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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.

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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Hyperspectral Imaging and SPA–LDA Quantitative Analysis for Detection of Colon Cancer Tissue

Hyperspectral imaging (HSI) has been demonstrated to provide a rapid, precise, and noninvasive method for cancer detection. However, because HSI contains many data, quantitative analysis is often necessary to distill information useful for distinguishing cancerous from normal tissue. To demonstrate that HSI with our proposed algorithm can make this distinction, we built a Vis–NIR HSI setup and made many spectral images of colon tissues, and then used a successive projection algorithm (SPA) to analyze the hyperspectral image data of the tissues. This was used to build an identification model based on linear discrimination analysis (LDA) using the relative reflectance values of the effective wavelengths. Other tissues were used as a prediction set to verify the reliability of the identification model. The results suggest that Vis–NIR hyperspectral images, together with the spectroscopic classification method, provide a new approach for reliable and safe diagnosis of colon cancer and could lead to advances in cancer diagnosis generally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using GANs to predict milling stability from limited data

Milling is a key manufacturing process that requires the selection of operating parameters that provide efficient performance. However, the presence of chatter, a self-excited vibration causing poor surface finish and potential damage to the machine and cutting tool, makes it challenging to select the appropriate parameters. To predict chatter, stability maps are commonly used, but their generation requires expensive data, making it difficult to employ these maps in industry. Therefore, there is a pressing need for an approach that can accurately predict stability maps using limited experimental data. This study introduces the new Encoder GAN (EGAN) approach based on Generative Adversarial Networks (GANs) that predicts stability maps using limited experimental data. The approach consists of the encoder, generator, and discriminator subnetworks and uses the trained encoder and generator to predict the target stability map. This versatile method can be applied to various tool setups and can accurately predict stability maps with limited experimental data (five to 10 cutting tests) even when there is little information available for unknown parameters. In conclusion, the study evaluates the proposed approach using both numerical data and experiments and demonstrates its superior performance compared to state-of-the-art benchmarks.

42 ENGINEERING↗
DOE OSTI2022

CUPID: The Next-Generation Neutrinoless Double Beta Decay Experiment

We report CUPID is a next-generation tonne-scale bolometric neutrinoless double beta decay experiment that will probe the Majorana nature of neutrinos and discover lepton number violation in case of observation of this singular process. CUPID will be built on experience, expertise and lessons learned in CUORE and will be installed in the current CUORE infra-structure in the Gran Sasso underground laboratory. The CUPID detector technology, successfully tested in the CUPID-Mo experiment, is based on scintillating bolometers of Li 2 MoO 4 enriched in the isotope of interest 100 Mo. In order to achieve its ambitious science goals, the CUPID collaboration aims to reduce the backgrounds in the region of interest by a factor 100 with respect to CUORE. This performance will be achieved by introducing the high efficient α/β discrimination demonstrated by the CUPID-0 and CUPID-Mo experiments, and using a high transition energy double beta decay nucleus such as 100 Mo to minimize the impact of the gamma background. CUPID will consist of about 1500 hybrid heat-light detectors for a total isotope mass of 250 kg. The CUPID scientific reach is supported by a detailed and safe background model based on CUORE, CUPID-Mo and CUPID-0 results. The required performances have already been demonstrated and will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Hierarchical Model Reduction Driven by Machine Learning for Parametric Advection-Diffusion-Reaction Problems in the Presence of Noisy Data

Abstract We propose a new approach to generate a reliable reduced model for a parametric elliptic problem, in the presence of noisy data. The reference model reduction procedure is the directional HiPOD method, which combines Hierarchical Model reduction with a standard Proper Orthogonal Decomposition, according to an offline/online paradigm. In this paper we show that directional HiPOD looses in terms of accuracy when problem data are affected by noise. This is due to the interpolation driving the online phase, since it replicates, by definition, the noise trend. To overcome this limit, we replace interpolation with Machine Learning fitting models which better discriminate relevant physical features in the data from irrelevant unstructured noise. The numerical assessment, although preliminary, confirms the potentialities of the new approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Multiparameter Methods are the New Field in Statistics

During the last decade statistical problems of a new kind have appeared more and more often, in which the dimensionality of observations is large, and the sample size is small or comparable with the dimensionality of observations. These problems may be characterized as multiparameter problems. The theory of multiparameter analysis, proposed by A.N.Kolmogorov and supported by the studies on the spectral theory of random matrices of V. A.Marchenko, L. A.Pastur, V. L.Girko, and others, revealed some specific phenomena appearing in statistics with a large number of weakly dependent variables. Particularly, there are stable relations between the principal parts of parameter set functions and the set of observed variables, which may be used to improve the statistical analysis. The use of these phenomena allows one to develop a thorough, always stable, and approximately optimal (irrespective of samples) versions of mostly used statistical procedures. The multiparameter versions of the discriminant analysis are of special interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Identifying and quantifying short-lived fission products from thermal fission of HEU using portable HPGe detectors

Due to the emerging potential for trafficking of special nuclear material, research programs are investigating current capabilities of commercially available portable gamma ray detection systems. Presented in this paper are the results of three different portable high-purity germanium (HPGe) detectors used to identify short-lived fission products generated from thermal neutron interrogation of small samples of highly enriched uranium. Samples were irradiated at the Washington State University (WSU) Nuclear Radiation Center’s 1MW TRIGA reactor. The three portable, HPGe detectors used were the ORTEC MicroDetective, the ORTEC Detective, and the Canberra Falcon. Canberra’s GENIE-2000 software was used to analyze the spectral data collected from each detector. Ultimately, these three portable detectors were able to identify a large range of fission products showing potential for material discrimination.

detectors↗
DOE OSTI2013

Comparison of Radionuclide Ratios in Atmospheric Nuclear Explosions and Nuclear Releases from Chernobyl and Fukushima seen in Gamma Ray Spectormetry

The Comprehensive Nuclear Test Ban Treaty (CTBT) has remote radionuclide monitoring followed by an On Site Inspection (OSI) to clarify the nature of a suspect event. An important aspect of radionuclide measurements on site is the discrimination of other potential sources of similar radionuclides such as reactor accidents or medical isotope production. The Chernobyl and Fukushima nuclear reactor disasters offer two different reactor source term environmental inputs that can be compared against historical measurements of nuclear explosions. The comparison of whole-sample gamma spectrometry measurements from these three events and the analysis of similarities and differences are presented. This analysis is a step toward confirming what is needed for measurements during an OSI under the auspices of the Comprehensive Test Ban Treaty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Porous Chromatographic Materials as Substrates for Preparing Synthetic Nuclear Explosion Debris Particles

In this study, we investigated several porous chromatographic materials as synthetic substrates for preparing surrogate nuclear explosion debris particles. The resulting synthetic debris materials are of interest for use in developing analytical methods. Eighteen metals, including some of forensic interest, were loaded onto materials by immersing them in metal solutions (556 mg/L of each metal) to fill the pores, applying gentle heat (110°C) to drive off water, and then treating them at high temperatures (up to 800°C) in air to form less soluble metal species. High-boiling-point metals were uniformly loaded on spherical controlled-pore glass to emulate early fallout, whereas low-boiling-point metals were loaded on core-shell silica to represent coated particles formed later in the nuclear fallout-formation process. Analytical studies were applied to characterize solubility, material balance, and formation of recalcitrant species. Dissolution experiments indicated loading was 1.5 to 3 times higher than expected from the pore volume alone, a result attributed to surface coating. Analysis of load solutions before and after filling the material pores revealed that most metals were passively loaded; that is, solutions filled the pores without active metal discrimination. However, niobium and tin concentrations were lower in solutions after pore filling, and were found in elevated concentrations in the final products, indicating some metals were selectively loaded. High-temperature treatments caused reduced solubility of several metal species, and loss of some metals (rhenium and tellurium) because volatile species were formed. Sample preparation reproducibility was high (the inter-batch relative standard deviation was 7.8%, and the intra-batch relative standard deviation was 0.84%) indicating that this material is suitable for use as a working standard for analytical methods development. We anticipate future standardized radionuclide-loaded materials will find use in radioanalytical methods development and/or serve as a starting material for the synthesis of more complex forms of nuclear explosion debris (e.g., Trinitite).

36 MATERIALS SCIENCE↗
DOE OSTI2015

Consideration of impact of atmospheric intrusion in subsurface sampling for investigation of suspected underground nuclear explosions

Radioactive noble gases radioxenon and radioargon constitute the primary smoking gun of an underground nuclear explosion. The aim of subsurface sampling of soil gas as part of an on-site inspection (OSI) is to search for evidence of a suspected underground nuclear event. It has been hypothesized that atmospheric gas can disturb soil gas concentrations and therefore potentially add to problems in civilian source discrimination verifying treaty compliance under the comprehensive nuclear-test-ban treaty. Furthermore, this work describes a study of intrusion of atmospheric air into the subsurface and its potential impact on an OSI using results of simulations from the underground transport of environmental xenon (UTEX) model.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Liquid Scintillation Counting of Environmental Radioisotopes: A Review of the Impact of Background Reduction

Liquid scintillation counting (LSC) is a versatile and commonplace method for radiometric measurement of charged particle emitting radionuclides. The LSC method provides utility in a range of environmental science applications including hydrological studies of water transport, anthropogenic releases of radionuclides into the environment, and vertical mixing rates within oceans. Instrumental measurement background is one limiting factor of radiometric measurement sensitivity. As part of the development of a custom low background LSC system located in a shallow underground laboratory at Pacific Northwest National Laboratory, a number of measurement applications of LSC have been considered and are summarized here. The focus is on determining which aspects of such measurements would gain the greatest benefit from the reduction of LSC backgrounds by a factor of 10-100 relative to values reported in the literature. Examples of benefits include lowering the minimum detectable activity, reducing the sample size required, and shortening the elapsed timeline of the processing and analysis sequence. In particular tritium, strontium, and actinium isotopes are examined as these isotopes cover a range of requirements related to the LSC measurement method (e.g., 3H: low energy; Sr: spectral deconvolution; Ac: alpha/beta discrimination).

actinium↗
DOE OSTI2019

Results from the third Galaxy Serpent tabletop exercise demonstrating the utility of nuclear forensics libraries in support of an investigation

Galaxy Serpent is a virtual, web-based international ongoing series of tabletop exercises designed to mature the concept of National Nuclear Forensics Libraries (NNFL) and illustrate their utility in answering investigative questions or providing investigative leads as part of an investigation involving nuclear or other radioactive material (R/N) out of regulatory control (MORC). Two prior versions of the exercise have been conducted; the first utilizing surrogate data for spent nuclear fuel as the material of interest, and the second using synthetic sealed radioactive source data. Teams participating in the recently concluded third version of the exercise were provided with synthetic uranium ore concentrate (UOC) data mimicking actual data characteristics (e.g. trace element concentrations), which was used to compile a model NNFL. Teams decided how to organize and interpret the data they were provided, dealt with real world features such as missing data, and assessed discriminating attributes. Next, a hypothetical scenario involving three UOC samples found out of regulatory control was provided, and each team had to assess the self-consistency of the individual sources in the unknown data, and employ their model NNFL as a comparative assessment instrument to determine whether the three UOC materials in question were consistent with any of the types of materials in their library. In conclusion, the design of the exercise, methodologies utilized by participating teams, and aggregate results of the exercise will be presented, along with challenges encountered and benefits realized.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

In the nuclear explosion monitoring context, what is an anomaly?

Abstract In the early years of nuclear explosion monitoring, experts used downwind detections with meaningful ratios of radioactive species to identify an explosion. Today’s reality is sparse networks of radionuclide monitoring stations looking for weak signals. Analysts need to discriminate between industrial background radioactivity and nuclear explosion signals, even using the detection of one isotope. Aerosol and xenon measurements potentially related to nuclear tests in 2006 and 2013 announced by the Democratic People’s Republic of Korea and from worldwide civilian background radioactivity are considered when defining radionuclide detection anomalies to objectively guide the use of limited analyst resources and reduce the possibility of not detecting nuclear explosions.

Miley, Harry S.↗
DOE OSTI2025

RIMS analysis of isotopically tagged uranium particles with application to Intentional Forensics

Traditional nuclear forensics approaches leverage isotopic measurements for characterizing nuclear forensics signatures in fuel cycle materials. To aid in provenance assessment, isotopically perturbed transition metal taggants can be added to fuel cycle materials. We present a case study for examining natural uranium oxide powder that was tagged with isotopically perturbed Mo before and after irradiation using resonance ionization mass spectrometry. In conclusion, this method accurately and precisely measures taggant and uranium compositions, rapidly enabling the ability to clearly discriminate between tagged particles and other material with application for robust assessment of material provenance.

Forensic Anthropology↗
DOE OSTI2019

Particle filter-based modulation domain infrared targets tracking

Faced with problems of low contrast, poor SNR, and relatively complicated tracking environment, stable infrared target tracking is worth researching for its many potential applications. In this paper, instead of traditional target tracking in the pixel domain, we propose a sampling importance resampling (SIR) particle filter method with indirect velocity measurements to track infrared targets in the modulation domain. The dominant amplitude modulation (AM) features used for tracking is extracted by decomposing the input image using an 18-channel Gabor filter bank followed by the application of the dominant component analysis approach. The dominant AM modulation features provide a significant partial texture characteristic of the target which can be separated from background with better discrimination. To take advantage of observed kinematics, we utilize the augmented state vector with indirect velocity information via combining the measurements of velocity in adjacent frames to the SIR particle filter framework, which weakens weights of particles with bad velocity estimates but still having association with the cluttered background or other moving objects. A dynamic template update strategy is also provided to prevent the tracker from appearance model drift. Experiments indicate that the proposed method is effective for raising the tracking accuracy compared with other tracking methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Vehicle detection based on visual attention mechanism and adaboost cascade classifier in intelligent transportation systems

Robust and efficient vehicle detection is an essential task in intelligent transportation systems (ITS). Unfortunately, due to a great diversity of vehicle profiles and outdoor illumination conditions, it is a challenge to detect vehicles effectively. This paper proposes a method for high-performance vehicle detection based on visual attention mechanism and AdaBoost cascade classifier. Our method constructs the structural Haar features and extracts the features of samples using structural Haar features and trains an AdaBoost cascade classifier. Then we use the visual attention mechanism to extract the target candidate region. At last, we generate detecting sub-windows in the candidate region and discriminate them with the cascade classifier to realize vehicle detection. We compare the performance of this method against two variants, one using MB–LBP features and another using Haar features. The experimental results demonstrate satisfactory performance for the proposed method in term of training speed, detecting speed and detecting accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

HIF2 ODD-luciferase reporter: the most sensitive assay for HIF prolyl hydroxylase inhibitors

Reporters expressing fusion proteins of HIF2 and HIF3 C-terminal oxygen degradable domain (ODD) with the firefly luciferase, HIF2 ODD-luc and HIF3 ODD-luc, were constructed and briefly characterized. Stable neuroblastoma cell lines expressing either reporter were generated, and their response to the known HIF prolyl hydroxylase inhibitors: dimethyloxalylglycine, ciclopirox, and adaptaquin, was studied and compared with the HIF1 ODD-luc reporter. The HIF2 ODD-luc reporter exhibited the highest sensitivity: its response in absolute luminescence value was almost an order of magnitude higher than that of the HIF1 ODD-luc reporter. The new reporter can be used for a fine discrimination of enzyme inhibitors stabilizing HIF2, and further structural optimization of adaptaquin discovered earlier by using the HIF1 ODD-luc reporter. The higher sensitivity of HIF2 ODD-luc reporter could be most likely explained by the lower affinity of the endogenous enzyme for this HIF isoform in comparison with the two others, which also resulted in the increased efficiency of inhibitors under the reporter assay conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Chiral guest in a chiral framework: X-ray diffraction study

The inclusion compound of zinc lactate terephthalate with R-butan-2-ol, [Zn{sub 2}(R-Bu{sup s}OH) (bdc)(S-lac)]•(R-Bu{sup s}OH) (Bu{sup s}OH is butan-2-ol, H{sub 2}bdc is terephthalic acid, S-H{sub 2}lac is lactic acid), was prepared by soaking crystals of [Zn{sub 2}(dmf)(bdc)(S-lac)]•DMF in pure R-butan-2-ol. The positions of chiral alcohol molecules in voids of the chiral framework and the host–guest contacts were determined by X-ray diffraction. These data provide an explanation for the origin of chiral discrimination of zinc lactate terephthalate toward the R-isomer of butan-2-ol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Scalable balanced training of conditional generative adversarial neural networks on image data

Here, we propose a distributed approach to train deep convolutional generative adversarial neural network (DC-CGANs) models. Our method reduces the imbalance between generator and discriminator by partitioning the training data according to data labels, and enhances scalability by performing a parallel training where multiple generators are concurrently trained, each one of them focusing on a single data label. Performance is assessed in terms of inception score, Fréchet inception distance, and image quality on MNIST, CIFAR10, CIFAR100, and ImageNet1k datasets, showing a significant improvement in comparison to state-of-the-art techniques to training DC-CGANs. Weak scaling is attained on all the four datasets using up to 1000 processes and 2000 NVIDIA V100 GPUs on the OLCF supercomputer Summit.

97 MATHEMATICS AND COMPUTING↗