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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗
DOE OSTI2025

Indicators of carbon alteration (ICAs) suggest patterns in reservoir methane emissions

Reservoir operations influence emissions via multiple causal pathways. In this paper, we quantify indicators of carbon alteration (ICAs) focused on methane. ICAs were chosen to reflect the potential for methane emission along four causal pathways: 1) water column mixing, 2) wet-dry cycles in sediment, 3) sediment redistribution, and 4) vegetation. We developed algorithms to calculate ICAs for three reservoirs along a longitudinal gradient in the Tennessee River basin of the southeast US. The ICAs revealed interesting longitudinal patterns. Indicators of both methane production and destruction increased downstream. The potential for ebullitive methane emissions driven by sub-daily water level fluctuations and emissions mediated by vegetation were higher in downstream mainstem reservoirs than in the upstream tributary reservoir. Along the remaining two pathways, longitudinal patterns were equivocal (sediment pathway) or suggested decreased emissions downstream (water-column mixing). We also observed seasonal patterns and, by combining ICAs, inferred times when ramping could be achieved with lower risk of emissions. The ICAs demonstrated here are the first step in quantifying mechanistic relationships between reservoir operation and methane emissions. In future, they may lead to improved operations in reservoir cascades and regional-scale estimates of emissions that account for differences among reservoirs.

Greenhouse gases↗
NASA NTRS2009

Kurtosis Approach to Solution of a Nonlinear ICA Problem

An algorithm for solving a particular nonlinear independent-component-analysis (ICA) problem, that differs from prior algorithms for solving the same problem, has been devised. The problem in question of a type known in the art as a post nonlinear mixing problem is a useful approximation of the problem posed by the mixing and subsequent nonlinear distortion of sensory signals that occur in diverse scientific and engineering instrumentation systems.

Duong, Vu↗
NASA NTRS2000

Charge Detector for the Imaging Calorimeter for ACCESS (ICA)

NASA's Advanced Cosmic Ray Experiment for the Space Station (ACCESS) Mission is planned to consist of a transition radiation detector (TRD) and a thin ionization calorimeter. In order to measure the charge of the primary cosmic ray, it is necessary for the calorimeter to have its own charge detector. Silicon detectors are chosen for the charge detector because of their excellent resolution, small size and nearly square shape. Monte Carlo simulations are performed to find the probability of misidentifying protons as alpha particles due to backscattered radiation from the calorimeter. Simulations were also used to investigate identifying primary cosmic rays that fragmented in the TRD before reaching the calorimeter. For this study algorithms have been developed for determining a direction of the core shower in the calorimeter. These algorithms are used to find the approximate location of the primary particle in the silicon detectors. Results show the probability to misidentify the charge depends upon the energy and direction of the primary particles.

Lee, Jeongin↗
DOE OSTI2024

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗
NASA NTRS2001

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

Non-NASA Center↗
NASA NTRS2021

An Efficient and Accurate Algorithm for Computing Grid-Averaged Solar Fluxes for Horizontally Inhomogeneous Clouds

A computationally efficient method is presented to account for the horizontal cloud inhomogeneity by using a radiatively equivalent plane parallel homogeneous (PPH) cloud. The algorithm can accurately match the calculations of the reference (rPPH) independent column approximation (ICA) results, but use only the same computational time required for a single plane parallel computation. The effective optical depth of this synthetic sPPH cloud is derived by exactly matching the direct transmission to that of the inhomogeneous ICA cloud. The ffective9 scattering asymmetry factor is found from a pre-calculated albedo inverse look-up-table that is allowed to vary over the range from -1.0 to 1.0. In the special cases of conservative scattering and total absorption, the synthetic method is exactly equivalent to the ICA, with only a small bias (about 0.2% in flux) relative to ICA due to imperfect interpolation in using the look-up tables. In principle, the ICA albedo can be approximated accurately regardless of cloud inhomogeneity. For a more complete comparison, the broadband shortwave albedo and transmission calculated from the synthetic sPPH cloud and averaged over all incident directions, have the RMS biases of 0.26% and 0.76%, respectively, for inhomogeneous clouds over a wide variation of particle size. The advantages of the synthetic PPH method are that (1) it is not required that all the cloud subcolumns have uniform microphysical characteristic, (2) it is applicable to any 1D radiative transfer scheme, and (3) it can handle arbitrary cloud optical depth distributions and an arbitrary number of cloud subcolumns with uniform computational efficiency.

cloud inhomogeneity↗
DOE OSTI2022

Transfer Learning-Based Independent Component Analysis

Understanding the underlying component structure is crucial for multivariate signal analysis. Among all the techniques that try to learn the latent structure, independent component analysis (ICA) is one of the most important and popular methods, which aims to extract independent components from multivariate signals and enables further analysis. For example, in electroencephalogram (EEG) analysis, artifacts filtering and disease detection are conducted based on the independent components of the signals. One critical challenge in existing ICA approaches is that the component extraction accuracy may degrade when the available data of a unit are limited. To address this issue, this paper proposes a transfer learning-based ICA method by innovatively transferring component distribution from a source domain, so that accurate component extraction results can be achieved even when only limited data are available in the target domain. To the best of our knowledge, this is the first work that leverages transfer learning to improve ICA accuracy with limited available data. In particular, we first extract all the independent components from the source domain by maximizing the log-likelihood function with a Newton-like method on a smooth manifold. Then for the target domain, the component with the largest negentropy is extracted in each round. To effectively leverage the knowledge from the source domain and to prevent the negative transfer, we try to find a component in the source domain that matches the component we are extracting. The probability density function of the matched component will then be used to improve the component extraction accuracy if such matched component can be found; otherwise, no knowledge will be transferred. Finally, numerical simulations and a case study with electrocardiogram (ECG) data are conducted, showing the effectiveness of the proposed method in transferring knowledge and reducing negative transfer.

42 ENGINEERING↗
NASA NTRS2000

Imaging Calorimeter for ACCESS Simulations with GEANT/FLUKA

Imaging Calorimeter for ACCESS (ICA) is a candidate of the calorimeter for the NASA's ACCESS program. The ICA studies the origin and acceleration mechanism of cosmic rays by measuring the elemental composition of the cosmic rays in the energy up to 10(exp 16) eV. For the past year, Monte Carlo simulation study for the ICA has been conducted to predict the detector performance and to design the system for match the scientific objectives. Simulation results show that the detector response resembles a Gaussian distribution and the energy resolution with ICA can be achieved about 40%. In addition, simulations of the detector's response to an assumed bent power law spectra in the region where the knee occurs have been conducted and clearly show that this detector can provide sufficiently accurate estimates of the spectral parameters that are a science goal of ACCESS.

Lee, Jeongin↗
NASA NTRS2000

A natural basis for efficient brain-actuated control

The prospect of noninvasive brain-actuated control of computerized screen displays or locomotive devices is of interest to many and of crucial importance to a few 'locked-in' subjects who experience near total motor paralysis while retaining sensory and mental faculties. Currently several groups are attempting to achieve brain-actuated control of screen displays using operant conditioning of particular features of the spontaneous scalp electroencephalogram (EEG) including central mu-rhythms (9-12 Hz). A new EEG decomposition technique, independent component analysis (ICA), appears to be a foundation for new research in the design of systems for detection and operant control of endogenous EEG rhythms to achieve flexible EEG-based communication. ICA separates multichannel EEG data into spatially static and temporally independent components including separate components accounting for posterior alpha rhythms and central mu activities. We demonstrate using data from a visual selective attention task that ICA-derived mu-components can show much stronger spectral reactivity to motor events than activity measures for single scalp channels. ICA decompositions of spontaneous EEG would thus appear to form a natural basis for operant conditioning to achieve efficient and multidimensional brain-actuated control in motor-limited and locked-in subjects.

NASA Discipline Space Human Factors↗
NASA NTRS2018

Initial Criticality Assessments to Guide FMEAs on Rocket Engine Hot Fire Testing

Presented is an explanation of the use of the Initial Criticality Assessment (ICA) technique, a triage process for prioritizing required Failure Modes and Effects Analysis (FMEAs), for the European Service Module's main propulsion system's hot-fire test bed at White Sands New Mexico. Rather than instinctively performing many FMEAs of subsystems, or one large system level FMEA where every subcomponent is analyzed, the ICA guided an informed analysis of only the hardware that had a large impact to hazards. The low criticality hardware was documented via the ICA and no FMEA was performed; the work could then focus on the high criticality hardware. Thus a savings of Program resources was achieved. The experiences gained in creating these ICAs for this international collaborative project confirmed that the need for continuous communication across the technical teams is one of the greatest areas of emphasis. The European Space Agency (ESA) is developing the European Service Module (ESM), with its primary contractor, Airbus Defence and Space in Germany, for delivery to the National Aeronautics and Space Administration (NASA). The module will be equipped with a total of 21 engines to support NASA’s Orion spacecraft: one U.S. Space Shuttle Orbital Maneuvering System-Engine (OMS-E), eight auxiliary thrusters and 12 smaller RCS (Reaction Control System) thrusters. The main ESM propulsion system, used for large translational maneuvers, consists of one OMS-E... To qualify the design of the ESM propulsion subsystem (PSS) an all-steel Propulsion Qualification Module (PQM) structure is used to test the propulsion systems on Orion, including “hot firing” of the OMS engine, thrusters, and RCS. The PQM has been developed as a hot-fire test bed to be tested at the NASA White Sands Test Facility (WSTF). One of the objectives of the testing is to assure that the OMS-E can be safely operated with the PQM. Testing will also demonstrate that the PQM can set the proper upstream pressures and temperatures for the OMS-E to operate nominally given the PQM has never been tested in hot-fire operation with OMS-E before. In order to safely conduct the test campaign, hardware such as the engine subassembly, fluid feed lines, valves, electrical power lines, instrumentation, stiff links, installation Ground Support Equipment (GSE), and diffuser [whose objectives are to collect the exhaust of the OMS-E to actively cool down the exhaust gases, reduce thermal exchanges, and create a vacuum at OMS-E level before igniting], had to be analyzed for any hazards and failure modes.

Fault Tolerance↗
NASA NTRSDate not supplied

Intracranial Effects of Artificial Gravity: A 3T MRI Study

INTRODUCTION Spaceflight associated neuro-ocular syndrome (SANS) is characterized by the development of optic disc edema, posterior globe flattening, choroidal/retinal folds and hyperopic refractive errors1. SANS is hypothesized to be a result of headward fluid shifts that invariably occurs in the microgravity environment. As a countermeasure, artificial gravity (AG) through centrifugation has been proposed to reduce this headward fluid shift, however there is no current proof of benefit. The goal of this study was to determine if the application of AG can prevent or reduce known changes in brain volumetry, internal carotid artery (ICA) stroke volume and cerebral spinal fluid (CSF) flow velocity that occurs during simulated chronic headward fluid shift using head down tilt bed rest (HDTBR) methodology2 as an indicator of countermeasure efficacy. METHODS Healthy volunteers were recruited for an IRB approved HDTBR study performed at the German Aerospace Center in Cologne, Germany. Strict six-degree HDTBR was used as a spaceflight analog to induce a continuous headward fluid shift. HDTBR was carried out for 60 days for all subjects. Short-arm centrifugation was utilized to generate AG equating to ~0.3g of acceleration at the level of the eye. The subjects were divided equally into three groups: NoAG (control; n=8), daily intermittent AG (6 x 5 min iAG; n=8), and daily continuous 30 min (cAG; n=8). All studies were performed on a single dedicated 3T MRI Scanner. Pulse-gated MRI phase-contrast flow imaging was used to quantify ICA stroke volume and peak-to-peak CSF flow velocity in the mid cerebral aqueduct. 3D-SPGR was acquired for volumetric segmentation of the brain and CSF spaces. MRI acquisitions were obtained at baseline (BDC), 14 days into HDTBR (HDTBR14), 52 days into HDTBR (HDTBR52) and 3-5 days after HDTBR (recovery, R+3/5).The data were analyzed by the mixed model, which included intervention and time (BDC, HDTBR 14, HDTBR 52, R+3/5) as the fixed effects and included subject as the random effect.RESULTS24 healthy subject volunteers (16 men, 8 women, mean age = 33 years ± 9 [standard deviation] and mean BMI = 24.3 kg/m2 ± 2.0) successfully completed all phases of the study. Strict six-degree HDTBR was characterized by progressive and statistically significant (p<.01) increases in mean combined brain and CSF volumes and mean aqueductal CSF peak-to-peak flow velocity, as well as statistically significant (p<.01) progressive decrease in mean ICA stroke volume from baseline to 52 days post intervention (Figs. 1-3). Compared to baseline, only combined brain and CSF volumes did not return to baseline values in the recovery period (p=NS). Neither iAG nor cAG exerted any significant effects on the measured MRI brain parameters as compared to HDTBR alone (p=NS). CONCLUSION Our results indicate that HDTBR at 6-degrees was effective in producing alterations in ICA stroke volume, aqueductal CSF flow velocity, and combined brain and CSF volumetric change that is associated with chronic headward fluid shift. Short duration, 30-min daily exposure to either iAG or cAG appears to be insufficient in preventing or reducing the effects of chronic HDTBR and thus may not be a suitable countermeasure as currently deployed. AG protocol modifications, including increased duration and magnitude of exposure, should be considered for future research.

L A Kramer↗
DOE OSTI2024

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Implementing nonlinear optics from Off-Energy closed orbit at NSLS-II

To characterize the second-order (chromatic sextupole) magnet lattice with high precision, we implemented nonlinear optics from off-energy closed orbit (NOECO) tool based on the linear optics from closed orbit modulation (LOCOM) method, named LOCOM-NOECO. The preliminary numerical study indicates that 1–2% precision can be achieved for the calibration of chromatic sextupoles. Further, this accuracy could potentially help in resolving some long-standing challenges of NSLS-II (e.g., the discrepancy between the designed and measured dynamic apertures) if such high precision can be fulfilled. As an independent crosscheck, we also implemented NOECO based on the independent component analysis (ICA) method using turn-by-turn (TBT) BPM data, named ICA-NOECO. Both ICA-NOECO and LOCOM-NOECO have been successfully applied to identify the pre-dialed random errors of a chromatic sextupole family including five power supplies, and achieved the root mean square (RMS) residual error of 1% and peak error less than 2%. Moreover, to mitigate the chromatic sextupole error effect, we applied the correction and achieved significant improvements in the injection efficiency as well as the dynamic apertures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1987

Development of tailorable advanced blanket insulation for advanced space transportation systems

Two items of Tailorable Advanced Blanket Insulation (TABI) for Advanced Space Transportation Systems were produced. The first consisted of flat panels made from integrally woven, 3-D fluted core having parallel fabric faces and connecting ribs of Nicalon silicon carbide yarns. The triangular cross section of the flutes were filled with mandrels of processed Q-Fiber Felt. Forty panels were prepared with only minimal problems, mostly resulting from the unavailability of insulation with the proper density. Rigidizing the fluted fabric prior to inserting the insulation reduced the production time. The procedures for producing the fabric, insulation mandrels, and TABI panels are described. The second item was an effort to determine the feasibility of producing contoured TABI shapes from gores cut from flat, insulated fluted core panels. Two gores of integrally woven fluted core and single ply fabric (ICAS) were insulated and joined into a large spherical shape employing a tadpole insulator at the mating edges. The fluted core segment of each ICAS consisted of an Astroquartz face fabric and Nicalon face and rib fabrics, while the single ply fabric segment was Nicalon. Further development will be required. The success of fabricating this assembly indicates that this concept may be feasible for certain types of space insulation requirements. The procedures developed for weaving the ICAS, joining the gores, and coating certain areas of the fabrics are presented.

Calamito, Dominic P.↗
NASA NTRS2000

Imaging Calorimeter for ACCESS Simulations with GEANT/FLUKA

Imaging Calorimeter for ACCESS (ICA) is a candidate of the calorimeter for the NASA's ACCESS program to be flown on the International Space Station. The ICA studies the origin and acceleration mechanism of cosmic rays by measuring the elemental composition of the cosmic rays in the energy up to 10(exp 16) eV. For the past year, Monte Carlo simulation study for the ICA has been conducted using GEANT/FLUKA to predict the detector performance and to design the system for match the scientific objectives. Simulation results will be shown for the detector response and the energy resolution for various configurations.

Watts, John↗
NASA NTRS2001

An Imaging Calorimeter for Access-Concept Study

A mission concept study to define the "Advanced Cosmic-ray Composition Experiment for Space Station (ACCESS)" was sponsored by the National Aeronautics and Space Administration (NASA). The ACCESS instrument complement contains a transition radiation detector and an ionization calorimeter to measure tile spectrum of protons, helium, and heavier nuclei up to approximately 10(exp 15) eV to search for the limit of S/N shock wave acceleration, or evidence for other explanations of the spectra. Several calorimeter configurations have been studied, including the "baseline" totally active bismuth germanate instrument and sampling calorimeters utilizing various detectors. The Imaging Calorimeter for ACCESS (ICA) concept comprises a carbon target and a calorimeter using a high atomic number absorber sampled approximately each radiation length (rl) by thin scintillating fiber (SCIFI) detectors. The main features and options of the ICA instrument configuration are described in this paper. Since direct calibration is not possible over most of the energy range, the best approach must be decided from simulations of calorimeter performance extrapolated from CERN calibrations at 0.375 TeV. This paper presents results from the ICA simulations study.

Parnell, T. A.↗