Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CHECK”

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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Expanded Classification of Hepatitis C Virus Into 7 Genotypes and 67 Subtypes: Updated Criteria and Genotype Assignment Web Resource

The 2005 consensus proposal for the classification of hepatitis C virus (HCV) presented an agreed and uniform nomenclature for HCV variants and the criteria for their assignment into genotypes and subtypes. Since its publication, the available dataset of HCV sequences has vastly expanded through advancement in nucleotide sequencing technologies and an increasing focus on the role of HCV genetic variation in disease and treatment outcomes. The current study represents a major update to the previous consensus HCV classification, incorporating additional sequence information derived from over 1,300 (near-)complete genome sequences of HCV available on public databases in May 2013. Analysis resolved several nomenclature conflicts between genotype designations and using consensus criteria created a classification of HCV into seven confirmed genotypes and 67 subtypes. There are 21 additional complete coding region sequences of unassigned subtype. The study additionally describes the development of a Web resource hosted by the International Committee for Taxonomy of Viruses (ICTV) that maintains and regularly updates tables of reference isolates, accession numbers, and annotated alignments (http://talk.ictvonline.org/links/hcv/hcv-classification.htm). The Flaviviridae Study Group urges those who need to check or propose new genotypes or subtypes of HCV to contact the Study Group in advance of publication to avoid nomenclature conflicts appearing in the literature. While the criteria for assigning genotypes and subtypes remain unchanged from previous consensus proposals, changes are proposed in the assignment of provisional subtypes, subtype numbering beyond “w,” and the nomenclature of intergenotypic recombinant. Conclusion: This study represents an important reference point for the consensus classification of HCV variants that will be of value to researchers working in clinical and basic science fields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of “how well do we know our parameters, along with their uncertainties?.” The results reveal that Bayesian inversion statistical analysis on an example, prototype $\mathrm{lr(0)_n}$ nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. Importantly, the paper can also be seen as a tutorial with the additional goal of achieving a “Gold Standard” Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Macrophysical Properties of Tropical Cirrus Clouds from the CALIPSO Satellite and from Ground-based Micropulse and Raman Lidars

Lidar observations of cirrus cloud macrophysical properties over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Darwin, Australia site are compared from the Cloud-Aerosol Lidar and In- frared Pathfinder Satellite Observation (CALIPSO) satellite, the ground-based ARM micropulse lidar (MPL), and the ARM Raman lidar (RL). Comparisons are made using the subset of profiles where the lidar beam is not fully attenuated. Daytime measurements using the RL are shown to be relatively unaffected by the solar background and are therefore suited for checking the validity of diurnal cycles. RL and CALIPSO cloud fraction profiles show good agreement while the MPL detects significantly less cirrus, particularly during the daytime. Both MPL and CALIPSO observations show that cirrus clouds occur less frequently during the day than at night at all altitudes. In contrast, the RL diurnal cy- cle is significantly different than zero only below about 11 km; where it is the opposite sign (i.e. more clouds during the daytime). For cirrus geomet- rical thickness, the MPL and CALIPSO observations agree well and both datasets have signficantly thinner clouds during the daytime than the RL. From the examination of hourly MPL and RL cirrus cloud thickness and through the application of daytime detection limits to all CALIPSO data we find that the decreased MPL and CALIPSO cloud thickness during the daytime is very likely a result of increased daytime noise. This study highlights the vast im- provement the RL provides (compared to the MPL) in the ARM program's ability to observe tropical cirrus clouds as well as a valuable ground-based lidar dataset for the validation of CALIPSO observations and to help im- prove our understanding of tropical cirrus clouds.

Cirrus Clouds↗
DOE OSTI2013

Novel utilization of 3D technology and the hybrid operating theatre: Peri-operative assessment of posterior sterno-clavicular dislocation using cone beam CT

A patient with a medial and posterior dislocation of the right sterno-clavicular (SC) joint and displacement of the trachea and brachiocephalic artery by the medial head of the clavicle underwent general anaesthetic in the operating theatre for an open reduction procedure. The surgeon initially attempted a closed reduction, but this required imaging to check SC alignment. The patient was transferred to an adjacent hybrid operating theatre for imaging. Cone beam computed tomography (CBCT) was performed, which successfully demonstrated a significant reduction in the dislocation of the SC joint. The trachea and brachiocephalic artery were no longer compressed or displaced. This case study demonstrates an alternative to the patient being transferred to the medical imaging department for multi-slice CT. It also describes a novel use of the hybrid operating theatre and its CBCT capabilities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Placement of a peripherally inserted central catheter into the azygous vein

Peripherally inserted central catheters (PICC) are used for a variety of infusion therapies. They are indicated in patients requiring long-term venous access. Incorrect positioning of the insertion of a PICC line is one of the known complications when inserting the device in clinical practice. Radiographers once performing imaging will commonly check if the tip of a PICC has entered the superior vena cava. This case study will report on a lesser known incorrect placement of a PICC line into the azygous vein and how this can be detected on radiographic imaging. This outcome for the patient can be detrimental as it has an increased risk of perforation, thrombus, and fistula formation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Self-diagnosis of model suitability for continuous measurements of stream-dissolved organic carbon derived from in situ UV–visible spectroscopy

Application of high-frequency monitoring of dissolved organic carbon (DOC) is difficult in instances where training datasets are challenging to develop (e.g., remote locations) and the relationship between optical features and DOC concentration changes due to environmental or landscape shifts (e.g., climate or land-use change). We developed and compared three partial least squares (PLS) models using in situ water level measurements, conductivity, and UV–Vis spectral attenuation to predict DOC. Two site-specific models were developed using data from a hillslope-dominated forest or a low-relief wetland-pond-dominated stream catchment. The third model, using data from both sites, exhibited the best performance (DOC range = 4–15.5 mg C L −1 , mean = 8.38 mg C L −1 , training RMSE = 0.34 mg C L −1 , internal validation RMSE = 0.50 mg C L −1 , external validation RMSE = 2.43 mg C L −1 ). We further demonstrate using PLS model statistics to monitor performance and elucidate when and how models should be updated. These statistics, Hotelling's T 2 and squared prediction errors, are useful consistency checks for the predictions made and detect underlying inconsistencies that, if undetected, can reduce the robustness of DOC prediction. For example, via the T 2 statistic, we identified the summer–autumn transition as a period when DOC composition differed from what was represented in the training dataset. We also determined that elevated SUVA 254 values contributed to the overall bias observed in predictions made during the subsequent year as part of the external validation. This enabled the application of a bias correction that reduced the RMSE from 2.43 to 0.89 mg C L −1 . The method presented here could be applied to future monitoring programs enabling model updates to monitor DOC fluxes accurately from optical datasets (e.g., attenuance or fluorescence) in the face of developing datasets in remote locations or environmental change. In conclusion, implementation of this approach may also identify possible regime shifts or landscape and hydrologic change associated with climate and other environmental changes relevant to terrestrial to aquatic fluxes.

UV-VIS spectroscopy↗
DOE OSTI2018

Liquid metasurface‐based periodically stacked radome design

Abstract We present liquid metasurface‐based periodically stacked radome design. Radome is a layer placed above the antenna to protect it from weather disturbances. The layer protects the antenna but reduces its gain. Periodic stacking of liquid metasurface based radome improve the antenna parameters like gain and bandwidth. Microstrip patch antenna is used as basic antenna to check the improvement in gain. The comparison of microstrip patch antenna, patch antenna with simple multilayer radome, patch antenna with liquid metasurface multilayer radome and patch antenna with liquid metasurface periodically stacked multilayer radome is presented in the manuscript. The improvement in terms of gain is clearly visible from the comparison of results for all the designs. Efficiency is also increasing by adding liquid metasurface periodically stacked multilayer radome to patch antenna.

Patel, Shobhit K.↗
DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗
DOE OSTI2021

Toward efficient polynomial preconditioning for GMRES

Here, we present a polynomial preconditioner for solving large systems of linear equations. The polynomial is derived from the minimum residual polynomial (the GMRES polynomial) and is more straightforward to compute and implement than many previous polynomial preconditioners. Our current implementation of this polynomial using its roots is naturally more stable than previous methods of computing the same polynomial. We implement further stability control using added roots, and this allows for high degree polynomials. We discuss the effectiveness and challenges of root-adding and give an additional check for stability. In this article, we study the polynomial preconditioner applied to GMRES; however it could be used with any Krylov solver. This polynomial preconditioning algorithm can dramatically improve convergence for some problems, especially for difficult problems, and can reduce dot products by an even greater margin.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Anderson acceleration with approximate calculations: Applications to scientific computing

Here we provide rigorous theoretical bounds for Anderson acceleration (AA) that allow for approximate calculations when applied to solve linear problems. We show that, when the approximate calculations satisfy the provided error bounds, the convergence of AA is maintained while the computational time could be reduced. We also provide computable heuristic quantities, guided by the theoretical error bounds, which can be used to automate the tuning of accuracy while performing approximate calculations. For linear problems, the use of heuristics to monitor the error introduced by approximate calculations, combined with the check on monotonicity of the residual, ensures the convergence of the numerical scheme within a prescribed residual tolerance. Motivated by the theoretical studies, we propose a reduced variant of AA, which consists in projecting the least-squares used to compute the Anderson mixing onto a subspace of reduced dimension. The dimensionality of this subspace adapts dynamically at each iteration as prescribed by the computable heuristic quantities. We numerically show and assess the performance of AA with approximate calculations on: (i) linear deterministic fixed-point iterations arising from the Richardson's scheme to solve linear systems with open-source benchmark matrices with various preconditioners and (ii) non-linear deterministic fixed-point iterations arising from non-linear time-dependent Boltzmann equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2017

APT malware static trace analysis through bigrams and graph edit distance

Research and business organizations are vulnerable to attack by malware, particularly advanced persistent threat malware tailored for a specific target. Malware identification is made more difficult because samples can be subtly altered to avoid detection by methods that check for an identical match to known code. Different versions of an original piece of malware form a malware family. And when new malicious software is identified, reverse engineers seek to identify its origin and purpose. Knowing whether new malware is from a known family or a previously unobserved family aids the efficiency of reverse engineers. Furthermore, this article presents a three-stage method to classify new malware into a family by comparing its similarity to existing static traces, and assigning it to the most similar family. First, a fast filtering method creates a shortlist of samples with some similarity to the new malware, using a simple bigram comparison of the instructions. The second stage takes the call graph view of the shortlisted static traces and uses simulated annealing to estimate the graph edit distance, a measure of dissimilarity between graphs. Finally, a random forest classifier combines the previous two results to predict the family to which a new sample belongs. Our paper also considers how to detect when malware is from a new family.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

DisClose: Discovering Colossal Closed Itemsets via a Memory Efficient Compact Row-Tree

Itemset mining has recently focused on discovery of frequent itemsets from high-dimensional datasets with relatively few rows and a larger number of items. With exponentially in-creasing running time as average row length increases, mining such datasets renders most conventional algorithms impracti-cal. Unfortunately, large cardinality closed itemsets are likely to be more informative than small cardinality closed itemsets in this type of dataset. This paper proposes an approach, called DisClose, to extract large cardinality (colossal) closed itemsets from high-dimensional datasets. The approach relies on a memory-efficient Compact Row-Tree data structure to represent itemsets during the search process. The search strategy explores the transposed representation of the dataset. Large cardinality itemsets are enumerated first followed by smaller ones. In addition, we utilize a minimum cardinality threshold to further reduce the search space. Experimental result shows that DisClose can complete the extraction of colossal closed itemsets in the considered dataset, even for low support thresholds. The algorithm immediately discovers closed itemsets without needing to check if each new closed itemset has previously been found.

Zulkurnain, Nurul F.↗
DOE OSTI2013

A Similarity-Based Analysis Tool for Porting OpenMP Applications. In: Facing the Multicore-Challenge III. Lecture Notes in Computer Science, vol 7686.

Exascale computers are expected to exhibit an unprecedented level of complexity, thereby posing significant challenges for porting applications to these new systems. One of the ways to support this transition is to create tools that allow their users to benefit from prior successful porting experiences. The key to such an approach is the manner in which we define source code similarity, and whether similar codes can be ported in the same way to a given system. In this paper, we propose a novel approach based on the notion of similarity that uses static and dynamic code features to check if two serial subroutines can be ported with the same OpenMP strategy. Our approach creates an annotated family distance tree based on the syntactic structure of subroutines, where subroutines that belong to the same syntactic family and share the similar code features have a greater potential to be optimized in the same way. We describe the design and implementation of a tool, based upon a compiler and performance tool, that is used to gather the data to build this porting planning tree. We then validate our approach by analyzing the similarity in subroutines of the serial version of the NAS benchmarks and comparing how they were ported in the OpenMP version of the suite.

Ding, Wei↗
DOE OSTI2015

Use of Combined Biogeochemical Model Approaches and Empirical Data to Assess Critical Loads of Nitrogen

Empirical and dynamic biogeochemical modelling are complementary approaches for determining the critical load (CL) of atmospheric nitrogen (N) or other constituent deposition that an ecosystem can tolerate without causing ecological harm. The greatest benefits are obtained when these approaches are used in combination. Confounding environmental factors can complicate the determination of empirical CLs across depositional gradients, while the experimental application of N amendments for estimating the CL does not realistically mimic the effects of chronic atmospheric N deposition. Biogeochemical and vegetation simulation models can provide CL estimates and valuable ecosystem response information, allowing for past and future scenario testing with various combinations of environmental factors, pollutants, pollutant control options, land management, and ecosystem response parameters. Even so, models are fundamentally gross simplifications of the real ecosystems they attempt to simulate. Empirical approaches are vital as a check on simulations and CL estimates, to parameterize models, and to elucidate mechanisms and responses under real world conditions. In this chapter, we provide examples of empirical and modelled N CL approaches in ecosystems from three regions of the United States: mixed conifer forest, desert scrub and pinyon- juniper woodland in California; alpine catchments in the Rocky Mountains; and lakes in the Adirondack region of New York state.

Fenn, Mark E.↗
DOE OSTI2015

Adjoint BFKL at finite coupling: a short-cut from the collinear limit

In the high energy Regge limit, the six gluons scattering amplitude is controlled by the adjoint BFKL eigenvalue and impact factor. In this paper we determine these two building blocks at any value of the ’t Hooft coupling in planar N=4 SYM theory. This is achieved by means of analytic continuations from the collinear limit, where similar all loops expressions were recently established. We check our predictions against all available data at weak and strong coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Helicity evolution at small x

Here, we construct small-x evolution equations which can be used to calculate quark and anti-quark helicity TMDs and PDFs, along with the g 1 structure function. These evolution equations resum powers of α s ln 2 (1/x) in the polarization-dependent evolution along with the powers of α s ln(1/x) in the unpolarized evolution which includes saturation effects. Moreover, the equations are written in an operator form in terms of polarization-dependent Wilson line-like operators. While the equations do not close in general, they become closed and self-contained systems of non-linear equations in the large-N c and large-N c & N f limits. Finally, as a cross-check, in the ladder approximation, our equations map onto the same ladder limit of the infrared evolution equations for the g 1 structure function derived previously by Bartels, Ermolaev and Ryskin.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗