SEARCH · Engineering Papers

Results for “critical mode detection”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

NASA NTRS1992

A monitor for the laboratory evaluation of control integrity in digital control systems operating in harsh electromagnetic environments

This paper presents a strategy for dynamically monitoring digital controllers in the laboratory for susceptibility to electromagnetic disturbances that compromise control integrity. The integrity of digital control systems operating in harsh electromagnetic environments can be compromised by upsets caused by induced transient electrical signals. Digital system upset is a functional error mode that involves no component damage, can occur simultaneously in all channels of a redundant control computer, and is software dependent. The motivation for this work is the need to develop tools and techniques that can be used in the laboratory to validate and/or certify critical aircraft controllers operating in electromagnetically adverse environments that result from lightning, high-intensity radiated fields (HIRF), and nuclear electromagnetic pulses (NEMP). The detection strategy presented in this paper provides dynamic monitoring of a given control computer for degraded functional integrity resulting from redundancy management errors, control calculation errors, and control correctness/effectiveness errors. In particular, this paper discusses the use of Kalman filtering, data fusion, and statistical decision theory in monitoring a given digital controller for control calculation errors.

Belcastro, Celeste M.↗

DOE OSTI2024

Two-fermion negativity and confinement in the Schwinger model

We consider the fermionic (logarithmic) negativity between two fermionic modes in the Schwinger model. Recent results pointed out that fermionic systems can exhibit stronger entanglement than bosonic systems, exhibiting a negativity that decays only algebraically. The Schwinger model is described by fermionic excitations at short distances, while its asymptotic spectrum is the one of a bosonic theory. We show that the two-mode negativity detects this confining, fermion-to-boson transition, shifting from an algebraic decay to an exponential decay at distances of the order of the de Broglie wavelength of the first excited state. We derive analytical expressions in the massless Schwinger model and confront them with tensor network simulations. We also perform tensor network simulations in the massive model, which is not solvable analytically, and close to the Ising quantum critical point of the Schwinger model, where we show that the negativity behaves as its bosonic counterpart. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗

DOE OSTI2022

To Fail or not to Fail: An Exploration of Machine Learning Techniques for Predictive Maintenance

Predictive maintenance refers to the ability to predict when machinery or systems need to be maintained. Making an accurate prediction is quite challenging given the costs for both over-estimating (unnecessary maintenance and reduction in availability of assets) and under-estimating (untimely breakdowns and possible loss of equipment or lives). To address these challenges researchers were able to develop new approaches for analyzing oil samples taken extracting samples from oil-wetted machinery that may provide information critical to developing predictive capabilities. We consider the problem from both supervised (though data limited) and unsupervised approaches and provide a first look into a data driven approach for identification of condition indicators. Through this work we identify a collection of candidate features that can form the basis of condition indicators for both a high level discrimination of failure vs. normal operation as well as a set for potential failure mode identification. Finally, we present an anomaly detection framework for detecting failures which can be a viable solution for an onboard analysis tool in deployed systems.

predictive maintenance, anomaly detection, Laserne↗

DOE OSTI2023

Nonlocal metasurface for circularly polarized light detection

Modern-day sensing and imaging applications increasingly rely on accurate measurements of the primary physical quantities associated with light waves: intensity, wavelength, directionality, and polarization. These are conventionally performed with a series of bulky optical elements, but recently, it has been recognized that optical resonances in nanostructures can be engineered to achieve selective photodetection of light waves with a specific set of predetermined properties. Here, we theoretically illustrate how a thin silicon layer can be patterned into a dislocated nanowire-array that affords detection of circularly polarized light with an efficiency that reaches the theoretical limit for circular dichroism of a planar detector in a symmetric external environment. The presence of a periodic arrangement of dislocations is essential in achieving such unparalleled performance as they enable selective excitation of nonlocal, guided-mode resonances for one handedness of light. We also experimentally demonstrate compact, high-performance chiral photodetectors created from these dislocated nanowire-arrays. This work highlights the critical role defects can play in enabling new nanophotonic functions and devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Through thick and thin: how optical cavities control spin

When light interacts with matter by means of scattering and absorption, we observe the resulting color. Light also probes the symmetry of matter and the result is encoded in its polarization. In the special case of circularly-polarized light, which is especially relevant in nonlinear optics, quantum photonics, and physical chemistry, a critical dimension of symmetry is along the longitudinal direction. We examine recent advances in controlling circularly-polarized light and reveal that the commonality in these advances is in judicious control of longitudinal symmetry. In particular, in the use of high quality-factor modes in dielectric metasurfaces, the finite thickness can be used to tune the modal profile. These symmetry considerations can be applied in multiplexed optical communication schemes, deterministic control of quantum emitters, and sensitive detection of the asymmetry of small molecules.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Altering Terahertz Sound Propagation in a Liquid upon Nanoparticle Immersion

One of the grand challenges of new generation Condensed Matter physicists is the development of novel devices enabling the control of sound propagation at terahertz frequency. Indeed, phonon excitations in this frequency window are the leading conveyor of heat transfer in insulators. Their manipulation is thus critical to implementing heat management based on the structural design. To explore the possibility of controlling the damping of sound waves, we used high spectral contrast Inelastic X-ray Scattering (IXS) to comparatively study terahertz acoustic damping in a dilute suspension of 50 nm nanospheres in glycerol and on pure glycerol. Bayesian inference-based modeling of measured spectra indicates that, at sufficiently large distances, the spectral contribution of collective modes in the glycerol suspension becomes barely detectable due to the enhanced damping, the weakening, and the slight softening of the dominant acoustic mode.

36 MATERIALS SCIENCE↗

NASA NTRS2004

Kinetic Roughening and Energetics of Tetragonal Lysozyme Crystal Growth: A Preliminary Atomic Force Microscopy Investigation

We examined particulars of crystal growth from measurements obtained at both microscopic and molecular levels. The crystal growth measurements performed at the microscopic level are well characterized by a model that balances the flux of macromolecules towards the crystal surface with the flux of the crystal surface. Numerical evaluation of model with measurements of crystal growth, in time, provided accurate estimates for the average growth velocities. Growth velocities thus obtained were also interpreted using well-established phenomenological theories. Moreover, we find that microscopic measurements of growth velocity measurements obtained as a function of temperature best characterizes changes in crystal growth modes, when present. We also examined the possibility of detecting a change in crystal growth modes at the molecular level using atomic force microscopy, AFM. From preliminary AFM measurements performed at various supersaturations, we find that magnitude of surface height fluctuations, h(x), increases with supersaturation. Further examination of surface height fluctuations using methods established for fluctuation spectroscopy also enabled the discovery of the existence of a characteristic length, c, which may possibly determine the mode of crystal growth. Although the results are preliminary, we establish the non- critical divergence of 5 and the root-mean-square (rms) magnitude of height-height fluctuations as the kinetic roughening transition temperatures are approached. Moreover, we also examine approximate models for interpreting the non-critical behavior of both 6 and rms magnitude of height-height fluctuations, as the solution supersaturation is increased towards the kinetic roughening supersaturation.

Gorti, Sridhar↗

DOE OSTI2024

Structural and phonon anomalies in the superconducting Bi 2 Sr 2 CaCu 2 O 8+σ with varying doping level at high pressures

Here we examined the effect of the lattice compression on the crystal structure of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductor with nearly optimally doped and overdoped composition using X-ray diffraction technique. Our studies show that at high pressures (up to 30 GPa ) the doping level does not affect the crystal structure of this superconductor. Along with this, structural anomalies in ratio appear at a pressure that corresponds to that at which T c begins to decrease. This fact indicates a close connection between the observed anomalies and superconductivity. We also studied the effect of doping and pressure on the T c (P) and on the Raman active lattice modes of the Bi 2 Sr 2 CaCu 2 O 8+σ superconductors. We find universal suppression of the T c by the pressure starting from the critical pressure P c in the range from 9 to 16 GPa, depending on the doping level of the Bi 2 Sr 2 CaCu 2 O 8+σ samples. Concomitantly, we observe phonon anomalies around 10 to 20 GPa, which indicate possible pressure-induced charge redistribution in BiO layers. These newly detected anomalies may be related to the changes in the electronic structure which compete with the superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Detecting fractionalization in critical spin liquids using color centers

Quantum spin liquids are highly entangled ground states of insulating spin systems, in which magnetic ordering is prevented down to the lowest temperatures due to quantum fluctuations. One of the most extraordinary characteristics of quantum spin liquid phases is their ability to support fractionalized, low-energy quasiparticles known as spinons, which carry spin-1/2 but bear no charge. Relaxometry based on color centers in crystalline materials—of which nitrogen-vacancy (NV) centers in diamond are a well-explored example—provides an exciting new platform to probe the spin spectral functions of magnetic materials with both energy and momentum resolution and to search for signatures of these elusive, fractionalized excitations. In this work, we theoretically investigate the color-center relaxometry of two archetypal quantum spin liquids: the two-dimensional U(1) quantum spin liquid with a spinon Fermi surface and the spin-1/2 antiferromagnetic spin chain. The former is characterized by a metallic, spin-split ground state of mobile, interacting spinons, which closely resembles a spin-polarized Fermi liquid ground state but with neutral quasiparticles. We show that the observation of the Stoner continuum and the collective spin wave mode in the spin spectral function would provide a strong evidence for the existence of spinons and fractionalization. In one dimension, mobile spinons form a Luttinger liquid ground state. We show that the spin spectral function exhibits strong features representing the collective density and spin-wave modes, which are broadened in an algebraic fashion with an exponent characterized by the Luttinger parameter. The possibilities of measuring these collective modes and detecting the power-law decay of the spectral weight using NV relaxometry are discussed. We also examine how the transition rates are modified by marginally irrelevant operators in the Heisenberg limit. Published by the American Physical Society 2024

Takei, So (ORCID:0000000191771895)↗

DOE OSTI2025

Neutron-Friendly Li-Ion Battery Coin Cell for In Situ 3D Visualization of Li Plating

Advanced battery characterization using in situ/operando neutron imaging is critical for uncovering degradation modes such as lithium (Li) plating in Li-ion batteries (LIBs). However, conventional LIBs hinder operando neutron radiography (NR) and in situ neutron micro-computed tomography (N-μCT) for visualizing Li plating near the graphite-separator interface due to strong attenuation from hydrogen-rich components like PP–PE–PP separators, electrolyte, and Fe-based spacers. In this work, we designed and tested a neutron-friendly battery (NFB) optimized for in situ Li detection during extreme fast charging (XFC). Guided by neutron attenuation cross-sections and material transmission, the NFB enables clear visualization at the graphite–separator interface, which is typically opaque in standard LIBs. Electrochemical tests show the NFB exhibits voltage/current responses like standard cells for up to 50 XFC cycles. However, its lower reversibility and capacity are likely due to Cu-coated Al spacer degradation from delamination or corrosion. We propose titanium spacers as a more stable alternative, albeit requiring custom machining. Using this optimized cell, we achieved simultaneous neutron tomography of multiple cells, capturing in situ 3D images of dead Li accumulation, particularly near graphite edges. These heterogeneous deposits and disconnected Li clusters suggest localized current density hotspots during XFC.

25 ENERGY STORAGE↗

DOE OSTI2022

Resonant acoustic monitoring of damage in plug‐screw feeders

Abstract Plug‐screw feeders are critical in many industrial processes for compressing slurry materials via a rotating plug‐screw feeder. Over time, increasing plug‐screw feeder wear will eventually lead to catastrophic mechanical failure. Early detection of the wear state can prevent unplanned catastrophic failures resulting in operational shut‐downs, costly repairs, and most importantly the health and safety of workers. We present a theoretical basis for a noninvasive, in operando acoustic resonant technique to monitor the wear state of plug‐screw feeders. The technique is based on tracking the resonant acoustic modes of the plug‐screw feeder, which are sensitive to the plug‐screw feeder geometry, material, and operating conditions. We implemented a multivariate polynomial model to estimate the plug‐screw feeder wear state using multiple acoustic resonances by simulating the acoustic resonant modes for two categories of wear (tip and thread damage) that are common in plug‐screw feeders. Fitting multiple resonances to the polynomial model, we demonstrate accurate estimation of the total mass loss, as well as characterization of the type of damage (i.e., tip vs. thread). Current approaches for monitoring plug‐screw feeder wear rely on shutting down the operation and visually inspecting the plug‐screw feeder. The presented acoustic technique offers a noninvasive, in operando measurement approach that mitigates unplanned catastrophic failures. The acoustic resonance technique presented in the paper has a broad range of industrial applications including the Pharmaceutical, Mining, Integrated Biorefineries (IBR), and Additive Manufacturing industries, to name a few.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Operando Infrared Nanospectroscopy of the Silicon/Electrolyte Interface during Initial Stages of Solid-Electrolyte-Interphase Layer Formation

The solid electrolyte interphase (SEI) is a critical component in Li-ion batteries; however, its nanoscale structure and composition and unstable nature make it difficult to characterize and ascertain primary functional mechanisms. We use operando nanoscale Fourier transform infrared spectroscopy (nano-FTIR) with a broadband synchrotron IR source to study the SEI formation on a thin-film Si electrode at nanometer-scale spatial resolution as a function of time and voltage. By probing the Si/carbonate electrolyte interface through a 25 nm-thick amorphous Si window/electrode, we detect molecular vibrational modes within a 10s of nanometers region adjacent to the Si surface and observe that PF6 – anions react to form LiF at 0.5 V. Spatially resolved nano-FTIR spectra showcase subtle nanoscale heterogeneities in the initial solid/liquid interface and the resulting deposited LiF. With its nanoscale resolution and high chemical specificity, operando nano-FTIR provides unique insights into the dynamics and heterogeneous formation of SEIs and opens opportunities for connecting nanoscale interfacial properties to bulk performance metrics.

Dopilka, Andrew↗

NASA NTRSDate not supplied

Decentralized and Asynchronous Planning for Cooperative Practices in High Altitude Digitally Enabled Operations

Cooperative practices will likely be foundational to future digitally enabled airspace operations characterized by decentralized and asynchronous decision-making. This paper explores the implementation of cooperative practices in high-altitude airspace. The digitally enabled operations framework, under exploratory investigation by NASA as a potential new operating mode, which is enabled and dependent on digital technologies and information sharing, may create new operational possibilities for a wide range of vehicle types and missions. An essential element of the operating mode framework under investigation, cooperative practices, could empower operators to manage critical functions such as deconfliction, equitable airspace usage, and demand-capacity balancing. The use of cooperative practices would involve asynchronous flight information sharing and decentralized conflict management by operators, representing a major change from traditional air traffic services that use synchronous surveillance information to support centralized decision-making by air traffic controllers. This paper details three key components for implementing cooperative practices for decentralized, digitally enabled operations: (a) intent modeling and sharing, (b) conflict detection, and (c) cooperative deconfliction.

cooperative operating practics↗

NASA NTRS2003

Detecting the Use of Intentionally Transmitting Personal Electronic Devices Onboard Commercial Aircraft

The need to detect unauthorized usage of intentionally transmitting portable electronic devices (PEDs) onboard commercial aircraft is growing, while still allowing passengers to use selected unintentionally transmitting devices, such as laptop computers and CD players during non-critical stages of flight. The following paper presents an installed system for detecting PEDs over multiple frequency bands. Additionally, the advantages of a fixed verses mobile system are discussed. While data is presented to cover the frequency range of 20 MHz to 6.5 GHz, special attention was given to the Cellular/PCS bands as well as Bluetooth and the FRS radio bands. Measurement data from both the semi-anechoic and reverberation chambers are then analyzed and correlated with data collected onboard a commercial aircraft to determine the dominant mode of coupling inside the passenger cabin of the aircraft versus distance from the source. As a final check of system feasibility, several PEDs transmission signatures were recorded and compared with the expected levels.

Woods, Randy↗

NASA NTRS2010

Estimation and Control for Autonomous Coring from a Rover Manipulator

A system consisting of a set of estimators and autonomous behaviors has been developed which allows robust coring from a low-mass rover platform, while accommodating for moderate rover slip. A redundant set of sensors, including a force-torque sensor, visual odometry, and accelerometers are used to monitor discrete critical and operational modes, as well as to estimate continuous drill parameters during the coring process. A set of critical failure modes pertinent to shallow coring from a mobile platform is defined, and autonomous behaviors associated with each critical mode are used to maintain nominal coring conditions. Autonomous shallow coring is demonstrated from a low-mass rover using a rotary-percussive coring tool mounted on a 5 degree-of-freedom (DOF) arm. A new architecture of using an arm-stabilized, rotary percussive tool with the robotic arm used to provide the drill z-axis linear feed is validated. Particular attention to hole start using this architecture is addressed. An end-to-end coring sequence is demonstrated, where the rover autonomously detects and then recovers from a series of slip events that exceeded 9 cm total displacement.

Hudson, Nicolas↗

DOE OSTI2024

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗

NASA NTRSDate not supplied

Systems Health Monitoring: Integrating FMEA into Bayesian Networks

The foreseeable high traffic density suggests that a large number of electric propulsion systems will enter the airspace, and that they will also operate at high frequency, e.g., large number of take offs and landings per unit time. The reliability of such critical systems is therefore key to ensure high safety standards in the low-altitude airspace. Diagnostic systems, which aim at identifying incipient faults, can mitigate unexpected failures or lower-than-expected reliability by performing early fault detection by monitoring the systems. A key element of fault diagnosis is fault detection and isolation (FDI), which complexity increases with the complexity of the system itself, namely the number of subsystems and components, interactions among sub-systems, and the number of sensors available. The proposed approach leverages combination of failure mode and effect analysis (FMEA) integrated with Bayesian networks, thus introducing dependability structures into a diagnostic framework to aid FDI. Faults and failure events from the FMEA are mapped within a Bayesian network, where network edges replicate the links embedded within FMEAs. The integrated framework enables the fault isolation process by identifying the probability of occurrence of specific faults or root causes given evidence observed through sensor signals. In this work, sub systems of Urban Air Mobility (UAM) type vehicle like avionics, structures, power-train etc. are taken into account to show the approach at the system level. This work integrates early design phase in the development of UAM type vehicles with diagnostic tools, which are often developed later in the product life-cycle, or retrofitted at a later time on systems. Failure mode and effect analysis (FMEA) derived for the system in the design phase is embedded within a Bayesian network (BN).

UAM↗