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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Load Margin Constrained Moving Target Defense against False Data Injection Attacks

Cyber physical security of power systems with high penetration of renewable generation has attracted attention from researchers. One critical issue is that cyber-physical attacks, disguised as uncertain renewable generation, can target conventional power system state estimation (SE). Moving target defense (MTD) is a promising defense strategy to detect stealthy false data injection (FDI) attacks against SE. However, all existing studies myopically perturb the reactance of transmission lines equipped with distributed flexible AC transmission system (D-FACTS) devices without adequately considering the system voltage stability. Exacerbated by the renewable generation uncertainty, existing MTD may cause voltage instability when the power grid is under stress. To address this issue, we propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow. We utilize the sensitivity matrix of power injection to line impedance, on which an optimization problem for maximizing load margin is formulated. This framework is validated on the IEEE 14-bus system and the IEEE 118-bus system, in which net load redistribution attacks are launched by sophisticated attackers. Steady-state simulations and dynamic simulations on PSS/E show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. The impact of the proposed method on attack detection effectiveness is also revealed.

Zhang, Hang↗
NASA NTRS1980

Decentralized stochastic control

Decentralized stochastic control is characterized by being decentralized in that the information to one controller is not the same as information to another controller. The system including the information has a stochastic or uncertain component. This complicates the development of decision rules which one determines under the assumption that the system is deterministic. The system is dynamic which means the present decisions affect future system responses and the information in the system. This circumstance presents a complex problem where tools like dynamic programming are no longer applicable. These difficulties are discussed from an intuitive viewpoint. Particular assumptions are introduced which allow a limited theory which produces mechanizable affine decision rules.

Speyer, J. L.↗
NASA NTRS1999

Fossils, molecules and embryos: new perspectives on the Cambrian explosion

The Cambrian explosion is named for the geologically sudden appearance of numerous metazoan body plans (many of living phyla) between about 530 and 520 million years ago, only 1.7% of the duration of the fossil record of animals. Earlier indications of metazoans are found in the Neoproterozic; minute trails suggesting bilaterian activity date from about 600 million years ago. Larger and more elaborate fossil burrows appear near 543 million years ago, the beginning of the Cambrian Period. Evidence of metazoan activity in both trace and body fossils then increased during the 13 million years leading to the explosion. All living phyla may have originated by the end of the explosion. Molecular divergences among lineages leading to phyla record speciation events that have been earlier than the origins of the new body plans, which can arise many tens of millions of years after an initial branching. Various attempts to date those branchings by using molecular clocks have disagreed widely. While the timing of the evolution of the developmental systems of living metazoan body plans is still uncertain, the distribution of Hox and other developmental control genes among metazoans indicates that an extensive patterning system was in place prior to the Cambrian. However, it is likely that much genomic repatterning occurred during the Early Cambrian, involving both key control genes and regulators within their downstream cascades, as novel body plans evolved.

Non-NASA Center↗
DOE OSTI2021

Effects of multiple simultaneous faults on characteristic fault detection features of a heat pump in cooling mode

Faults in air-cooled vapor compression air-conditioning systems are known to reduce performance, including efficiency, capacity, and lifespan. Their effects have been studied, and fault detection and diagnostic (FDD) methods have been developed as tools for field technicians to install or repair systems, or for monitoring to alert operators to the fault’s presence. Most of this work has focused on faults that occur singly. It is likely that in some systems, multiple faults occur simultaneously, but it is uncertain what effects this may have on diagnostics. Here, this paper describes a laboratory study of a split system air source heat pump in which combinations of two, three, and four simultaneous faults occur. The study includes all combinations of: improper evaporator airflow; overcharge or undercharge of refrigerant; liquid line restrictions; and non-condensable gas in the refrigerant, each at multiple fault intensities. Fault features – those characteristics that can be determined from measurements, for use in diagnostics – are analyzed, and the key fault features are presented. A robust existing method for determining refrigerant charge, the virtual refrigerant charge sensor (VRC) is tested using the multiple fault data, in order to understand how its performance is impacted by the combined faults. The VRC performs well, typically able to correctly determine whether a system is undercharged or overcharged, but the magnitude estimates are impacted. The results suggest that simple subcooling-based methods of charging a system are likely to provide unsatisfactory results when other faults are present.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

Learning to integrate reactivity and deliberation in uncertain planning and scheduling problems

This paper describes an approach to planning and scheduling in uncertain domains. In this approach, a system divides a task on a goal by goal basis into reactive and deliberative components. Initially, a task is handled entirely reactively. When failures occur, the system changes the reactive/deliverative goal division by moving goals into the deliberative component. Because our approach attempts to minimize the number of deliberative goals, we call our approach Minimal Deliberation (MD). Because MD allows goals to be treated reactively, it gains some of the advantages of reactive systems: computational efficiency, the ability to deal with noise and non-deterministic effects, and the ability to take advantage of unforseen opportunities. However, because MD can fall back upon deliberation, it can also provide some of the guarantees of classical planning, such as the ability to deal with complex goal interactions. This paper describes the Minimal Deliberation approach to integrating reactivity and deliberation and describe an ongoing application of the approach to an uncertain planning and scheduling domain.

Chien, Steve A.↗
DOE OSTI2024

Practical and Optimal Sequential Bayesian Experimental Design for Complex Systems Incorporating Human Experimenter Preferences (Final Scientific/Technical Report)

Experiments are indispensable for developing models of complex systems. Carefully designed experiments can provide substantial savings for these expensive data-acquisition opportunities. However, designs based on heuristics are often suboptimal for systems with multiphysics, nonlinear dynamics, and uncertain and noisy environments. Optimal experimental design, while leveraging predictive models, seeks to systematically quantify and maximize the value of experiments. In this project, we focused on the design of multiple experiments, where current approaches are largely suboptimal: batch-design does not adapt to new data acquired during the experiment campaign (no feedback), and greedy/myopic design ignores future dynamics and consequences (no lookahead). We developed the mathematical framework and computational methods for sequential optimal experimental design (sOED) for complex systems. We enabled tractable model-based sOED in a rigorous manner through novel algorithms based on reinforcement learning, and investigated the effects of human experimenters on the design process. Our methods are fully Bayesian, able to quantify and update uncertainty in a principled manner. The traits aimed by our approach—mathematical rigor and optimality, human effects and uncertainty quantification, computational practicality—are crucial for elevating the standards of artificial intelligence (AI) to support decision-making in scientific domains, and contribute toward trust and realistic adoption of AI in experimental design practice.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Role of PHM in Autonomous Decision-Making: Aerospace applications

There is an increased need for onboard decision-making capabilities in cyber-physical systems be it in energy, automotive, aviation, space, or other industries as they aim for increased efficiency, resiliency, and mission assurance capabilities. Emerging next-gen technologies such as multi-rover planetary missions, distributed satellites, unmanned ground and aerial vehicle operations and smart grid systems rely on in-time risk assessment and autonomous decision-making. One critical piece of the autonomy puzzle is reliable prediction of system behavior under time-varying and potentially uncertain environmental conditions. Further, if agent states change during operation such as initiation of faults or degradation, reliable diagnostic tools need to be investigated. In this tutorial, we will revise approaches that integrates existing physics-based and data-driven models of agents interacting with probability models of the environment and component operation state. Role of existing PHM methodologies as they feed into decision-making under uncertainty will be studied. Balancing critical trade-offs between high-fidelity prognostic models, prediction time-horizons and the computational requirements for in-time cost-effective decision-making will be discussed through the implementation of surrogate models. Finally, the audience will be introduced to a real-time application of in-time trajectory planning of an unmanned aerial system (UAS) based on its PHM assessments under uncertain and varying wind conditions.

decision-making↗
NASA NTRS2017

Interstellar and Solar Nebula Materials in Cometary Dust

Laboratory studies of cometary dust collected in the stratosphere and returned from comet 81P/Wild 2 by the Stardust spacecraft have revealed ancient interstellar grains and molecular cloud organic matter that record a range of astrophysical processes and the first steps of planetary formation. Presolar materials are rarer meteorites owing to high temperature processing in the solar nebula and hydrothermal alteration on their asteroidal parent bodies. The greater preservation of presolar materials in comets is attributed to their low accretion temperatures and limited planetary processing. Yet, comets also contain a large complement of high temperature materials from the inner Solar System. Owing to the limited and biased sampling of comets to date, the proportions of interstellar and Solar System materials within them remains highly uncertain. Interstellar materials are identified by coordinated isotopic, mineralogical, and chemical measurements at the scale of individual grains. Chondritic porous interplanetary dust particles (CP IDPs) that likely derive from comets are made up of 0.1 - 10 micron-sized silicates, Fe-Ni-sulfides, oxides, and other phases bound by organic material. As much as 1% of the silicates are interstellar grains that have exotic isotopic compositions imparted by nucleosynthetic processes in their parent stars. Crystalline silicates in CP IDPs dominantly have normal isotopic compositions and probably formed in the Solar System. 81P samples include isotopically normal refractory minerals that resemble Ca-Al rich inclusions and chondrules common in meteorites. The origins of sub-micron amorphous silicates in IDPs are not certain, but at least a few % of them are interstellar grains. The remainder have isotopic compositions consistent with Solar System origins and elemental compositions that are inconsistent with interstellar grain properties, thus favoring formation in the solar nebula [4]. The organic component in comets and primitive meteorites has large enrichments in D/H and N-15/N-14 relative to terrestrial materials. These isotopic signatures are probably due to low temperature chemical processes in cold molecular clouds or the outermost reaches of the protoplanetary disk. The greatest isotopic anomalies are found in sub-micron organic nanoglobules that show chemical signatures of interstellar chemistry. The observation that cometary dust is mostly composed of isotopically normal minerals within isotopically anomalous organic matter is difficult to reconcile with the formation models of each component. The mineral component likely formed in high temperature processes in the inner Solar System, while the organic fraction shows isotopic and chemical signatures of formation near 10 K. Studying more primitive remnants of the Solar System starting materials would help in resolving this paradox. Comets formed across a vast expanse of the outer disk under differing thermal and collisional regimes, and some are likely to be better preserved than others. Finding truly pristine aggregates of presolar materials may require return of a pristine sample of comet nucleus material.

Messenger, Scott↗
NASA NTRS1990

Dynamic control of robotic welding - On-going research

Two major challenges exist for the development of dynamic control systems: first, the control system must be resourceful enough to provide problem-solving capabilities in unforeseen circumstances; second, it must be rapid enough to respond to dynamic environments. Most conventional control systems do not have the ability to 'step back' and problem-solve, especially in environments with incomplete and uncertain models and data. Orthogonally, commercially available AI systems usually do not respond at the rates required to support 'real-time' control. Hence, control systems are not available that respond to complex dynamic environments within appropriate time constraints. This paper describes work on an AI-based control system designed to address these challenges. A prototype system has been used, in a simulated environment, to control the robotic welding of aerospace components. This AI-based control system has demonstrated the ability to flexibly control a complex process within required time constraints by incorporating higher level reasoning and the ability to deal with uncertainty. Further work is in progress to expand the system's problem-solving capabilities.

Ruokangas, Corinne C.↗
NASA NTRS1991

New bounds on parameter uncertainties for robust stability

The problem of robust stability in linear systems with parametric uncertainties is considered. A method is developed to determine bounds on uncertain parameters in the state-space model of the system, so that stability is preserved. Both continuous- and discrete-time systems are considered. Unlike previous results, the stability bounds are derived in terms of actual parameters instead of their absolute values, and consequently the stable region in the parameter space is not necessarily symmetric with respect to the origin. Furthermore, the uncertain parameters do not have to be linearly independent to each other.

Gao, Zhiqiang↗
NASA NTRS1993

Explicit asymmetric bounds for robust stability of continuous and discrete-time systems

The problem of robust stability in linear systems with parametric uncertainties is considered. Explicit stability bounds on uncertain parameters are derived and expressed in terms of linear inequalities for continuous systems, and inequalities with quadratic terms for discrete-times systems. Cases where system parameters are nonlinear functions of an uncertainty are also examined.

Gao, Zhiqiang↗
DOE OSTI2021

Global Sensitivity Analysis of Large Distribution System with PVs using Deep Gaussian Process

Global sensitivity analysis (GSA) of the voltage to uncertain power injection variations plays an important role for appropriate Volt-VAR optimization. This paper proposes a data-driven GSA method for large-scale distribution systems with a large number of uncertain sources. Specifically, the deep Gaussian process is used to identify the mapping relationship between uncertain power injections and voltages. This allows us to resort to the analysis of variance framework to calculate the Sobol indices for GSA. Unlike the existing polynomial chaos expansion and Gaussian process-based approaches, our proposed method has much better scalability. Test results on the EPRI 1747-node K1 circuit with a different number and different probability distributions of uncertain sources demonstrate that the proposed method can achieve accurate GSA under various conditions.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Enabling Simulation Interoperability between International Standards in the Space Domain

Today, the design and development of space systems are conducted cooperatively by historical space agencies in this area such as NASA, ESA, Roscosmos, and JAXA together with their industrial partners. The space system lifecycle is characterized by high costs, uncertain conditions, and dangerous scenarios. To mitigate these issues, space agencies rely heavily on Modelling and Simulation as a key technology to support the analysis, design, and operation of space systems. To support large-scale distributed simulations, the scientific community has developed several standards to support the reuse and interoperability of simulation models such as IEEE 1516 High-Level Architecture (HLA), Real-time Platform Reference Federation Object Model (RPR FOM), Simulation Model Portability (SMP), and the novel Space Reference Federation Object Model (SpaceFOM). While the SpaceFOM standard has been specifically conceptualized for handling space systems, the other ones are more general-purpose and can be used to design and simulate generic complex systems. As a consequence, there is a lake of rules and guidelines to enable interoperability among these standards. The paper presents solutions and experiences for enabling interoperability and transferability of HLA, RPR FOM, and SMP simulation models with SpaceFOM.

Simulation↗
DOE OSTI2021

Chapter 9: Impact of Variable Renewable Energy Sources on Bulk Power System Planning and Operations

Wind and solar photovoltaics (PV) have experienced remarkable growth in recent years, with many consequent benefits within and outside of power systems. At the same time, wind and solar PV have unique characteristics relative to the historically dominant dispatchable technologies like coal, gas, and nuclear power plants that have required and will continue to require changes in power system planning and operations. This chapter discusses planning and operational challenges of integrating wind and solar PV into bulk power systems. We first present the key characteristics of wind and solar PV that differentiate it from conventional technologies, such as variable and uncertain electricity generation, asynchronous interconnection to the power system, and near-zero marginal costs. We then link these characteristics to power system planning and operational challenges at low through high wind and solar penetrations. Finally, we discuss near- and long-term solutions to those challenges, such as diversifying the generation mix and wind and solar fleets, improving system flexibility, diversifying ancillary service products, and integrating generation and transmission planning.

bulk power system↗
DOE OSTI2020

Advanced Synchrophasor-based Application for Potential Distributed Energy Resources Management: Key Technology, Challenge and Vision

With an increasing number of distributed energy resources (DERs) integrating into the power system, the power grid is becoming more complex and uncertain. Owing to most of DERs are through grid-connected converters to integrate into the power system, the intermittent nature and resource-depended characteristic of the DERs are challenging their monitoring and control. Conventional synchronized measurement devices (SMDs) may be difficult to provide qualified data for DERs management for its accuracy and reporting-rate limitation. The monitoring systems developed basing on SMDs may be insufficient for depicting detailed dynamic manifestations of power systems with a high proportion integration of DERs. This paper shares some advanced synchrophasor-based applications developed in FNET/GridEye, which have a broad prospect for assisting system operator on the control and integration of the DERs.

Wang, Weikang↗
NASA NTRS2018

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Nguyen, Nhan T.↗
NASA NTRS1988

Robustness with real parametric and structured complex uncertainty

The problem of robust stability and performance in feedback control systems with n real (possibly related) uncertain parameters and structured unmodeled dynamics (the latter taking the form of m complex blocks dynamic uncertainties) is considered. A robustness margin rm is defined with respect to such model uncertainty structure and an algorithm is developed to compute it. Robust stability and performance are characterized in terms of r sub m or the structured singular value mu. An iterative procedure using the above algorithm is given to compute tight bounds on k sub m and mu. These bounds are exact for the case m = 3 or less.

Pena, Ricardo S. Sanchez↗
NASA NTRS1992

Nonlinear robust controller design for multi-robot systems with unknown payloads

This work is concerned with the control problem of a multi-robot system handling a payload with unknown mass properties. Force constraints at the grasp points are considered. Robust control schemes are proposed that cope with the model uncertainty and achieve asymptotic path tracking. To deal with the force constraints, a strategy for optimally sharing the task is suggested. This strategy basically consists of two steps. The first detects the robots that need help and the second arranges that help. It is shown that the overall system is not only robust to uncertain payload parameters, but also satisfies the force constraints.

Song, Y. D.↗