Search NASA⌕ Search

SEARCH · Search NASA

Results for “System Process”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ML-based calibration and control of the GlueX Central Drift Chamber

The GlueX Central Drift Chamber (CDC) in Hall D at Jefferson Lab, used for detecting and tracking charged particles, is calibrated and controlled during data taking using a Gaussian process. The system dynamically adjusts the high voltage applied to the anode wires inside the chamber in response to changing environmental and experimental conditions such that the gain is stabilized. Control policies have been established to manage the CDC's behavior. These policies are activated when the model's uncertainty exceeds a configurable threshold or during human-initiated tests during normal production running. Finally, we demonstrate the system reduces the time detector experts dedicate to calibration of the data offline, leading to a marked decrease in computing resource usage without compromising detector performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

14 SOLAR ENERGY↗
DOE OSTI2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Strongly resonating bosons in hot nuclei

When two heavy ions near the Fermi energy collide, a warm and low-density region can form in which fragments appear. This region is mainly dominated by proton (p) and alpha (α) particles. In such an environment, the α particles interact with each other and, especially through strong resonances, form complex systems such as 8 Be and 12 C. Our experiments show that 70(64) Zn( 64 Ni) + 70(64) Zn( 64 Ni) reactions at E/A = 35 MeV/nucleon levels of 8Be appear around relative energies E ij = 0.092 MeV, 3.03 MeV as well as above 10 and 100 MeV. We propose a different method to derive the correlation function based on the relative transverse energy distribution to minimize the experimental uncertainties. For the 3α systems, multiresonance processes give rise to excited levels of 12 C. For instance, the Hoyle state at 7.654 MeV excitation energy shows a decay component through the ground state of 8 Be and also components where two different α couples are at relative energies consistent with the ground state of 8 Be at the same time.

6 ≤ A ≤ 19↗
DOE OSTI2024

Laminography as a tool for imaging large-size samples with high resolution

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high-resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X-ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab-shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low-cost instrument setup installed at the 2-BM micro-CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi-GPU systems for processing large-scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Hyperspectral target detection using manifold learning and multiple target spectra

Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interest in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Facet Suppression in (100) GaAs Spalling via Use of a Nanoimprint Lithography Release Layer

Controlled spalling is an emerging technique developed for fast, scalable wafer reuse, but for the commonly used (100) GaAs substrate system, the process leaves large facets ranging from 5-10 µm on the wafer surface. Removing them for wafer reuse requires a costly re-polishing step that limits the cost savings that can be achieved with spalling as a wafer reuse technique. In this study, we investigate facet suppression in spalling of (100) GaAs by redirecting the fracture front along features created by buried nanoimprint lithography (NIL)-patterned SiO 2 . We show successful facet suppression using patterns that result in favorable fracture along the SiO 2 /GaAs interface. The results from this work show NIL patterned interlayers are a promising method for faceting suppression in (100) GaAs spalling.

controlled spalling↗
DOE OSTI2017

Enhancing Critical Infrastructure and Key Resources (CIKR) Level-0 Physical Process Security Using Field Device Distinct Native Attribute Features

Here, the need for improved Critical Infrastructure and Key Resource (CIKR) security is unquestioned and there has been minimal emphasis on Level-0 (PHY Process) improvements. Wired Signal Distinct Native Attribute (WS-DNA) Fingerprinting is investigated here as a non-intrusive PHY-based security augmentation to support an envisioned layered security strategy. Results are based on experimental response collections from Highway Addressable Remote Transducer (HART) Differential Pressure Transmitter (DPT) devices from three manufacturers (Yokogawa, Honeywell, Endress+Hauer) installed in an automated process control system. Device discrimination is assessed using Time Domain (TD) and Slope-Based FSK (SB-FSK) fingerprints input to Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML) and Random Forest (RndF) classifiers. For 12 different classes (two devices per manufacturer at two distinct set points), both classifiers performed reliably and achieved an arbitrary performance benchmark of average cross-class percent correct of %C > 90%. The least challenging cross-manufacturer results included near-perfect %C ≈ 100%, while the more challenging like-model (serial number) discrimination results included 90%< %C < 100%, with TD Fingerprinting marginally outperforming SB-FSK Fingerprinting; SB-FSK benefits from having less stringent response alignment and registration requirements. The RndF classifier was most beneficial and enabled reliable selection of dimensionally reduced fingerprint subsets that minimize data storage and computational requirements. The RndF selected feature sets contained 15% of the full-dimensional feature sets and only suffered a worst case %CΔ = 3% to 4% performance degradation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Novel Method for Preoperative Positioning of Total Ankle Replacement Using 3D Digital Model

Abstract Objective To establish a digital model of the ankle joint through 3D imaging technology and explore the preoperative placement of ankle replacement prostheses. Methods Computed tomography images of intact ankle joints from 54 cases in the outpatient and inpatient departments of our hospital were collected; according to the INBONE® total ankle system surgery process, the surgery model and surgical osteotomy were finished using MIMICS based on computer simulation method. The shortest distance was measured between the center point and the anterior, posterior, medial, and lateral, respectively, to ensure the precise position of the ankle replacement prosthesis by digital simulation surgery. The relationship between the two variables was analyzed by bivariate correlation analysis. Results The dataset of this study included 48 cases of the sub‐data set (26 males and 22 females) and included 27 cases of left ankle and 21 cases of right ankle. The average medial malleolar angle was 18.67°± 2.87°, the average amount of bone resection was 12.13 ± 1.86 cm 3 , the mid‐anterior distance was 1.72 ± 0.19 cm, the mid‐posterior distance was 2.00 ± 0.19 cm, the ratio of mid‐anterior to mid‐posterior was 0.87, the mid‐medial distance was 1.26 ± 0.17 cm, the mid‐lateral distance was 1.19 ± 0.16 cm, and the ratio of mid‐medial to mid‐lateral was 1.06. After osteotomy, the anteroposterior diameter was 3.73 ± 0.32 cm, the transverse diameter was 2.46 ± 0.27 cm, and the ratio of anteroposterior diameter to transverse diameter was 1.53. In the bottom view, the shape after osteotomy is rectangular. The mid‐anterior distance was strongly negatively correlated with age, the mid‐anterior distance and the amount of bone resection, the mid‐medial distance and the amount of bone resection, the mid‐lateral distance and the amount of bone resection, the mid‐lateral distance and the anteroposterior diameter, the anteroposterior diameter and the transverse diameter were all strongly positively correlated. Conclusion The projection point of the lower tibia centerline on the tibial horizontal osteotomy surface is located at a position slightly anterior to the midpoint of the transverse diameter after ankle arthroplasty. The rational positioning of the total ankle replacement is located at both a position slightly anterior to the midpoint of the transverse diameter and midpoint of the anteroposterior diameter, which can be used as a reference method before total ankle arthroplasty surgery.

Wu, Shi‐xun↗
DOE OSTI2025

Review of High‐Speed Digital Image Correlation: Advancements and Good Practices

This paper reviews the current state of the art in high‐speed (HS) and ultrahigh‐speed (UHS) digital image correlation (DIC) techniques, emphasizing their critical role in experimental research across various scientific domains. HS and UHS DIC have evolved significantly, driven by advancements in camera systems, image processing algorithms and experimental methodologies. These developments have opened new avenues for capturing and analysing dynamic events with unprecedented temporal and spatial detail, but not without introducing challenges such as optical distortions, motion blur and lighting issues that can affect measurement quality. This review advocates for standardized reporting practices in HS/UHS DIC methodologies to improve reproducibility and reliability across studies, drawing on guidelines from the International Digital Image Correlation Society (iDICs). Through a comprehensive analysis of over 150 articles, this review identifies key advancements in imaging technology and their application in six research domains: material characterization, test development, fracture mechanics, model validation, ballistic and explosive phenomena assessment and measurement uncertainties. Distinctions between two‐dimensional (2D) and stereo‐DIC applications are explored, offering insights into their practical implementation and trade‐offs. Good practices for HS/UHS DIC applications are proposed along with suggestions for future directions for this evolving field, highlighting the indispensable role of technological innovation in expanding the capabilities of optical metrology.

experimental mechanics↗
DOE OSTI2017

State of the Art and Future Research Needs for Multiscale Analysis of Li-Ion Cells

The performance, safety, and reliability of Li-ion batteries are determined by a complex set of multiphysics, multiscale phenomena that must be holistically studied and optimized. This paper provides a summary of the state of the art in a variety of research fields related to Li-ion battery materials, processes, and systems. The material presented here is based on a series of discussions at a recently concluded bilateral workshop in which researchers and students from India and the U.S. participated. It is expected that this summary will help understand the complex nature of Li-ion batteries and help highlight the critical directions for future research.

25 ENERGY STORAGE↗
DOE OSTI2023

Combining Agent Based Modeling and System Dynamics to Investigate the Circularity of Plastics

The United States currently produces about 1 million metric ton of ocean plastic pollution annually. One proposed solution to combat plastic waste is a circular economy (CE), which aims to transition from today's take-make-waste linear pattern of production and consumption to a system where the value of resources is maximized over time. Two key methods in industrial ecology are useful in assessing the viability of CE: (1) System Dynamics (SD) and (2) Agent Based Modeling (ABM). In prior work, the plastic life cycle was modeled with SD and ABM. The two models calculate recycling rates and costs in different ways, making it difficult to pinpoint necessary next steps. We integrate the ABM and SD models - linking the emergent patterns from micro-level human decisions to system level processes - which allows a more comprehensive understanding of feedbacks, costs, and environmental impacts. The integrated model is more accurate, and can be used to visualize recycling rates and human health and environmental impacts over time. The difference between the integrated and original SD model prompts a Sobol sensitivity analysis, which is used to understand which behavioral factors most affect plastic recycling patterns. We find that the habitual component is typically the most influential in promoting positive recycling behavior. Additionally, we utilize the combined model to understand and visualize how various behavioral intervention scenarios, like improved access to recycling programs and cart tagging, influence recycling patterns; these results can guide future policy-making.

agent-based modeling↗
DOE OSTI2016

MO-FG-202-07: Real-Time EPID-Based Detection Metric For VMAT Delivery Errors

Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling and translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error source. J. V. Siebers receives funding support from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

pnnl/pecblocks

ConverterBlocks uses the output of detailed electromagnetic transient (EMT) simulations to produce generalized block diagram models of power electronic systems. The process uses deep learning with customized block architectures. The outputs are reduced-order models that meet specified accuracy requirements, while providing important advantages over the original EMT models: ConverterBlock models have fewer nodes and can take longer time steps, resulting in shorter simulation times ConverterBlock models are continuously differentiable, making them compatible with control design methodsGeneralized block diagram modeling of power electronic converters for grid solar and storage applications.

McDermott, Tom↗
DOE OSTI2019

Synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions

Recent advances in metabolic engineering have enabled the production of chemicals via bio-conversion using microbes. However, downstream separation accounts for 60–80% of the total production cost in many cases. Previous work on microbial production of extracellular chemicals has been mainly restricted to microbiology, biochemistry, metabolomics, or techno-economic analysis for specific product examples such as succinic acid, xanthan gum, lycopene, etc. In these studies, microbial production and separation technologies were selected apriori without considering any competing alternatives. However, technology selection in downstream separation and purification processes can have a major impact on the overall costs, product recovery, and purity. To this end, we apply a superstructure optimization based framework that enables the identification of critical technologies and their associated parameters in the synthesis and analysis of separation processes for extracellular chemicals generated from microbial conversions. We divide extracellular chemicals into three categories based on their physical properties, such as water solubility, physical state, relative density, volatility, etc. We analyze three major extracellular product categories (insoluble light, insoluble heavy and soluble) in detail and provide suggestions for additional product categories through extension of our analysis framework. The proposed analysis and results provide significant insights for technology selection and enable streamlined decision making when faced with any microbial product that is released extracellularly. The parameter variability analysis for the product as well as the associated technologies and comparison with novel alternatives is a key feature which forms the basis for designing better bioseparation strategies that have potential for commercial scalability and can compete with traditional chemical production methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Bias Between ENDF/B-VIII and ENDF/B-VII.1 for LEU Pin Array Systems

Extensive testing of new cross section data is performed in SCALE prior to its release. The release of ENDF/B-VIII.0 requires the generation and testing of new data libraries which are planned to be included in the release of SCALE 6.3 in 2019 or 2020. KENO benchmark results have been published previously for beta and final releases of ENDF/B-VIII.0 using the entire Verified, Archived Library of Inputs and Data (VALID). This work presents an energy-dependent change in the results for low-enriched uranium (LEU) pin array systems. The process of identifying the difference is highlighted as a case study to determine how data testing and benchmarking can be performed to provide more detailed feedback to the data community on potential data deficiencies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗