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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multi-resolution, Multi-scale Modeling for Scalable Macroalgae Production

Macroalgae harvested along coastlines and in the open ocean has traditionally been used as food for human consumption, animal feed, and fertilizer. The U.S. ARPA-E MARINER Program estimates that the nation has suitable conditions and geography to produce at least 500 million dry metric tons of macroalgae per year, yielding approximately 2.7 quadrillion BTUs of energy in the form of liquid fuel, which is roughly 10% of the nation’s annual transportation energy demand. Adverse environmental effects of nutrient overload and ocean acidification may also be reduced by large-scale macroalgae cultivation in many coastal ocean regions. However, the successful deployment of large-scale marine macroalgae farms for fuel production depends on ambient hydrodynamic conditions and nutrient availability, as well as their interactions with macroalgae farm structures. Pacific Northwest National Laboratory led an ARPA-E MARINER project to develop a set of numerical modeling tools capable of simulating ocean hydrodynamic and biogeochemical processes, macroalgae trajectories for free-floating systems, macroalgae growth and biomass yields, and hydrodynamic load on macroalgae canopies and farm structures using a multi-resolution and multi-scale approach. This set of modeling tools provides a suite of information essential for system design, optimal project siting, risk analysis, and management of macroalgae production systems in the ocean. Better clarity can also help macroalgae system developers reduce deployment costs, operational risk, and potential impacts on the local marine environment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Fayyad, Usama M.↗
NASA NTRS1993

Streak camera based SLR receiver for two color atmospheric measurements

To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.

Varghese, Thomas K.↗
NASA NTRS1975

Control optimization, stabilization and computer algorithms for aircraft applications

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

Source record↗
NASA NTRS1981

A programing system for research and applications in structural optimization

The paper describes a computer programming system designed to be used for methodology research as well as applications in structural optimization. The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities existing in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of contraints and design variables. Features shown in numerical examples include: (1) variability of structural layout and overall shape geometry, (2) static strength and stiffness constraints, (3) local buckling failure, and (4) vibration constraints. The paper concludes with a review of the further development trends of this programing system.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1978

Theory and applications for optimization of every part of a photovoltaic system

A general method is presented for quantitatively optimizing the design of every part and fabrication step of an entire photovoltaic system, based on the criterion of minimum cost/Watt for the system output power. It is shown that no element or process step can be optimized properly by considering only its own cost and performance. Moreover, a fractional performance loss at any fabrication step within the cell or array produces the same fractional increase in the cost/Watt of the entire array, but not of the full system. One general equation is found to be capable of optimizing all parts of a system, although the cell and array steps are basically different from the power-handling elements. Applications of this analysis are given to show (1) when Si wafers should be cut to increase their packing fraction; and (2) what the optimum dimensions for solar cell metallizations are. The optimum shadow fraction of the fine grid is shown to be independent of metal cost and resistivity as well as cell size. The optimum thicknesses of both the fine grid and the bus bar are substantially greater than the values in general use, and the total array cost has a major effect on these values. By analogy, this analysis is adaptable to other solar energy systems.

Redfield, D.↗
DOE OSTI2023

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗
DOE OSTI2025

A Behavioral Robotics Approach to Radiation Mapping Using Adaptive Sampling

Radiation mapping is a desirable task to automate because of the inherent risks involved and its tedious nature. A novel system was designed to address this by combining various existing technologies, utilizing behavior-based robotics and Bayesian optimization. The system uses a quadruped robot equipped with a manipulator and gamma detector to take measurements at locations that are selected based on the uncertainty of a surrogate model used to estimate the true radiation field. The robot uses input from the world with depth cameras to avoid collisions with the robot’s body, and unreachable points for the end effector are addressed by both allowing for a soft collision with the environment to occur, prompting the system to abandon that point, and varying the exploration tendency of the optimization based on consecutive collisions. This approach provides unique traversability and adaptability over other strategies in the literature. Experiments were performed by placing a Cesium-137 source on the ground and varying geometric setups and an optimization parameter demonstrating the adaptability to diverse environments and the increased robustness resulting from the designed behavior. The results additionally demonstrate that dynamically adjusting the optimization algorithm’s exploration tendency based on the arm’s collision history improves the system’s ability to navigate cluttered environments and construct accurate radiation maps without getting stuck in unreachable areas.

Adams, Joel↗
DOE OSTI2022

Data-Driven Distribution System Coordinated PV Inverter Control Using Deep Reinforcement Learning

The deployment of distributed solar photovoltaic (PV) systems has increased consistently over the past decades. High penetrations of PVs could cause a series of adverse grid impacts, such as voltage violations. The recent development of smart inverter technologies rises the incentives of developing PV control solutions that regulate the inverter output power and seeking the optimization on system operational objectives. This paper proposes a data-driven control solution based on deep reinforcement learning (DRL) to optimize PV inverters for voltage regulation. The proposed solution can minimize PV real power curtailment while maintaining network voltage at an acceptable range. Comparison results between the proposed DRL control algorithms with deep deterministic policy gradient (DDPG) and volt-var control on a real feeder in west Colorado highlight the advantage of the proposed framework in controlling the system voltage while minimizing the PV real power curtailment.

deep reinforcement learning↗
DOE OSTI2020

Improving AHU Performance by Minimizing Approach Temperature, Reducing Air Maldistribution, and Efficiently Handling Sensible and Latent Loads (Phase 1 Interim Final Technical Report)

Residential air handling units (AHUs) have stayed the same in form and efficiency for the past 30+ years, with incremental improvements made to address safety, functionality, and energy-efficiency. The purpose of this research in Phase I, Topic 9a: Next Generation Residential Air Handlers, was to improve AHU performance by minimizing heat exchanger (HX) approach temperature, reducing air maldistribution, and developing alternative system configurations which more efficiently handle sensible and latent loads. In this research Optimized Thermal Systems (OTS) developed, modeled, and evaluated multiple alternative system concepts. A dual vapor compression system separate sensible and latent cooling (SSLC) concept was studied to inform work on alternative concepts and to show best-case performance benefit. System concepts included ejector enhanced vapor compression cycles, desiccant assisted dehumidification, dual evaporator SSLC, and alternative AHU HX configurations. A dual vapor compression system showed COP improvement of 20%, however, required additional components, increased unit size, and increased cost. Two types of ejector enhanced vapor compression cycles with dual evaporators improved system COP by 9 to 11%, and reduced AHU losses by as much as 18%, with design changes limited to the AHU, no unit physical size increase, and a moderate increase to system first cost. Desiccant assisted air-conditioning required increased air flow rate resulting in higher fan power and the desiccant wheel increased sensible heat load leading to increased compressor power and reduced system COP. Dual evaporator cycles were found to degrade performance due to increased expansion losses. Optimized single slab HX designs used in place of the traditional A-coil HX led to 44–49% reduction in aluminum, 47–60% less refrigerant charge, and improved HX velocity distribution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA’s ISRU Technology Demonstration Plant

In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s)range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant.

ISRU↗
DOE OSTI2026

Mu2e resonant extraction regulation system simulation in delivery ring

Mu2e is an upcoming experiment at Fermilab that relies on the slowly extracted 8 GeV proton beam from the Delivery Ring. The experiment imposes strong requirements on the spill uniformity. To address these requirements, the fast spill regulations system is being developed and commissioned. To inform this development and optimize the system performance we are carrying out the detailed simulations of the regulation process. The simulation includes the effect of six harmonic sextupoles that excite the third-integer resonance and three fast ramping quadrupoles that drive the horizontal tune to 29/3. The components of spill regulation system are designed to mitigate long-term drifts in the beam, ensuring stable operation over extended timescales, as well as addresses rapid variations within single spill. In this study, we review the regulation system design, simulation of the slow regulation, and the fast regulation PID regulation to curtail random variations in the extraction rate that could occur within a single spill.

Narayanan, Aakaash [Fermilab]↗
DOE OSTI2022

MFVI Energy Efficiency Audit Training Module 3.1: Cooling Systems [Slides]

This slide deck is designed to help trained energy efficiency professionals conduct an energy efficiency audit for commercial and industrial buildings, particularly for micro-, small-, and medium-sized businesses in Mexico. This training module is focused on cooling systems. As such, it will assist its user in determining the optimal cooling system for a given space and then identifying the most efficient means of delivering that system.

21CPP↗
DOE OSTI2020

Solving Optimal Power Flow for Distribution Networks with State Estimation Feedback

Conventional optimal power flow (OPF) solvers assume full observability of the involved system states. However in practice, there is a lack of reliable system monitoring devices in the distribution networks. To close the gap between the theoretic algorithm design and practical implementation, this work proposes to solve the OPF problems based on the state estimation (SE) feedback for the distribution networks where only a part of the involved system states are physically measured. The SE feedback increases the observability of the under-measured system and provides more accurate system states monitoring when the measurements are noisy. We analytically investigate the convergence of the proposed algorithm. The numerical results demonstrate that the proposed approach is more robust to large pseudo measurement variability and inherent sensor noise in comparison to the other frameworks without SE feedback.

distirbution systems↗
NASA NTRS1973

A mesh gradient technique for numerical optimization

A class of successive-improvement optimization methods in which directions of descent are defined in the state space along each trial trajectory are considered. The given problem is first decomposed into two discrete levels by imposing mesh points. Level 1 consists of running optimal subarcs between each successive pair of mesh points. For normal systems, these optimal two-point boundary value problems can be solved by following a routine prescription if the mesh spacing is sufficiently close. A spacing criterion is given. Under appropriate conditions, the criterion value depends only on the coordinates of the mesh points, and its gradient with respect to those coordinates may be defined by interpreting the adjoint variables as partial derivatives of the criterion value function. In level 2, the gradient data is used to generate improvement steps or search directions in the state space which satisfy the boundary values and constraints of the given problem.

Willis, E. A., Jr.↗
NASA NTRS2002

A System for Planning Ahead

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

Source record↗