Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Input Sensitivity”

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.

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

At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Early Oscillation Detection Technique for Hybrid DC/DC Converters

Oscillation or instability is a situation that must be avoided for reliable hybrid DC/DC converters. A real-time electronics measurement technique was developed to detect catastrophic oscillations at early stages for hybrid DC/DC converters. It is capable of identifying low-level oscillation and determining the degree of the oscillation at a unique frequency for every individual model of the converters without disturbing their normal operations. This technique is specially developed for space-used hybrid DC/DC converters, but it is also suitable for most of commercial and military switching-mode power supplies. This is a weak-electronic-signal detection technique to detect hybrid DC/DC converter oscillation presented as a specific noise signal at power input pins. It is based on principles of feedback control loop oscillation and RF signal modulations, and is realized by using signal power spectral analysis. On the power spectrum, a channel power amplitude at characteristic frequency (CPcf) and a channel power amplitude at switching frequency (CPsw) are chosen as oscillation level indicators. If the converter is stable, the CPcf is a very small pulse and the CPsw is a larger, clear, single pulse. At early stage of oscillation, the CPcf increases to a certain level and the CPsw shows a small pair of sideband pulses around it. If the converter oscillates, the CPcf reaches to a higher level and the CPsw shows more high-level sideband pulses. A comprehensive stability index (CSI) is adopted as a quantitative measure to accurately assign a degree of stability to a specific DC/DC converter. The CSI is a ratio of normal and abnormal power spectral density, and can be calculated using specified and measured CPcf and CPsw data. The novel and unique feature of this technique is the use of power channel amplitudes at characteristic frequency and switching frequency to evaluate stability and identify oscillations at an early stage without interfering with a DC/DC converter s normal operation. This technique eliminates the probing problem of a gain/phase margin method by connecting the power input to a spectral analyzer. Therefore, it is able to evaluate stability for all kinds of hybrid DC/DC converters with or without remote sense pins, and is suitable for real-time and in-circuit testing. This frequency-domain technique is more sensitive to detect oscillation at early stage than the time-domain method using an oscilloscope.

Wang, Bright L.↗
DOE OSTI2022

Laser Welded Edge Seals for Glass/Glass Modules

Polymers used in module construction are often involved in degradation mechanisms and hamper recycling. This project explores femtosecond (fs) laser welding of glass/glass modules to enable polymer-free modules. We are utilizing the knowledge base of the industrial laser community to apply glass/glass fs laser welding technology to solar modules. Experimentally measured stress intensity factors for glass welds are input into a COMSOL model of a full-size module to test weld failure under static loading. If successful, fs laser welding could enable modules that are polymer-free that will extend module warrantees, allow hermetically sealed glass/glass modules for moisture-sensitive semiconductors, and improve module recyclability.

COMSOL finite element model↗
DOE OSTI2025

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗
DOE OSTI2025

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗
NASA NTRS2011

Application of Temperature Sensitivities During Iterative Strain-Gage Balance Calibration Analysis

A new method is discussed that may be used to correct wind tunnel strain-gage balance load predictions for the influence of residual temperature effects at the location of the strain-gages. The method was designed for the iterative analysis technique that is used in the aerospace testing community to predict balance loads from strain-gage outputs during a wind tunnel test. The new method implicitly applies temperature corrections to the gage outputs during the load iteration process. Therefore, it can use uncorrected gage outputs directly as input for the load calculations. The new method is applied in several steps. First, balance calibration data is analyzed in the usual manner assuming that the balance temperature was kept constant during the calibration. Then, the temperature difference relative to the calibration temperature is introduced as a new independent variable for each strain--gage output. Therefore, sensors must exist near the strain--gages so that the required temperature differences can be measured during the wind tunnel test. In addition, the format of the regression coefficient matrix needs to be extended so that it can support the new independent variables. In the next step, the extended regression coefficient matrix of the original calibration data is modified by using the manufacturer specified temperature sensitivity of each strain--gage as the regression coefficient of the corresponding temperature difference variable. Finally, the modified regression coefficient matrix is converted to a data reduction matrix that the iterative analysis technique needs for the calculation of balance loads. Original calibration data and modified check load data of NASA's MC60D balance are used to illustrate the new method.

Ulbrich, N.↗
NASA NTRS1995

Feasibility of Coupling Between a Single-Mode Elliptical-Core Fiber and a Single Mode Rib Waveguide Over Temperature

To determine the feasibility of coupling the output of an optical fiber to a rib waveguide in a temperature environment ranging from 20 C to 300 C, a theoretical calculation of the coupling efficiency between the two was investigated. This is a significant problem which needs to be addressed to determine whether an integrated optic device can function in a harsh temperature environment. Because the behavior of the integrated-optic device is polarization sensitive, a polarization-preserving optic fiber, via its elliptical core, was used to couple light with a known polarization into the device. To couple light energy efficiently from an optical fiber into a channel waveguide, the design of both components should provide for well-matched electric field profiles. The rib waveguide analyzed was the light input channel of an integrated-optic pressure sensor. Due to the complex geometry of the rib waveguide, there is no analytical solution to the wave equation for the guided modes. Approximation or numerical techniques must be utilized to determine the propagation constants and field patterns of the guide. In this study, three solution methods were used to determine the field profiles of both the fiber and guide: the effective-index method (EIM), Marcatili's approximation, and a Fourier method. These methods were utilized independently to calculate the electric field profile of a rib channel waveguide and elliptical fiber at two temperatures, 20 C and 300 C. These temperatures were chosen to represent a nominal and a high temperature that the device would experience. Using the electric field profile calculated from each method, the theoretical coupling efficiency between the single-mode optical fiber and rib waveguide was calculated using the overlap integral and results of the techniques compared. Initially, perfect alignment was assumed and the coupling efficiency calculated. Then, the coupling efficiency calculation was repeated for a range of transverse offsets at both temperatures. Results of the calculation indicate a high coupling efficiency can be achieved when the two components were properly aligned. The coupling efficiency was more sensitive to alignment offsets in the y direction than the x, due to the elliptical modal profile of both components. Changes in the coupling efficiency over temperature were found to be minimal.

Tuma, Margaret L.↗
NASA NTRS2012

Modeling the Meteoroid Input Function at Mid-Latitude Using Meteor Observations by the MU Radar

The Meteoroid Input Function (MIF) model has been developed with the purpose of understanding the temporal and spatial variability of the meteoroid impact in the atmosphere. This model includes the assessment of potential observational biases, namely through the use of empirical measurements to characterize the minimum detectable radar cross-section (RCS) for the particular High Power Large Aperture (HPLA) radar utilized. This RCS sensitivity threshold allows for the characterization of the radar system s ability to detect particles at a given mass and velocity. The MIF has been shown to accurately predict the meteor detection rate of several HPLA radar systems, including the Arecibo Observatory (AO) and the Poker Flat Incoherent Scatter Radar (PFISR), as well as the seasonal and diurnal variations of the meteor flux at various geographic locations. In this paper, the MIF model is used to predict several properties of the meteors observed by the Middle and Upper atmosphere (MU) radar, including the distributions of meteor areal density, speed, and radiant location. This study offers new insight into the accuracy of the MIF, as it addresses the ability of the model to predict meteor observations at middle geographic latitudes and for a radar operating frequency in the low VHF band. Furthermore, the interferometry capability of the MU radar allows for the assessment of the model s ability to capture information about the fundamental input parameters of meteoroid source and speed. This paper demonstrates that the MIF is applicable to a wide range of HPLA radar instruments and increases the confidence of using the MIF as a global model, and it shows that the model accurately considers the speed and sporadic source distributions for the portion of the meteoroid population observable by MU.

Pifko, Steven↗
DOE OSTI2022

Autoencoders for semivisible jet detection

The production of dark matter particles from confining dark sectors may lead to many novel experimental signatures. Depending on the details of the theory, dark quark production in proton-proton collisions could result in semivisible jets of particles: collimated sprays of dark hadrons of which only some are detectable by particle collider experiments. The experimental signature is characterised by the presence of reconstructed missing momentum collinear with the visible components of the jets. This complex topology is sensitive to detector inefficiencies and mis-reconstruction that generate artificial missing momentum. With this work, we propose a signal-agnostic strategy to reject ordinary jets and identify semivisible jets via anomaly detection techniques. A deep neural autoencoder network with jet substructure variables as input proves highly useful for analyzing anomalous jets. The study focuses on the semivisible jet signature; however, the technique can apply to any new physics model that predicts signatures with anomalous jets from non-SM particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurements of multijet event isotropies using optimal transport with the ATLAS detector

A measurement of novel event shapes quantifying the isotropy of collider events is performed in 140 fb -1 of proton-proton collisions with $\sqrt{s}$ = 13 TeV centre-of-mass energy recorded with the ATLAS detector at CERN’s Large Hadron Collider. These event shapes are defined as the Wasserstein distance between collider events and isotropic reference geometries. This distance is evaluated by solving optimal transport problems, using the ‘Energy-Mover’s Distance’. Isotropic references with cylindrical and circular symmetries are studied, to probe the symmetries of interest at hadron colliders. The novel event-shape observables defined in this way are infrared- and collinear-safe, have improved dynamic range and have greater sensitivity to isotropic radiation patterns than other event shapes. The measured event-shape variables are corrected for detector effects, and presented in inclusive bins of jet multiplicity and the scalar sum of the two leading jets’ transverse momenta. The measured distributions are provided as inputs to future Monte Carlo tuning campaigns and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Field-to-farm gate greenhouse gas emissions from corn stover production in the Midwestern U.S.

Measured field data were used to compare two allocation methods on life cycle greenhouse gas emissions from corn (Zea mays L.) stover production in the Midwest U.S. We used publicly-available crop yield, nitrogen fertilizer, and direct soil nitrous oxide emissions data from the USDA-ARS Resilient Economic Agricultural Practices research program. Field data were aggregated from 9 locations across 26 site-years for 3 stover harvest rates (no removal; moderate removal – 3.1 Mg ha –1 ; high removal – 7.2 Mg ha –1 ) and 2 tillage practices (conventional; reduced/no-till). Net carbon uptake by crops was computed from measured plant carbon content. Monte Carlo simulations sampled input distributions to assess variability in farm-to-gate GHG emissions. The base analysis assumed no change in soil organic carbon stocks. In all cases, net CO 2 uptake during crop growth and soil-respired CO 2 dominated system emissions. Emissions were most sensitive to co-product accounting method, with system expansion emissions ~15% lower than mass allocation. Regardless of accounting method, lowest emissions occurred for a moderate removal rate under reduced/no-till management. The absence of correlations between N fertilization rate and stover removal rate or soil N 2 O emissions in this study challenges the use of such assumptions typically employed in life cycle assessments Storage of all carbon retained on the field as SOC could reduce emissions by an additional 15%. Furthermore, our results highlight how variability in GHG emissions due to location and weather can overshadow the impact of farm management practices on field-to-farm gate emissions. Graphical abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data

Atom probe tomography (APT) is a powerful technique to characterize buried 3D nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the DBSCAN algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the non-uniformity of the atomic density in the APT reconstruction itself (e.g. crystallographic poles and other field evaporation artifacts). The clustering results of DBSCAN-like method rely heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we present a new cluster analysis method consisting of a well-known algorithm, called OPTICS, and a cluster extraction algorithm we developed to enable accurate detection of clusters of varying atomic density in APT data. The new method requires only one free parameter, and other inputs can be estimated based on physical parameters of the material. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen. The method’s sensitivity with respect to parameter selection is discussed and compared with the current widely used methods.

atom probe tomography, cluster analysis, density-b↗
DOE OSTI2022

Assessing the Sensitivity of the Tropical Cyclone Boundary Layer to the Parameterization of Momentum Flux in the Community Earth System Model

Recent studies have demonstrated that high-resolution (~25 km) Earth System Models (ESMs) have the potential to skillfully predict tropical cyclone (TC) occurrence and intensity. However, biases in ESM TCs still exist, largely due to the need to parameterize processes such as boundary layer (PBL) turbulence. Building on past studies, we hypothesize that the depiction of the TC PBL in ESMs is sensitive to the configuration of the PBL parameterization scheme, and that the targeted perturbation of tunable parameters can reduce biases. The Morris one-at-a-time (MOAT) method is implemented to assess the sensitivity of the TC PBL to tunable parameters in the PBL scheme in an idealized configuration of the Community Atmosphere Model, version 6 (CAM6). The MOAT method objectively identifies several parameters in an experimental version of the Cloud Layers Unified by Binormals (CLUBB) scheme that appreciably influence the structure of the TC PBL. We then perturb the parameters identified by the MOAT method within a suite of CAM6 ensemble simulations and find a reduction in model biases compared to observations and a high-resolution, cloud-resolving model. Importantly, we demonstrate that the high-sensitivity parameters are tied to PBL processes that reduce turbulent mixing and effective eddy diffusivity, and that in CAM6 these parameters alter the TC PBL in a manner consistent with past modeling studies. In this way, we provide an initial identification of process-based input parameters that, when altered, have the potential to improve TC predictions by ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Search for Rare Processes: Mu2e and KOTO

The Standard Model (SM) of particle physics has been very successful in describing the fundamental forces, the properties of elementary particles, and predicting particles prior to their discovery, for example the top quark and the Higgs boson. Yet the SM does not explain all phenomena, and discoveries of physics processes beyond the SM will allow progress in our understanding of the fundamental nature of matter and forces. The search for rare processes is one of the paths to look for new physics. Two of these searches are for muon to electron conversion and the decay $\text{K}_\text{L}\rightarrow \pi^0 \nu \bar{\nu}$. Our main effort was in the Mu2e experiment under construction at Fermilab, which has the goal of searching for the neutrinoless conversion of a muon into an electron at a single event sensitivity of 2.87 x 10-17 and, in the process, provide evidence of physics processes beyond the Standard Model. We developed the firmware to be used in the Mu2e tracker readout, assisted in the construction and operation of the Mu2e Vertical Slice Test, and provided input to studies of cosmic event reconstructions in Mu2e using simulated data. Under this reward we also concluded our effort in two KOTO experiment in J-PARC, Japan and set a limit on the rate of the rare decay, $\text{K}_\text{L}\rightarrow \pi^0 \nu \bar{\nu}$ using the data collected in the 2016-2018 period. We also maintained and operated the DAQ system used for data collection thru 2021.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

Solar energy system economic evaluation for Solaron Akron, Akron, Ohio

The economic analysis of the solar energy system that was installed at Akron, Ohio is developed for this and four other sites typical of a wide range of environmental and economic conditions. The analysis is accomplished based on the technical and economic models in the f chart design procedure with inputs based on the characteristics of the installed parameters of present worth of system cost over a projected twenty year life: life cycle savings, year of positive savings and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables is also investigated. Results show that only in Albuquerque, New Mexico, where insolation is 1828 Btu/sq ft/day and the conventional energy cost is high, is this solar energy system marginally profitable.

Source record↗
NASA NTRS1980

Microwave remote sensing of soil moisture content over bare and vegetated fields

Remote measurements of soil moisture contents over bare fields and fields covered with orchard grass, corn, and soybean were made during October 1979 with 1.4 GHz and 5 GHz microwave radiometers mounted on a truck. Ground truth of soil moisture content, ambient air, and soil temperatures was acquired concurrently with the radiometric measurements. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperature data with appropriate values of dielectric constants for soil-water mixtures. Good agreement was found between the calculated and the measured results over 10-70 deg incident angles. The presence of vegetation was found to reduce the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from approximately 20% for 10-cm tall grassland to over 60% for the dense soybean field. At 5 GHz the corresponding reduction in sensitivity ranged from approximately 70 to approximately 90%.

Wang, J. R.↗
NASA NTRS1983

Optical measurements of a large-scale laboratory Beam Plasma Discharge (BPD)

Optical emission measurements provided information on the spatial distribution of energetic (primary and suprathermal) electrons producing the emissions; power dissipation during beam transit of the system; and modifications of the primary beam velocity distribution. The measurements were carried out for BPD's produced in a very large vacuum chamber using a 391.4 nm scanning photometer and total light (red sensitive) TV systems. Results for conditions Eb 500 to 2000 V, injection pitch angle 0 to 75 deg, and neutral density are presented. The typical power loss in ionization in transit of the 20 m pathlength during BPD is from 3 to 10% of the input power, an order of magnitude greater than attributable to collisional ionization alone. Differences between rocket observations and the laboratory results are noted.

Bernstein, W.↗
NASA NTRS1991

TRAC based sensing for autonomous rendezvous

The Targeting Reflective Alignment Concept (TRAC) sensor is to be used in an effort to support an Autonomous Rendezvous and Docking (AR&D) flight experiment. The TRAC sensor uses a fixed-focus, fixed-iris CCD camera and a target that is a combination of active and passive components. The system experiment is anticipated to fly in 1994 using two Commercial Experiment Transporters (COMET's). The requirements for the sensor are: bearing error less than or equal to 0.075 deg; bearing error rate less than 0.3 deg/sec; attitude error less than 0.5 deg.; and attitude rate error less than 2.0 deg/sec. The range requirement depends on the range and the range rate of the vehicle. The active component of the target is several 'kilo-bright' LED's that can emit 2500 millicandela with 40 milliwatts of input power. Flashing the lights in a known pattern eliminates background illumination. The system should be able to rendezvous from 300 meters all the way to capture. A question that arose during the presentation: What is the life time of the LED's and their sensitivity to radiation? The LED's should be manufactured to Military Specifications, coated with silicon dioxide, and all other space qualified precautions should be taken. The LED's will not be on all the time so they should easily last the two-year mission.

Everett, Louis J.↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗