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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methods, systems, and devices to optimize a fluid harvester

An apparatus for energy extraction from fluid flow including an assembly including a plenum. The assembly further includes an aperture extending from an exterior surface to the plenum to allow flow therethrough. The apparatus further includes a channel including an inlet and an outlet in fluid communication with the plenum. The apparatus yet further includes an energy extraction device. The assembly is configured to create a pressure differential between the plenum and the inlet of the channel. The pressure differential causes fluid flow from the inlet of the channel to the plenum. The energy extraction device is configured to extract energy from the fluid flow. The apparatus additionally includes a control system configured to modify the pressure differential to control the fluid flow between the inlet of the channel and the plenum based on a characteristic of an exterior environment.

Houchens, Brent Charles↗
NASA NTRS2004

Adaptive, Distributed Control of Constrained Multi-Agent Systems

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Bieniawski, Stefan↗
DOE OSTI2024

Considerations in Proliferation Resistance Optimization of Medical Isotope Facilities

The U.S. Proliferation Resistance and Optimization (PRO-X) program provides a framework for design optimization of a system, component, or feature of a nuclear facility to minimize potential Special Nuclear Material production and diversion pathways while optimizing system performance for peaceful, asintended missions.

Groden, Nicholas D.↗
DOE OSTI2021

Optimizing Mu2e Spill Regulation System Algorithms

A slow extraction system is being developed for the Fermilab’s Delivery Ring to deliver protons to the Mu2e experiment. During the extraction, the beam on target experiences small intensity variations owing to many factors. Various adaptive learning algorithms will be employed for beam regulation to achieve the required spill quality. We discuss here preliminary results of the slow and fast regulation algorithms validation through the computer simulations before their implementation in the FPGA. Particle tracking with sextupole resonance was used to determine the fine shape of the spill profile. Fast semi-analytical simulation schemes and Machine Learning models were used to optimize the fast regulation loop.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Operation at Reduced Atmospheric Pressure and Concept of Reliability Redundancy for Optimized Design of Insulation Systems

Electrified transportation is calling for insulation design criteria that is adequate to provide elevated levels of power density, power dynamics and reliability. Increasing voltage levels are expected to cause accelerated intrinsic and extrinsic aging effects which will not be easily predictable at the design stage due to a lack of suitable modeling. Designing reliable insulation systems would require finding solutions able to control accelerated aging due to an unpredictable increase of intrinsic stresses and the onset of extrinsic stresses as partial discharges. This paper proposes the concept of reliability redundancy for the insulation design of aerospace electrical asset components, which is also validated at lower-than-standard atmospheric pressure. The principle is that extrinsic-aging-free design might be achieved upon determining the aging stress or abnormal service stresses distribution and being sure that aging will not generate conditions that can incept extrinsic aging (partial discharges) during operation life. However, such information is never, in practice, fully available to insulation system designers. Hence, especially in critical applications such as electrified aircraft, aerospace, and combat ships a further level of reliability should be added to a partial-discharge-free design, which can consist of the use of corona-resistant materials and/or of life models able to consider the accelerated aging effect of partial discharges (or any other type of extrinsic-accelerated aging factor). Innovative life modeling considering both extrinsic and intrinsic aging stresses, insulating material testing to estimate model parameters, and a metric for quantifying the extent of corona (or partial discharge) resistance can lead to establishing feasibility and limit conditions for optimized or fully reliability-redundant design. It is shown in the paper that if an extrinsic-aging-free design is not feasible, and it is therefore replaced by a redundant design, a further level of reliability redundancy can be provided by effective condition monitoring plans.

Montanari, Gian Carlo↗
DOE OSTI2021

Network-Level Optimization for Unbalanced Power Distribution System: Approximation and Relaxation

The nonlinear programming (NLP) problem to solve distribution-level optimal power flow (D-OPF) poses convergence issues and does not scale well for unbalanced distribution systems. The existing scalable D-OPF algorithms either use approximations that are not valid for an unbalanced power distribution system, or apply relaxation techniques to the nonlinear power flow equations that do not guarantee a feasible power flow solution. In this paper, we propose scalable D-OPF algorithms that simultaneously achieve optimal and feasible solutions by solving multiple iterations of approximate, or relaxed, D-OPF subproblems of low complexity. The first algorithm is based on a successive linear approximation of the nonlinear power flow equations around the current operating point, where the D-OPF solution is obtained by solving multiple iterations of a linear programming (LP) problem. The second algorithm is based on the relaxation of the nonlinear power flow equations as conic constraints together with directional constraints, which achieves optimal and feasible solutions over multiple iterations of a second-order cone programming (SOCP) problem. Finally, it is demonstrated that the proposed algorithms are able to reach an optimal and feasible solution while significantly reducing the computation time as compared to an equivalent NLPD-OPF model for the same distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1999

NASA's Virtual Product Laboratory: An Overview

The Virtual Product Laboratory (VPL) developed by NASA's Commercial Remote Sensing Program at the John C. Stennis Space Center is a tool that enables simulation, design, and verification of remote sensing systems within a software (virtual) environment. The VPL can serve industry, government, and university communities by providing a means to conduct system trade studies, optimization, visual modeling, and data product simulations entirely in a virtual environment. The VPL can serve as a complete end-to-end simulation tool capable of producing system and subsystem performance characterizations, system optimization, and simulated data products or as a means of evaluating any one component of a remote sensing system. In this paper, we present an overview of the VPL capabilities. The VPL functional areas include Requirements, Design & Analysis, Simulation, Project Management, Knowledge Base, and Help. A description of each function along with the tools and techniques used to accomplish these functions will be provided. When possible, sample VPL displays and products will be used in the presentation.

Gasser, Jerry↗
NASA NTRS1989

Locally optimal-digital redesign of continuous-time systems

This paper presents a new optimal digital redesign technique for finding a dynamic digital control law from the given continuous-time counterpart by minimizing a local quadratic performance index. The quadratic performance index is chosen as the integral of the weighted squared difference between the states of the original closed-loop system and those of the digitally controlled closed-loop system at any instant between each sampling period. The developed optimal digital redesign control law enables the states of the digitally controlled closed-loop system 10 closely match those of the original closed-loop system at any instant between each sampling period, and it can easily be implemented using microcomputers with a relatively large sampling period.

Shieh, Leang-San↗
NASA NTRS2010

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Nguyen, Nhan T.↗
NASA NTRS1979

Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

Sobieszczanski-Sobieski, J.↗
DOE OSTI2022

An agent-based blackboard system for multi-objective optimization

In the field of multi-objective optimization, there are a multitude of algorithms from which to choose. Each algorithm has strengths and weaknesses associated with the mechanics for finding the Pareto front. Recently, researchers have begun to examine how multi-agent environments can be used to help solve multi-objective optimization problems. In this work, we propose a multi-objective optimization algorithm based on a multi-agent blackboard system (MABS). The MABS framework allows for multiple agents to read and write pertinent optimization problem data to a central blackboard agent. Agents can stochastically search the design space, use previously discovered solutions to explore local optima, or update and prune the Pareto front. A centralized blackboard framework allows the optimization problem to be solved in a cohesive manner and permits stopping, restarting, or updating the optimization problem. The MABS framework is tested against three alternative optimization algorithms across a suite of engineering design problems and typically outperforms the other algorithms in discovering the Pareto front. A parallelizability study is performed where we find that the MABS is able to evaluate a set number of designs, which require an evaluation time ranging from 0 to 300 seconds, quicker than a traditional optimization algorithm: this fact becomes more apparent the longer it takes to evaluate a design. To provide context for the benefits provided by MABS, a real-world nuclear engineering design problem is examined. MABS is used to examine the placement of experiments in a nuclear reactor, where we are able to evaluate hundreds of configurations for experimental placement while maintaining a strict set of safety constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1990

Expert system for multidisciplinary analysis and optimization using ASTROS

This paper discusses the framework of a Knowledge Based Expert System (KBES) environment to design aerospace structures under structural and aerodynamic constraints using ASTROS (Automated Structural Optimization program). ASTROS is a synthesis tool built around the NASTRAN finite element program. The knowledge base capabilities are discussed for synthesizing in statics, normal mode, steady and unsteady aerodynamic disciplines. A description of the two ASTROS advisor modules the Editor/Bulk Data generator and Post-processor is included. Experiences and issues involved in hierarchical representation of knowledge as menu options at different levels of abstraction are presented. A brief overview of Knowledge Based Systems and the shell CLIPS (C Language Integrated Production System) used to develop the ASTROS Advisor are discussed. Illustrative examples of the advisor in designing airframe structures are also included.

Sarma, Hari K.↗
NASA NTRS2000

Performance Optimization of a Rotor Alone Nacelle for Acoustic Fan Testing

This paper describes the techniques, equipment, and results from the optimization of a two-axis traverse actuation system used to maintain concentricity between a sting-mounted fan and a wall-mounted nacelle in the 9 x 15 (9 Foot by 15 Foot Test Section) Low Speed Wind Tunnel (LSWT) at the NASA Glenn Research Center (GRC). The Rotor Alone Nacelle (RAN) system, developed at GRC by the Engineering Design and Analysis Division (EDAD) and the Acoustics Branch, used nacelle-mounted lasers and an automated control system to maintain concentricity as thermal and thrust operating loads displace the fan relative to the nacelle. This effort was critical to ensuring rig/facility safety and experimental consistency of the acoustic data from a statorless, externally supported nacelle configuration. Although the tip clearances were originally predicted to be about 0.020 in. at maximum rotor (fan) operating speed, proximity probe measurements showed that the nominal clearance was less than 0.004 in. As a result, the system was optimized through control-loop modifications, active laser cooling, data filtering and averaging, and the development of strict operational procedures. The resultant concentricity error of RAN was reduced to +/- 0.0031 in. in the Y-direction (horizontal) and +0.0035 in./-0.001 3 in. in the Z-direction (vertical), as determined by error analysis and experimental results. Based on the success of this project, the RAN system will be transitioned to other wind tunnel research programs at NASA GRC.

Cunningham, C. C.↗
NASA NTRS1991

H(infinity) and H2 optimal controllers for periodic and multi-rate systems

The solutions to the optimal l2 to l2 disturbance rejection problem H(infinity) as well as to the LQG (linear quadratic Gaussian) H2 problem in periodic systems using the lifting technique are presented. Both problems involve a causality condition on the optimal LTI (linear time invariant) compensator when viewed in the lifted domain. The H(infinity) problem is solved using the Nehari's theorem, whereas in the H2 problem the solution is obtained using the projection theorem in Hilbert spaces. The authors demonstrate that exactly the same method of solution to the H(infinity) and H2 problems in periodic systems applies when considering the same problems in multirate sampled data systems.

Voulgaris, Petros G.↗
NASA NTRS2004

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗