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Results for “distributed optimization”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Estimating energy consumption and GHG emissions in the U.S. food supply chain for net-zero

This work provides a database of the U.S. food system’s energy consumption and GHG emissions at the national and state levels by food supply chain (FSC) stage, fuel type, and food commodity. We estimate that the U.S. FSC consumed a total 4660 TBTU (4900 PJ) of site energy, 7130 TBTU (7500 PJ) of primary energy, and generated 970 MMT of GHG emissions in 2016. Among all the stages, on-farm production is the largest energy consumer (31% primary energy) and GHG emissions contributor (70%), largely due to raising animals. Optimizing distribution can reduce the stage’s energy consumption and GHG emissions and increase products’ shelf-life. Reducing food loss and waste is another good option, as it decreases the amount of food necessary to grow, thus impacting the overall FSC. The database can help stakeholders identify stage- and region-specific strategies and measures to curtail the environmental footprint of the U.S. food system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Networked Microgrids for Improved Resilient Operation: A Case Study in Adjuntas Puerto Rico

This paper presents a case study of a network microgrid orchestrator designed to allow coordinated operation of microgrids. Through Control Hardware in the Loop (CHIL), the proposed microgrid orchestrator was validated using, as case study two community-owned microgrids in Adjuntas, Puerto Rico. These two microgrids in Adjuntas were designed to provide affordable and reliable access to electricity to 14 businesses located in the town square. In its current design, these two microgrids operate independently from each other. This paper studies how networking them would increase their resiliency metrics while operating as an island. A distributed optimization is implemented in the microgrid orchestrator due to its superior scalability compared to centralized approach as well as to maintain data privacy. Two operational modes are considered in this study to showcase the advantages of networking microgrids: a) normal island, and b) degraded island. CHIL simulations are performed to validate the proposed microgrid orchestrator. CHIL results show meaningful resiliency improvements obtained by networking microgrids during contingencies such as loss of PV generation.

Ferrari Maglia, Max↗
DOE OSTI2020

A Robust Hierarchical Dispatch Scheme for Active Distribution Networks Considering Home Thermal Flexibility

Distribution networks are changing from passive absorbers of electric energy to active distribution networks (ADNs) capable of operating and participating in electricity markets. In the context of residential microgrids, which is a type of ADNs, aggregated home heating, ventilation and air-conditioning (HVAC) loads present a key opportunity to drive operational and economic objectives, facilitate high renewable energy penetration, and enhance both system resiliency and flexibility. A robust, hierarchical dispatch scheme is developed and presented in this paper, which connects an upper level multi-phase distribution optimal power flow (DOPF) to a lower level model predictive control (MPC)-based HVAC fleet controller. The approach is tested and verified on a modified IEEE 13 bus system in an intraday market application. The results demonstrate that the proposed hierarchical dispatch scheme is able to drive both economic and operational objectives for the ADN operator.

Rooks, Cody D.↗
DOE OSTI2021

The effects of allelochemical transfer on the dynamics of hosts, parasitoids, and competing hyperparasitoids

Allelochemicals produced by plants may be ingested by herbivorous insects and transferred to higher trophic levels with potentially deleterious effects. We develop a system of differential equations to investigate the effect of the transfer of allelochemicals, such as nicotine, on the population dynamics of a system of hosts, parasitoids, and two competing hyperparasitoids that attack different life stages of the parasitoids. We find both somewhat deleterious effects of nicotine on the larvae-attacking hyperparasitoids and increased attack rates for the pupae-attacking hyperparasitoids can promote coexistence. We also use an evolutionary game-theoretic approach to determine the optimal distribution of hyperparasitoid attacks among nicotine-producing and nicotine-free plants. With strong deleterious effects of nicotine and increased attack rates for the pupae-attacking hyperparasitoid, we find both species attack parasitoids on the nicotine-free plant but only pupae-attacking hyperparasitoids attack parasitoids on the nicotine-producing plant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Interpreting Ionic Conductivity for Polymer Electrolyte Fuel Cell Catalyst Layers with Electrochemical Impedance Spectroscopy and Transmission Line Modeling

A cathode catalyst layer containing optimally distributed ionomer is critical to reduce the platinum loading and increase its utilization in polymer electrolyte fuel cells. Here, electrochemical impedance spectroscopy (EIS) was used to measure effective ionic conductivity of pseudo catalyst layers (PCLs) at a relative humidity (RH) range of 50%-120%. These results are compared to previous work using the hydrogen pump (HP) method. EIS effective ionic conductivity results reported here are higher than those from the HP because in the HP set-up ionic pathways must be effectively connected through the PCL to be counted, whereas in the EIS measurement, ionomer segments that are in contact with the membrane but are not effectively connected all the way through the PCL can be detected. Double layer capacitances and effective ionic conductivities of Pt/C catalyst layers with various supports and ionomer to carbon (I/C) ratios were studied. High surface area carbon support resulted in a lower effective ionic conductivity compared to the graphitized carbon support due to worse ionomer dispersion. Effective ionic conductivities of Pt/C layers were compared to that of PCLs. On average, effective ionic conductivities of Pt/C layers were higher than PCLs because of possible carbon agglomeratio n within the PCLs.

25 ENERGY STORAGE↗
DOE OSTI2020

Wattile: Probabilistic Deep Learning-based Forecasting of Building Energy Consumption [SWR-20-94]

Accurate energy forecasting is becoming critical due to many reasons: i ) optimal distributed energy resources operations and dispatch, ii) fault detection and diagnostics, and iii) meeting operational energy efficiency targets. Wattile uses deep learning (DL) for the building's short-term load forecasting application. Two specific types of neural networks called, Long Short Term Memory (LSTM) and Sequence-to-Sequence (S2S) models are used to make predictions. Forecasting models are trained using online historical weather and occupancy indicator data streams from the Intelligent Campus Program's data acquisition systems at the National Renewable Energy Laboratory (NREL) for main meters and sub-meters of multiple building types. These models use probabilistic methods to provide quantile-based forecasts in addition to nominal conditional median predictions of electricity consumption.

Frank, Stephen↗
DOE OSTI2023

Multi-injection investigation of a high-volatility diesel in advanced compression ignition combustion for NO x control

Traditional selective catalytic reduction aftertreatment technologies used to reduce [Formula: see text] are very limited at exhaust temperatures below [Formula: see text]. Therefore, under these low engine load conditions, having effective in-cylinder control of [Formula: see text] emissions is important. Previous work by the authors explored the effect of fuel physical properties on the ability to control [Formula: see text] in-cylinder. That work was limited to one direct injection near top dead center. Modern diesel high-pressure fuel systems have the capability of five or more injections in one engine cycle. A higher-volatility diesel fuel and high amounts of exhaust gas recirculation to delay ignition could provide an opportunity for reduction in engine-out [Formula: see text] through an increased level of fuel premixing. By appropriately timing multiple short injections, a more optimal distribution of fuel in-cylinder may be achieved, which could reduce [Formula: see text] while maintaining an efficient combustion phasing. A computational fluid dynamics model previously validated against experimental data was used to explore several injection strategies with increased levels of fuel premixing to assess the potential trade-offs between [Formula: see text] and CO/unburned hydrocarbon (UHC) emissions and thus reduce reliance on the aftertreatment system for [Formula: see text] control. The results show that the devised injection strategies resulted in an increased level of fuel premixing. However, none of the attempted injection strategies resulted in significant [Formula: see text] reductions, and all strategies showed a significant increase in CO and UHC emissions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks

The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized strategy that requires transferring the training data to a centralized location. Such a strategy, however, limits our ability to secure data privacy or use high-performance distributed/parallel computing platforms. To alleviate such limitations, in this paper, we study the federated training of DeepONets for the first time. That is, we develop a framework, which we refer to as Fed-DeepONet, that allows multiple clients to train DeepONets collaboratively under the coordination of a centralized server. To achieve Fed-DeepONets, we propose an efficient stochastic gradient-based algorithm that enables the distributed optimization of the DeepONet parameters by averaging first-order estimates of the DeepONet loss gradient. Then, to accelerate the training convergence of Fed-DeepONets, we propose a moment-enhanced (i.e., adaptive) stochastic gradient-based strategy. Finally, we verify the performance of Fed-DeepONet by learning, for different configurations of the number of clients and fractions of available clients, (i) the solution operator of a gravity pendulum and (ii) the dynamic response of a parametric library of pendulums.

Moya, Christian↗
DOE OSTI2019

Getting the Most Out of Your Crystals: Data Collection at the New High-Flux, Microfocus MX Beamlines at NSLS-II

Advances in synchrotron technology are changing the landscape of macromolecular crystallography. The two recently opened beamlines at NSLS-II—AMX and FMX—deliver high-flux microfocus beams that open new possibilities for crystallographic data collection. They are equipped with state-of-the-art experimental stations and automation to allow data collection on previously intractable crystals. Optimized data collection strategies allow users to tailor crystal positioning to optimally distribute the X-ray dose over its volume. Vector data collection allows the user to define a linear trajectory along a well diffracting volume of the crystal and perform rotational data collection while moving along the vector. This is particularly well suited to long, thin crystals. We describe vector data collection of three proteins—Akt1, PI3Kα, and CDP-Chase—to demonstrate its application and utility. For smaller crystals, we describe two methods for multicrystal data collection in a single loop, either manually selecting multiple centers (using H108A-PHM as an example), or “raster-collect”, a more automated approach for a larger number of crystals (using CDP-Chase as an example).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Conjugate gradient determination of optimal plane changes for a class of three-impulse transfers between noncoplanar circular orbits

A particular type of three-impulse transfer between two circular orbits is analyzed. The possibility of three plane changes is recognized, and the problem is to optimally distribute these plane changes to minimize the sum of the individual impulses. Numerical difficulties and their solution are discussed. Numerical results obtained from a conjugate gradient technique are presented for both the case where the individual plane changes are unconstrained and for the case where they are constrained. Possibly not unexpectedly, multiple minima are found. The techniques presented could be extended to the finite burn case, but primarily the contents are addressed to preliminary mission design and vehicle sizing.

Burrows, R. R.↗
NASA NTRS1974

Analysis of three-dimensional unsteady flow around oscillating wings

A method based on the Navier-Stokes equations was developed for determining analytically the three-dimensional unsteady flow patterns around oscillating wings. The Helmholz vorticity transport equations were discretized in three-dimensional finite element form from a variational formulation and integrated numerically. At each time step of the numerical integration the velocity field was calculated from the representation of the three-dimensional wing by a system of optimized distribution of vortices in space. During the numerical integration of the vorticity transport equations the time-dependent boundary conditions on the wing were specified as external constraint conditions. Examples of obtained results describing the three-dimensional unsteady flow around a wing were presented.

Bratanow, T.↗
NASA NTRS1979

A procedure for optimal control of flexible surface vibrations

The vibration controller design for a thin flexible surface with a given boundary is formulated as an unconstrained optimization problem. It is shown that this formulation is equivalent to a system of uncoupled optimization problems each of which is a linear regulator design problem for a second-order modal system. The regulator solutions give the gains on the modal amplitude and velocity associated with each modal system. For the constrained control case corresponding to a finite number of actuators, an approximation to the optimal distributed control is given. For the case of a limited number of physical sensors, a dual approach yields a system of second-order observers or filters. Simulations indicate that the constrained controller has a satisfactory performance as long as the number of actuators is more than half the number of controlled modes.

Caglayan, A. K.↗
NASA NTRS1990

NASA-UCLA Workshop on Computational Techniques in Identification and Control of Flexible Flight Structures, Lake Arrowhead, CA, Nov. 2-4, 1989, Proceedings

The present conference on the identification and control of flexible flight structures with computational techniques encompasses existing and planned testbeds, modeling techniques, adaptive control, and numerical computation and simulation. Specific issues addressed include the NASA/MFSC ground test facility, an active control test on the NASA Minimast, the Astrex testbed for large precision space structures, the dynamic analysis of truss-beam modeling, combined structure-controls-integrated optimization, distributed parameter modeling applicable to the control of flexible flight structures, and approaches to nonclassically damped dynamic systems. Also addressed are adaptive control concepts, techniques for vibration and decentralized slew maneuver control, the discretization of second-order-in-time differential equations which are applicable to nonlinear wave problems, the finite-dimensional approximations of Riccati equations, and numerical simulations of actively controlled space structures.

Balakrishnan, A. V.↗
NASA NTRS1992

Spacecraft survivability in the meteoroid and debris environment

A number of methods for providing adequate protection from meteoroid and orbital debris impact are available to space vehicle designers. Several techniques to reduce the risks from meteoroid and debris (M&D) impact are presented and assessed in the context of Space Station Freedom (SSF) applications. Evaluations of these options were made using BUMPER, a computer program to perform M&D analyses. M&D survivability can be improved by conducting an in-depth analysis of spacecraft penetration risks to reveal weak areas of the design and to determine optimal distribution of shielding and/or protection capability around the space vehicle. This paper compares enhanced hypervelocity impact shielding techniques that are more weight efficient than conventional shielding approaches. Other design and operational strategies to reduce meteoroid and debris risks are also discussed.

Christiansen, Eric L.↗
NASA NTRS1993

Optimization of energy transfer in microwave electrothermal thrusters

Results are presented from preliminary tests conducted to evaluate the performance of a prototype microwave electrothermal thruster. The primary component of the device is a microwave resonant cavity. The device produces stable axial plasmas within a pressurized section of the cavity with the plasma positioned in the inlet region of the nozzle. Plasma stability is enhanced by axial power coupling, an optimal distribution of electric power density within the cavity, and a propellant gas flow which has a large vortical velocity component. The thruster has been operated with a number of propellant gases: helium, nitrogen, ammonia, and hydrogen. Plasmas can be formed in a reliable manner at cavity pressures of 1 kPa and incident power levels ranging from 50 W to 350 W, depending on the gas used, and can be operated at pressures up to 300 kPa at power levels up to 2200 W. Ideal performance results of vacuum Isp and thermal efficiency vs. specific power are presented for each gas. Representative results of this preliminary work are: He - Isp = 625 s, eta-thermal = 90 percent; N2 - Isp = 270 s, eta-thermal = 41 percent; NH3 - Isp = 475 s, eta-thermal= 55 percent; H2 - Isp = 1040 s, eta-thermal = 53 percent.

Sullivan, D. J.↗
NASA NTRS1994

Space/ground systems as cooperating agents

Within NASA and the European Space Agency (ESA) it is agreed that autonomy is an important goal for the design of future spacecraft and that this requires on-board artificial intelligence. NASA emphasizes deep space and planetary rover missions, while ESA considers on-board autonomy as an enabling technology for missions that must cope with imperfect communications. ESA's attention is on the space/ground system. A major issue is the optimal distribution of intelligent functions within the space/ground system. This paper describes the multi-agent architecture for space/ground systems (MAASGS) which would enable this issue to be investigated. A MAASGS agent may model a complete spacecraft, a spacecraft subsystem or payload, a ground segment, a spacecraft control system, a human operator, or an environment. The MAASGS architecture has evolved through a series of prototypes. The paper recommends that the MAASGS architecture should be implemented in the operational Dutch Utilization Center.

Grant, T. J.↗
NASA NTRS2000

A Reduced Order Model of the Linearized Incompressible Navier-Strokes Equations for the Sensor/Actuator Placement Problem

A reduced order modeling approach of the Navier-Stokes equations is presented for the design of a distributed optimal feedback kernel. This approach is based oil a Krylov subspace method where significant modes of the flow are captured in the model This model is then used in all optimal feedback control design where sensing and actuation is performed oil tile entire flow field. This control design approach yields all optimal feedback kernel which provides insight into the placement of sensors and actuators in the flow field. As all evaluation of this approach, a two-dimensional shear layer and driven cavity flow are investigated.

Allan, Brian G.↗