Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Identifiability”

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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Identifying build orientation of 3D-printed materials using convolutional neural networks

The advent of additive manufacturing (AM) processes brought with it intense research into various materials and manufacturing processes. At the same time, the need for validation of material properties, as well as study and forecasting of aging, has arisen. Modern imaging techniques, like X-ray computed tomography (XCT), are a convenient vehicle for such studies; however, the large datasets they produce require novel analysis techniques to efficiently extract critical information. Here, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars produced by AM. Using only information from XCT, our method achieves a 99.3% correct classification at a misidentification of 1%.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Using the CPTAC Assay Portal to identify and implement highly characterized targeted proteomics assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and post-translational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

An overview of methods to identify and manage uncertainty for modelling problems in the water-environment-agriculture cross-sector

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

How to identify different new neutrino oscillation physics scenarios at DUNE

Next generation neutrino oscillation experiments are expected to measure the remaining oscillation parameters with very good precision. They will have unprecedented capabilities to search for new physics that modify oscillations. DUNE, with its broad band beam, good particle identification, and relatively high energies will provide an excellent environment to search for new physics. If deviations from the standard three-flavor oscillation picture are seen however, it is crucial to know which new physics scenario is found so that it can be verified elsewhere and theoretically understood. We investigate several benchmark new physics scenarios by looking at existing long-baseline accelerator neutrino data from NOvA and T2K and determine at what sensitivity DUNE can differentiate among them. We consider sterile neutrinos and both vector and scalar non-standard neutrino interactions, all with new complex phases, the latter of which could conceivably provide absolute neutrino mass scale information. We find that, in many interesting cases, DUNE will have good model discrimination. We also perform a new fit to NOvA and T2K data with scalar NSI.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Anisotropic flow of identified particles in Pb-Pb collisions at $ {\sqrt{s}}_{\mathrm{NN}}=5.02 $ TeV

The elliptic (v 2 ), triangular (v 3 ), and quadrangular (v 4 ) flow coefficients of π ± , K ± , p+$ \overline{p}\ $,Λ+$ \overline{Λ}\ $,K S 0 , and the Φ-meson are measured in Pb-Pb collisions at $ {\sqrt{s}}_{\mathrm{NN}}=5.02 $ TeV. Results obtained with the scalar product method are reported for the rapidity range |y| < 0.5 as a function of transverse momentum, p T , at different collision centrality intervals between 0–70%, including ultra-central (0–1%) collisions for π ± , K ± , and p + $ \overline{p}\ $. For p T < 3 GeV/c, the flow coefficients exhibit a particle mass dependence. At intermediate transverse momenta (3 < p T < 8–10 GeV/c), particles show an approximate grouping according to their type (i.e., mesons and baryons). The Φ-meson v 2 , which tests both particle mass dependence and type scaling, follows p + $ \overline{p}\ $ v 2 at low p T and π ± v 2 at intermediate p T . The evolution of the shape of v n (p T ) as a function of centrality and harmonic number n is studied for the various particle species. Flow coefficients of π ± , K ± , and p + $ \overline{p}\ $ for p T < 3 GeV/c are compared to iEBE-VISHNU and MUSIC hydrodynamical calculations coupled to a hadronic cascade model (UrQMD). The iEBE-VISHNU calculations describe the results fairly well for p T < 2.5 GeV/c, while MUSIC calculations reproduce the measurements for p T < 1 GeV/c. A comparison to v n coefficients measured in Pb-Pb collisions at $ {\sqrt{s}}_{\mathrm{NN}}=2.76 $ TeV is also provided. [Figure not available: see fulltext.].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Anisotropic flow of identified hadrons in $\mathrm{X}$e-$\mathrm{X}$e collisions at $\sqrt{s_{NN}}$ = 5.44 $\mathrm{T}$e$\mathrm{V}$

Measurements of elliptic (v 2 ) and triangular (v 3 ) flow coefficients of π ± , K ± , $p+\bar{p}$, $K$$^{0}_{S}$, and $Λ+\bar{Λ}$ obtained with the scalar product method in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV are presented. The results are obtained in the rapidity range |y| < 0.5 and reported as a function of transverse momentum, p T , for several collision centrality classes. The flow coefficients exhibit a particle mass dependence for p T < 3 GeV/c, while a grouping according to particle type (i.e., meson and baryon) is found at intermediate transverse momenta (3 < p T < 8 GeV/c). The magnitude of the baryon v 2 is larger than that of mesons up to p T = 6 GeV/c. The centrality dependence of the shape evolution of the p T -differential v 2 is studied for the various hadron species. The v 2 coefficients of π ± , K ± , and $p+\bar{p}$ are reproduced by MUSIC hydrodynamic calculations coupled to a hadronic cascade model (UrQMD) for p T < 1 GeV/c. A comparison with v n measurements in the corresponding centrality intervals in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV yields an enhanced v 2 in central collisions and diminished value in semicentral collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

The complexity of identifying Ryu-Takayanagi surfaces in AdS 3 /CFT 2

Here, we present a constructive algorithm for the determination of Ryu-Takayanagi surfaces in AdS 3 /CFT 2 which exploits previously noted connections between holographic entanglement entropy and max-flow/min-cut. We then characterize its complexity as a polynomial time algorithm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1ß and IL-17 upregulation in alcoholic hepatitis mice.

Extracellular vesicles (EVs) have been growingly recognized as biomarkers and mediators of alcoholic liver disease (ALD) in human and mice. Here we characterized hepatocyte-derived EVs (HC-EVs) and their cargo for their biological functions in a novel murine model that closely resembles liver pathology observed in patients with alcoholic hepatitis (AH), the most severe spectrum of ALD. The number of circulating EVs and HC-EVs were significantly increased by 10-fold in AH mice compared to control mice. The miRNA(miR)-seq analysis detected 20 up-regulated and 4 down-regulated miRNAs (P < 0.001-0.05) in AH-HC-EVs. Treatment of murine primary hepatic stellate cells (HSCs) with AH-HC-EVs induced ?-SMA (P < 0.05) and Col1a1 (P < 0.001). Smad7, Nr1d2, and Rora genes which regulate HSC activation were predicted targets of 17 miRs up-regulated in AH-HC-EVs. Among them were miR-27a and miR-181 which upon transfection in HSCs, repressed Nr1d2, the HSC quiescence marker. AH-HC-EVs were also enriched in organelle proteins and mitochondrial DNA (10-fold, P < 0.05) and upregulated IL-1??and IL-17 production by hepatic macrophages (HMs) from AH mice in a TLR9-dependent manner. These results demonstrate HC-EV release is intensified in AH and suggest that AH-HC-EVs orchestrate liver fibrogenesis by directly targeting HSC quiescence transcripts via a unique set of miRNAs and by amplifying HSC activation via DAMP-based induction of profibrogenic IL-1? and IL-17 by HMs.

AH, hepatocyte-derived EVs, miRNAs, DAMPs, HSC act↗
DOE OSTI2018

Breaking the curse of dimensionality to identify causal variants in Breeding 4

In the past, plant breeding has undergone three major transformations and is currently transitioning to a new technological phase, Breeding 4. This phase is characterized by the development of methods for biological design of plant varieties, including transformation and gene editing techniques directed toward causal loci. The application of such technologies will require to reliably estimate the effect of loci in plant genomes by avoiding the situation where the number of loci assayed ($p$) surpasses the number of plant genotypes (n). Here, we discuss approaches to avoid this curse of dimensionality ($n\ll p$), which will involve analyzing intermediate phenotypes such as molecular traits and component traits related to plant morphology or physiology. Because these approaches will rely on novel data types such as DNA sequences and high-throughput phenotyping images, Breeding 4 will call for analyses that are complementary to traditional quantitative genetic studies, being based on machine learning techniques which make efficient use of sequence and image data. In this article, we will present some of these techniques and their application for prioritizing causal loci and developing improved varieties in Breeding 4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Identifying the Learning Curve for Uterine Artery Embolisation in an Interventional Radiological Training Unit

AimA clear understanding of operator experience is important in improving technical success whilst minimising patient risk undergoing endovascular procedures, and there is the need to ensure that trainees have the appropriate skills as primary operators. The aim of the study is to retrospectively analyse uterine artery embolisation (UAE) procedures performed by interventional radiology (IR) trainees at an IR training unit analysing fluoroscopy times and radiation dose as surrogate markers of technical skill.MethodsTen IR fellows were primary operator in 200 UAE procedures over a 5-year period. We compared fluoroscopy times, radiation dose and complications, after having them categorised according to three groups: Group 1, initial five, Group 2, >5 procedures and Group 3, penultimate five UAE procedures. We documented factors that may affect screening time (number of vials employed and use of microcatheters).ResultsMean fluoroscopy time was 18.4 (±8.1), 17.3 (±9.0), 16.3 (±8.4) min in Groups 1, 2 and 3, respectively. There was no statistically significant difference between these groups (p > 0.05) with respect to fluoroscopy time or radiation dose. Analysis after correction for confounding factors showed no statistical significance (p > 0.05). All procedures were technically successful, and total complication rate was 4 %.ConclusionUAE was chosen as a highly standardised procedure followed by IR practitioners. Although there is a non-significant trend for shorter screening times with experience, technical success and safety were not compromised with appropriate Consultant supervision, which illustrates a safe construct for IR training. This is important and reassuring information for patients undergoing a procedure in a training unit.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Low Cerebral Blood Volume Identifies Poor Outcome in Stent Retriever Thrombectomy

BackgroundMechanical thrombectomy (MT) is an efficient treatment of acute stroke caused by large-vessel occlusion. We evaluated the factors predicting poor clinical outcome (3-month modified Rankin Scale, mRS >2) although MT performed with modern stent retrievers.MethodsWe prospectively collected the clinical and imaging data of 105 consecutive anterior circulation stroke patients who underwent MT after multimodal CT imaging. Patients with occlusion of the internal carotid artery and/or middle cerebral artery up to the M2 segment were included. We recorded baseline clinical, procedural and imaging variables, technical outcome, 24-h imaging outcome and the clinical outcome. Differences between the groups were studied with appropriate statistical tests and binary logistic regression analysis.ResultsLow cerebral blood volume Alberta stroke program early CT score (CBV-ASPECTS) was associated with poor clinical outcome (median 7 vs. 9, p = 0.01). Lower collateral score (CS) significantly predicted poor outcome in regression modelling with CS = 0 increasing the odds of poor outcome 4.4-fold compared to CS = 3 (95% CI 1.27–15.5, p = 0.02). Lower CBV-ASPECTS significantly predicted poor clinical outcome among those with moderate or severe stroke (OR 0.82, 95% CI 0.68–1, p = 0.05) or poor collateral circulation (CS 0–1, OR 0.66, 95% CI 0.48–0.90, p = 0.009) but not among those with mild strokes or good collaterals.ConclusionsCBV-ASPECTS estimating infarct core is a significant predictor of poor clinical outcome among anterior circulation stroke patients treated with MT, especially in the setting of poor collateral circulation and/or moderate or severe stroke.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A groundwater salinity hotspot and its connection to an intermittent stream identified by environmental tracers (Mt Lofty Ranges, South Australia)

High and variable levels of salinity were investigated in an intermittent stream in a high-rainfall area (∼800 mm/year) of the Mt. Lofty Ranges of South Australia. The groundwater system was found to have a local, upslope saline lens, referred to here as a groundwater salinity ‘hotspot’. Environmental tracer analyses (δ{sup 18}O, δ{sup 2}H, {sup 87/86}Sr, and major elements) of water from the intermittent stream, a nearby permanent stream, shallow and deep groundwater, and soil-water/runoff demonstrate seasonal groundwater input of very saline composition into the intermittent stream. This input results in large salinity increases of the stream water because the winter wet-season stream flow decreases during spring in this Mediterranean climate. Furthermore, strontium and water isotope analyses demonstrate: (1) the upslope-saline-groundwater zone (hotspot) mixes with the dominant groundwater system, (2) the intermittent-stream water is a mixture of soil-water/runoff and the upslope saline groundwater, and (3) the upslope-saline-groundwater zone results from the flushing of unsaturated-zone salts from the thick clayey regolith and soil which overlie the metamorphosed shale bedrock. The preferred theory on the origin of the upslope-saline-groundwater hotspot is land clearing of native deep-rooted woodland, followed by flushing of accumulated salts from the unsaturated zone due to increased recharge. This cause of elevated groundwater and surface-water salinity, if correct, could be widespread in Mt. Lofty Ranges areas, as well as other climatically and geologically similar areas with comparable hydrogeologic conditions.

58 GEOSCIENCES↗
DOE OSTI2018

Application of multiple-isotope and groundwater-age data to identify factors affecting the extent of denitrification in a shallow aquifer near a river in South Korea

The extent of denitrification in a small agricultural area near a river in Yangpyeong, South Korea, was determined using multiple isotopes, groundwater age, and physicochemical data for groundwater. The shallow groundwater at one monitoring site had high concentrations of NO{sub 3}-N (74–83 mg L{sup −1}). The δ{sup 15}N-NO{sub 3} values for groundwater in the study area ranged between +9.1 and +24.6‰ in June 2014 and +12.2 to +21.6‰ in October 2014. High δ{sup 15}N-NO{sub 3} values (+10.7 to +12.5‰) in both sampling periods indicated that the high concentrations of nitrate in the groundwater originated from application of organic fertilizers and manure. In the northern part of the study area, some groundwater samples showed elevated δ{sup 15}N-NO{sub 3} and δ{sup 18}O-NO{sub 3} values, which suggest that nitrate was removed from the groundwater via denitrification, with N isotope enrichment factors ranging between −4.8 and −7.9‰ and O isotope enrichment factors varying between −3.8 and −4.9‰. Similar δD and δ{sup 18}O values of the surface water and groundwater in the south appear to indicate that groundwater in that area was affected by surface-water infiltration. The mean residence times (MRTs) of groundwater showed younger ages in the south (10–20 years) than in the north (20–30 years). Hence, it was concluded that denitrification processes under anaerobic conditions with longer groundwater MRT in the northern part of the study area removed considerable amounts of nitrate. This study demonstrates that multi-isotope data combined with physicochemical data and age-dating information can be effectively applied to characterize nitrate contaminant sources and attenuation processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗
DOE OSTI2019

Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways

Discrete fracture networks (DFN) are often used to model flow and transport in fractured porous media. The accurate resolution of flow and transport behavior on a large DFN involving thousands of fractures is computationally expensive. This makes uncertainty quantification studies of quantities of interest such as travel time through the network computationally intractable, since hundreds to thousands of runs of the DFN model are required to get bounds on the uncertainty of the predictions. Prior works on the subject demonstrated that the complexity of a DFN could be reduced by considering a sub-network of it (often termed a “backbone” sub-network), one whose flow and transport properties were then shown to be similar to that of the full network. The technique is tantamount to partitioning the complete set of fractures of a network into two disjoint sets, one of which is the backbone sub-network while the other its complement. It is in this context that we present a system-reduction technique for DFNs using supervised machine learning via a Random Forest Classifier that selects a backbone sub-network from the full set of fractures. The in-sample errors (in terms of precision and recall scores) of the trained classifier are found to be very accurate indicators of the out-of-sample errors, thus exhibiting that the classifier generalizes well to test data. Moreover, this system-reduction technique yields sub-networks as small as 12% of the full DFN that still recover transport characteristics of the full network such as the peak dosage and tailing behavior for late times. Most importantly, the sub-networks remain connected, and their size can be controlled by a single dimensionless parameter. Furthermore, measures of KL-divergence and KS-statistic for the breakthrough curves of the sub-networks with respect to the full network show physically realistic trends in that the measures decrease monotonically as the size of the sub-networks increase. In conclusion, the computational efficiency gained by this technique depends on the size of the sub-network, but large reductions in computational time can be expected for small sub-networks, yielding as much as 90% computational savings for sub-networks that are as small as 10-12% of the full network.

97 MATHEMATICS AND COMPUTING↗