectives beyond the cis‐lunar environment. One option being considered includes the deployment of a habitable element or elements, which could be used as a central location for aggregation of supplies and resources for human missions in cis‐lunar space and beyond. Characterizing candidate orbit locations for this asset and the impacts on system design and mission operations is important in the overall assessment of the options being considered. The orbits described in this paper were initially selected by taking advantage of previous studies conducted by NASA and the work of other authors. In this paper orbits are assessed for their relative attractiveness based on various factors. A set of constraints related to the capability of the combined Orion and SLS system to deliver humans and cargo to and from the orbit are evaluated. Deployed assets intended to spend multiple years in the Proving Ground would ideally require minimal station keeping costs to reduce the mass budget allocated to this function. Additional mission design drivers include eclipse frequency, potential for uninterrupted communication with deployed assets, thermal, attitude control, communications, and other operational implications. Also the ability to support potential lunar surface activities and excursion missions beyond Earth‐Moon space is considered. The results of the characterization and evaluation of the selected orbits indicate a Near Rectilinear Orbit (NRO) is an attractive candidate as an aggregation point or staging location for operations. In this paper, the NRO is further described in terms which balance a number of key attributes that favor a variety of mission classes to meet multiple, sometimes competing, constraints.

Martinez, Roland↗
NASA NTRS2015

Options for Staging Orbits in Cis-Lunar Space

NASA has been studying options to conduct missions beyond Low Earth Orbit, but within the Earth-Moon system, in preparation for deep space exploration including human missions to Mars. Referred to as the Proving Ground, this arena of exploration activities will enable the development of human spaceflight systems and operations to satisfy future exploration objectives beyond the cis-lunar environment. One option being considered includes the deployment of a habitable element or elements, which could be used as a central location for aggregation of supplies and resources for human missions in cis-lunar space and beyond. Characterizing candidate orbit locations for this asset and the impacts on system design and mission operations is important in the overall assessment of the options being considered. The orbits described in this paper were initially selected by taking advantage of previous studies conducted by NASA and the work of other authors. In this paper orbits are assessed for their relative attractiveness based on various factors. First, a set of constraints related to the capability of the combined Orion and SLS system to deliver humans and cargo to and from the orbit are evaluated. Second, the ability to support potential lunar surface activities is considered. Finally, deployed assets intended to spend multiple years in the Proving Ground would ideally require minimal station keeping costs to reduce the mass budget allocated to this function. Additional mission design drivers include potential for uninterrupted communication with deployed assets, thermal, communications, and other operational implications. The results of the characterization and evaluation of the selected orbits indicate a Near Rectilinear Orbit (NRO) is an attractive candidate as an aggregation point or staging location for operations. In this paper, the NRO is further described in terms which balance a number of key attributes that favor a variety of mission classes to meet multiple, sometimes competing, constraints.

Whitley, Ryan↗
NASA NTRS2010

LCROSS - Lunar Impactor: Pioneering Risk-Tolerant Exploration in Search for Water on the Moon

The Lunar CRater Observation and Sensing Satellite (LCROSS) was launched with the Lunar Reconnaissance Orbiter (LRO) on June 18, 2009 to determine the presence of water-ice in a permanently shadowed crater on the south pole of the Moon. However, an equally important purpose was to pioneer low-cost, quick-turnaround NASA missions that could accept a higher-than-normal-level of technical risk. When the LCROSS mission proposal was competitively selected by the NASA Exploration Systems Mission Directorate to design, build, and launch a spacecraft in 31 months with a $79M cost-capped budget and a fixed mass allocation, NASA Ames Research Center and its industry partner, Northrop-Grumman, needed a game-changing approach to be successful. That approach was a ground-breaking combination of having a risk-tolerant NASA Class D mission status and finding the right balance point between the inflexible elements of cost and schedule and the newly-flexible element of technical capability.

Andrews, Daniel R.↗
DOE OSTI2026

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗
NASA NTRS1987

Allocating Spare Parts In Complicated Systems

Assortments analyzed for cost effectiveness and effects on system functionality. Eisenberger-Maiocco algorithm (EMA) is efficient Markov algorithm to aid in provision of spare parts. Two calculations performed: forecasting availability of system with given pool of spare parts and determining most cost-effective assortment of spares. EMA written in interpreter PC-BASIC.

Eisenberger, I.↗
NASA NTRS1983

Estimating regression coefficients from clustered samples: Sampling errors and optimum sample allocation

A number of surveys were conducted to study the relationship between the level of aircraft or traffic noise exposure experienced by people living in a particular area and their annoyance with it. These surveys generally employ a clustered sample design which affects the precision of the survey estimates. Regression analysis of annoyance on noise measures and other variables is often an important component of the survey analysis. Formulae are presented for estimating the standard errors of regression coefficients and ratio of regression coefficients that are applicable with a two- or three-stage clustered sample design. Using a simple cost function, they also determine the optimum allocation of the sample across the stages of the sample design for the estimation of a regression coefficient.

Kalton, G.↗
NASA NTRS1981

Study of Thermal Control Systems for orbiting power systems

Thermal control system designs were evaluated for the 25 kW power system. Factors considered include long operating life, high reliability, and meteoroid hazards to the space radiator. Based on a cost advantage, the bumpered pumped fluid radiator is recommended for the initial 25 kW power system and intermediate versions up to 50 kW. For advanced power systems with heat rejection rates above 50 kW the lower weight of the advanced heat pipe radiator offsets the higher cost and this design is recommended. The power system payloads heat rejection allocations studies show that a centralized heat rejection system is the most weight and cost effective approach. The thermal interface between the power system and the payloads was addressed and a concept for a contact heat exchanger that eliminates fluid transfer between the power system and the payloads was developed. Finally, a preliminary design of the thermal control system, with emphasis on the radiator and radiator deployment mechanism, is presented.

Howell, H. R.↗
NASA NTRS1976

Cost benefit analysis of space communications technology: Volume 1: Executive summary

The questions of (1) whether or not NASA should support the further development of space communications technology, and, if so, (2) which technology's support should be given the highest priority are addressed. Insofar as the issues deal principally with resource allocation, an economics perspective is adopted. The resultant cost benefit methodology utilizes the net present value concept in three distinct analysis stages to evaluate and rank those technologies which pass a qualification test based upon probable (private sector) market failure. User-preference and technology state-of-the-art surveys were conducted (in 1975) to form a data base for the technology evaluation. The program encompassed near-future technologies in space communications earth stations and satellites, including the noncommunication subsystems of the satellite (station keeping, electrical power system, etc.). Results of the research program include confirmation of the applicability of the methodology as well as a list of space communications technologies ranked according to the estimated net present value of their support (development) by NASA.

Holland, L. D.↗
DOE OSTI2020

Land Use in Computable General Equilibrium Models

Constant Elasticity of Transformation (CET) functions are widely used to allocate land across uses in Computable General Equilibrium (CGE) models. These models fail to maintain area of land in balance. Several ways have been used or offered to fix this problem. This paper first examines the extent to which the CET approach may generate imbalances in area of land and identifies determinants of such imbalances. It then evaluates the merits, properties, and welfare impacts of the available approaches that restore area of land in balance. We show that heterogeneity in land prices (land rents) is the main source of imbalance in area of land, not the curvature of the CET function. Furthermore, we show that the available approaches that restore area of land in balance either introduce ad hoc adjustments in land allocation or undermine the conventional welfare assessments of the CET results and ignore the opportunity costs of land transformation. The CGE models which applied stochastic productivity distribution functions to allocate land among uses maintain area of land in balance, but they suffer from important limitations and ignore costs of land transformation.

Taheripour, Farzad↗
DOE OSTI2025

Game theoretic modeling and optimization of competition and collaboration in dual channel electronic waste supply chains

The rapid growth of electronic waste (e-waste) presents critical challenges for sustainable resource recovery and environmental protection. This study develops a dual-channel closed-loop supply chain (CLSC) model formulated as a hierarchical Stackelberg game, that integrates dynamic pricing and cost-sharing mechanisms to optimize both economic and environmental outcomes. The model explicitly captures strategic interactions between manufacturer-led and third-party recycling channels, accounting for consumer behavior, regulatory incentives, and market competition. Numerical simulations conducted (implemented over a four-iteration horizon using a commercial optimization solver) show that, relative to the baseline equilibrium, manufacturer profit increases from 11.6 thousand USD to 37.9 thousand USD (+226.8%), total recycled volume rises from 7,848 to 7,942 units (+1.2%), and collector profit nearly doubles under cost-sharing, enabling more equitable profit distribution. Furthermore, scenario-based simulations across Sub-Saharan Africa, high-income economies, and emerging Asian industrial countries reveal that infrastructure quality, policy intensity, and labor costs critically shape recycling efficiency and profit allocation. These findings demonstrate that subsidies alone are insufficient to ensure system efficiency. Instead, coordinated strategies that integrate internal incentive alignment with context-sensitive policy support are required. Overall, this study offers a robust framework for designing resilient, efficient, and regionally adaptable e-waste management systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Reinforcement Learning for Volt- Var Control: A Novel Two-stage Progressive Training Strategy

This paper develops a reinforcement learning (RL) approach to solve a cooperative, multi-agent Volt-Var Control (VVC) problem for high solar penetration distribution systems. The ingenuity of our RL method lies in a novel two-stage progressive training strategy that can effectively improve training speed and convergence of the machine learning algorithm. In Stage 1 (individual training), while holding all the other agents inactive, we separately train each agent to obtain its own optimal VVC actions in the action space: fconsume, generate, do-nothingg. In Stage 2 (cooperative training), all agents are trained again coordinatively to share VVC responsibility. Rewards and costs in our RL scheme include (i) a system-level reward (for taking an action), (ii) an agent-level reward (for doing-nothing), and (iii) an agent-level action cost function. This new framework allows rewards to be dynamically allocated to each agent based on their contribution while accounting for the trade-off between control effectiveness and action cost. The proposed methodology is tested and validated in a modified IEEE 123-bus system using realistic PV and load profiles. Simulation results confirm that the proposed approach is robust and computationally efficient; and it achieves desirable volt-var control performance under a wide range of operation conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗