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At least 1,117 records · Page 62

Comments on Frequency Swept Rotating Input Perturbation Techniques and Identification of the Fluid Force Models in Rotor/bearing/seal Systems and Fluid Handling Machines

Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.

Muszynska, Agnes↗

TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging

Purpose: We have previously described the development and testing of a coherent-scatter spectral imaging system for identification of cancer. Our prior evaluations were performed using either tissue surrogate phantoms or formalin-fixed tissue obtained from pathology. Here we present the first results from a scatter imaging study using fresh breast tumor tissues obtained through surgical excision. Methods: A coherent-scatter imaging system was built using a clinical X-ray tube, photon counting detectors, and custom-designed coded-apertures. System performance was characterized using calibration phantoms of biological materials. Fresh breast tumors were obtained from patients undergoing mastectomy and lumpectomy surgeries for breast cancer. Each specimen was vacuum-sealed, scanned using the scatter imaging system, and then sent to pathology for histological workup. Scatter images were generated separately for each tissue specimen and analyzed to identify voxels containing malignant tissue. The images were compared against histological analysis (H&E + pathologist identification of tumors) to assess the match between scatter-based and histological diagnosis. Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2–3 mm, and the total scan time for each specimen was under 15 minutes. Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It presents the first results from coherent scatter imaging of fresh (unfixed) breast tissue using our coded-aperture scatter imaging approach for cancer identification.

60 APPLIED LIFE SCIENCES↗

A reliable dual-redundant sensor FDI system for the NASA F8C-DFBW aircraft

In this paper we outline the structure of a sensor failure detection and identification (FDI) system designed for the NASA F8C DFBW aircraft. The system is for use in a dual-redundant environment, and it takes maximal advantage of all functional and kinematic relationships among the sensed variables. The technique is reliable in that we have designed the system to account for a variety of unmodeled effects and have introduced a new concept - the quality sequential probability ratio (QSPR) - that provides a useful measure of our confidence in each test. The methodology used for determining detector parameters and the 'outer loop logic' for combining the various sources of information are described.

Deckert, J. C.↗

Star Identification Using a Triplet Algorithm

The stars observed by onboard star trackers must be identified in order for the star tracker information to be used for attitude determination. Star identification associates the observed stars in the body frame with catalog stars, the positions of which in an inertial frame are well known. If the attitude is approximately known (from less accurate sensors) identification is relatively simple, but if there is no prior attitude knowledge (the Lost in Space problem) star identification is quite difficult. A new, reliable, and accurate star identification algorithm has been developed for use in a batch, ground-based attitude determination system. The identification algorithm uses input from one or more star trackers, each of which can observe three or more stars simultaneously. If observations are available at different times, rate data is used to relate them. The algorithm includes the following steps that are automatically performed: 1) Observations are examined to determine the optimal set of simultaneous star observations in a single tracker. 2) The selected optimal observations are identified using a triplet match. 3) The identified stars in the selected tracker at the selected time are used to compute an attitude at that time. 4) The rate data is refined by determination of biases that minimize the dispersion of repeated observations of the same stars. 5) The refined rate data is used to propagate the attitude to the times of each star observation. 6) The attitude at each time is used to associate all stars observed at that time, in each tracker, with catalog stars. The overall algorithm is very dependable at producing accurate star identification with no initial attitude input.

Hashmall, Joseph A.↗

Antimicrobial Materials for Advanced Microbial Control in Spacecraft Water Systems

Microbial detection, identification, and control are essential for the maintenance and preservation of spacecraft water systems. Requirements set by NASA put limitations on the energy, mass, materials, noise, cost, and crew time that can be devoted to microbial control. Efforts are being made to attain real-time detection and identification of microbial contamination in microgravity environments. Research for evaluating technologies for capability enhancement on-orbit is currently focused on the use of adenosine triphosphate (ATP) analysis for detection purposes and polymerase chain reaction (peR) for microbial identification. Additional research is being conducted on how to control for microbial contamination on a continual basis. Existing microbial control methods in spacecraft utilize iodine or ionic silver biocides, physical disinfection, and point-of-use sterilization filters. Although these methods are effective, they require re-dosing due to loss of efficacy, have low human toxicity thresholds, produce poor taste, and consume valuable mass and crew time. Thus, alternative methods for microbial control are needed. This project also explores ultraviolet light-emitting diodes (UV-LEDs), surface passivation methods for maintaining residual biocide levels, and several antimicrobial materials aimed at improving current microbial control techniques, as well as addressing other materials presently under analysis and future directions to be pursued.

Birmele, Michele↗

Computer-aided design and distributed system technology development for large space structures

Proposed large space structures have many characteristics that make them difficult to analyze and control. They are highly flexible, with components mathematically modeled by partial differential equations or very large systems of ordinary differential equations. They have many resonant frequencies, typically low and closely spaced. Natural damping may be low and/or improperly modeled. Coupled with stringent operational requirements of orientation, shape control, and vibration suppression, and the inability to perform adequate ground testing, these characteristics present an unconventional identification and control design problem to the systems theorist. Some of the research underway within Langley's Spacecraft Control Branch, Guidance and Control Division aimed at developing theory and algorithms to treat large space structures systems identification and control problems is described. The research areas to be considered are computer-aided design algorithms, and systems identification and control of distributed systems.

Armstrong, Ernest S.↗

Learning-Based Real-Time Event Identification Using Rich Real PMU Data

A large-scale deployment of phasor measurement units (PMUs) that reveal the inherent physical laws of power systems from a data perspective enables an enhanced awareness of power system operation. However, the high-granularity and non-stationary nature of PMU data and imperfect data quality could bring great technical challenges for real-time system event identification. To address these challenges, this paper proposes a two-stage learning-based framework. In the first stage, a Markov transition field (MTF) algorithm is exploited to extract the latent data features by encoding temporal dependency and transition statistics of PMU data in graphs. Then, a spatial pyramid pooling (SPP)-aided convolutional neural network (CNN) is established to efficiently and accurately identify power events. The proposed method fully builds on and is also tested on a large real-world dataset from several tens of PMU sources (and the corresponding event logs), located across the U.S., with a time span of two consecutive years. We report the numerical results validate that our method has high identification accuracy while showing good robustness against poor data quality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification and control integration strategies

This paper describes an autonomous control concept for pointing and articulation of science instruments on the Eos (Earth observing system) NASA/NOAA platforms intended to be operational by the late 1990s. Key features of this concept include advanced control adaptation and tuning strategies which provide performance robustness over a wide range of system uncertainties and mission time criticality. System identification-control modification paradigms are synthesized to form an adaptation continuum over this extended regime of autonomous operations.

Milman, Mark↗

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.↗

The exotic helium variable PG 1346 + 082

The results of an extensive study of the blue object PG 1346 + 082, which is both a photometric and a spectroscopic variable, are presented. The system spans the B magnitude range 13.6-17.2, is brighter than m(pg) of about 14.0 roughly 74 percent of the time, and has a photometric quasi-period of four to five days. The rapid photometric flickering at minimum light is identified as the signature of mass transfer in a binary sytsem, and the He I emission at minimum light as indicating the presence of an accretion disk. The inability to detect high-energy X-rays, the absence of the high-excitation lines of He II in the optical spectrum, and the complete absence of hydrogen in the spectrum show that PG 1346 + 082 is an interacting binary white dwarf system. This identification lends strong support to the interacting twin-degenerate interpretation for AM CVn. The outbursts of the system may be similar in physical origin to dwarf novae outbursts.

Wood, M. A.↗

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Evaluation Studies↗

Verification and Validation of Safety-Critical Aircraft Systems Operating under Off-Nominal, Contingency, and Emergency Conditions

Verification and validation (V&V) of safety-critical technologies developed for loss of control (LOC) prevention and recovery and other aviation safety concerns pose significant challenges. Aircraft LOC can result from a wide spectrum of hazards, often occurring in combination, which cannot be fully replicated during evaluation. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of hazardous and uncertain conditions, and the verification and validation of these technologies must provide some measure of assurance that the new vehicle safety technologies do no harm (i.e., that they themselves do not introduce new safety risks). V&V technologies must also enable the identification of system limitations and constraints, as well as enable the identification of safe and unsafe operating conditions (and their boundaries). Additionally, the V&V of complex, increasingly autonomous systems is a fundamental concern. Scalable, reproducible and cost-effective techniques for the assurance of safety critical systems during their design and operation is a key barrier to fielding new systems or updating current systems. Moreover, these techniques need to provide artifacts that enable a comprehensive evidence-based approach to certification. This briefing summarizes research performed under NASA’s Aviation Safety Program and follow-on research for the V&V of safety-critical aircraft system technologies developed for LOC prevention and recovery and increasingly autonomous systems, and for a broad assurance capability in both current and emerging aviation applications. Note that, in this briefing, the term “validation” refers to a confirmation that the system implementation (e.g., algorithms etc.) is performing the intended function(s), as well as an affirmation of effectiveness in these functions. “Verification” refers to a confirmation that the system implementation in the software and hardware meets its (hopefully validated) specifications (e.g., correctly executes algorithms as designed).

Validation↗

Anomaly Detection, Active Learning, Precursor Identification,and Human Knowledge for Autonomous System Safety

The project Autonomy Teaming and TRajectories for ComplexTrusted Operational Reliability (ATTRACTOR) researched and developed Artificial Intelligence with application to multi-Unmanned Aerial Systems (UAS) missions. Such missions, like other complex systems-of-systems, are likely to have previously-unknown, safety relevant anomalies occur due to many possible factors including system failures or degradations, emergent behavior, changes in the environment in which the systems operate, changes in the way the systems are operated. We discuss the application of anomaly detection, active learning, and precursor identification to identify such anomalies and the conditions under which they are more likely to appear. We demonstrate results on simulated multi-UAS missions that show promise to be applied to real missions.

machine learning↗

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CSPlib

This computational singular perturbation library (CSPlib) software is useful for analysis of chemical kinetic systems. The code is used to analyze and describe the dynamical landscape underlying the time evolution of a chemical system. Given a database of state vectors, it allows the analysis of the source term and Jacobian matrix of the chemical system, the identification and decoupling of fast and slow processes, and the analysis of cause-and-effect relationships in the coupled system dynamics. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2391 O

Najm, HabibN.↗

Verification and Validation of Performance with Dissemination of Best Practices in District Energy and CHP for Enhanced Resiliency, Energy Efficiency, and Cybersecurity

This report contains the results of the International District Energy Association’s work to analyze, validate, and verify performance data of existing district energy systems and identify industy best practices for the purpose of improving system reliability, resiliency, and efficiency, and to accellerate decarbonization. In addition to a technical evaluation of the surveyed systems and identification of a series of technical performance metrics, the report illustrates the accompanying operations and financial best practices employed by surveyed systems to fully serve their customer base. Additionally, the third chapter of the report describes the current landscape of cybersecurity threats and counteracting measures, and recommends a series of steps for effectively guarding highly networked district energy systems against cybersecurity attacks.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Assessment Study of the State of the Art in Adaptive Control and its Applications to Aircraft Control

Many papers relevant to reconfigurable flight control have appeared over the past fifteen years. In general these have consisted of theoretical issues, simulation experiments, and in some cases, actual flight tests. Results indicate that reconfiguration of flight controls is certainly feasible for a wide class of failures. However many of the proposed procedures although quite attractive, need further analytical and experimental studies for meaningful validation. Many procedures assume the availability of failure detection and identification logic that will supply adequately fast, the dynamics corresponding to the failed aircraft. This in general implies that the failure detection and fault identification logic must have access to all possible anticipated faults and the corresponding dynamical equations of motion. Unless some sort of explicit on line parameter identification is included, the computational demands could possibly be too excessive. This suggests the need for some form of adaptive control, either by itself as the prime procedure for control reconfiguration or in conjunction with the failure detection logic. If explicit or indirect adaptive control is used, then it is important that the identified models be such that the corresponding computed controls deliver adequate performance to the actual aircraft. Unknown changes in trim should be modelled, and parameter identification needs to be adequately insensitive to noise and at the same time capable of tracking abrupt changes. If however, both failure detection and system parameter identification turn out to be too time consuming in an emergency situation, then the concepts of direct adaptive control should be considered. If direct model reference adaptive control is to be used (on a linear model) with stability assurances, then a positive real or passivity condition needs to be satisfied for all possible configurations. This condition is often satisfied with a feedforward compensator around the plant. This compensator must be robustly designed such that the compensated plant satisfies the required positive real conditions over all expected parameter values. Furthermore, with the feedforward only around the plant, a nonzero (but bounded error) will exist in steady state between the plant and model outputs. This error can be removed by placing the compensator also in the reference model. Design of such a compensator should not be too difficult a problem since for flight control it is generally possible to feedback all the system states.

Kaufman, Howard↗

Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems

Here, the paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.

97 MATHEMATICS AND COMPUTING↗