Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “progress”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Biogas Opportunities Roadmap Progress Report

In support of the Obama Administration's Climate Action Plan, the U.S. Department of Energy, the U.S. Environmental Protection Agency, and U.S. Department of Agriculture jointly released the Biogas Opportunities Roadmap Progress Report, updating the federal government's progress to reduce methane emissions through biogas systems since the Biogas Opportunities Roadmap was completed by the three agencies in July 2014. The report highlights actions taken, outlines challenges and opportunities, and identifies next steps to the growth of a robust biogas industry.

09 BIOMASS FUELS↗
DOE OSTI2019

MicroRNAs as biomarkers of diabetic retinopathy and disease progression

Diabetes mellitus, together with its complications, has been increasing in prevalence worldwide. Its complications include cardiovascular disease (e.g., myocardial infarction, stroke), neuropathy, nephropathy, and eye complications (e.g., glaucoma, cataracts, retinopathy, and macular edema). In patients with either type 1 or type 2 diabetes mellitus, diabetic retinopathy is the leading cause of visual impairment or blindness. It is characterized by progressive changes in the retinal microvasculature. The progression from nonproliferative diabetic retinopathy to a more advanced stage of moderate to severe nonproliferative diabetic retinopathy and proliferative diabetic retinopathy occurs very quickly after diagnosis of mild nonproliferative diabetic retinopathy. The etiology of diabetic retinopathy is unclear, and present treatments have limited effectiveness. Currently diabetic retinopathy can only be diagnosed by a trained specialist, which reduces the population that can be examined. A screening biomarker of diabetic retinopathy with high sensitivity and specificity would aid considerably in identifying those individuals in need of clinical assessment and treatment. The majority of the studies reviewed identified specific microRNAs in blood serum/plasma able to distinguish diabetic patients with retinopathy from those without retinopathy and for the progresion of the disease from nonproliferative diabetic retinopathy to proliferative diabetic retinopathy. In addition, certain microRNAs in vitreous humor were dysregulated in proliferative diabetic retinopathy compared to controls. A very high percentage of patients with diabetic retinopathy develop Alzheimer’s disease. Thus, identifying diabetic retinopathy by measurement of suitable biomarkers would also enable better screening and treatment of those individuals at risk of Alzheimer’s disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

MicroRNAs in blood and cerebrospinal fluid as diagnostic biomarkers of multiple sclerosis and to monitor disease progression

Multiple sclerosis is a chronic autoimmune disease of the central nervous system. It is the main cause of non-traumatic neurological disability in young adults. Multiple sclerosis mostly affects people aged 20–50 years; however, it can occur in young children and much older adults. Factors identified in the distribution of MS include age, gender, genetics, environment, and ethnic background. Multiple sclerosis is usually associated with progressive degrees of disability. The disease involves demyelination of axons of the central nervous system and causes brain and spinal cord neuronal loss and atrophy. Diagnosing multiple sclerosis is based on a patient’s medical history including symptoms, physical examination, and various tests such as magnetic resonance imaging, cerebrospinal fluid and blood tests, and electrophysiology. The disease course of multiple sclerosis is not well correlated with the biomarkers presently used in clinical practice. Blood-derived biomarkers that can detect and distinguish the different phenotypes in multiple sclerosis may be advantageous in personalized treatment with disease-modifying drugs and to predict response to treatment. The studies reviewed have shown that the expression levels of a large number of miRNAs in peripheral blood, serum, exosomes isolated from serum, and cerebrospinal fluid are altered in multiple sclerosis and can distinguish the disease phenotypes from each other. Further studies are warranted to independently validate these findings so that individual or pairs of miRNAs in serum or cerebrospinal fluid can be used as potential diagnostic markers for adult and pediatric multiple sclerosis and for monitoring disease progression and response to therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease states in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

Generalized Method of Cells↗
NASA NTRS2018

GEONEX: Progressive Conditional Generative Adversarial Training Using Transfer learning

Obtaining accurate segmentation on large scale images is an open problem in deep learning. The main problem is the amount of labeled data that exists for large scale images. Traditionally, the common solution to this problem is to crop the large images into smaller images to increase the amount of available data and train a Conditional Generative Adversarial Network (CGAN). CGANs are currently the state of the art in image to image translation and provide better accuracy than the traditional method of training a encoder based conv-net architecture to minimize the loss at each pixel. This method can produce noisy and discontinuous images with inaccurate results. We seek to solve this problem by utilizing the concepts of transfer learning and progressive training to create a CGAN that can segment large scale images with a limited amount of labeled data. In transfer learning we recognize that many learned features are applicable to many classes from multiple domains. This introduces the concept of feature reusability, which is the basis for finetuning. Progressive training got its start in training models on the same images at different resolutions. In this work we instead train a GAN on increasing image scales by transferring the weights from the smaller scales to the larger scales. The learned features at the smaller scales are continually reused and applied to larger scales to create a CGAN that can perform accurate segmentation on large scale images. We apply this method to detect building footprints on very high-resolution overhead imagery (e.g Digital Globe and high resolution airborne platforms).

GEONEX↗
NASA NTRS2020

Progressive Failure Analysis Correlation with Notched Composite Laminate Test Data

Testing of small and intermediate laminate panels with notches was performed and Progressive Failure Analyses (PFA) models were developed for aid in test planning and for correlation with the test data. Two progressive damage failure models were included in the study: the commercially available Abaqus built-in damage model and COmplete STress Reduction (COSTR) damage model developed at NASA Langley Research Center (LaRC). The finite elements models used for the analysis were developed using shell elements. The pre-test PFA results obtained from the two damage models were compared to test data. Then a post-test PFA with updated material properties based on additional available material property data was executed with the COSTR damage model and compared to the test data. The panels tested in compression all exhibited less scatter in the failure load with self-similar failure behavior. The panels tested in tension exhibited more scatter in the failure load with a failure mode that included delamination of plies. However, a self-similar crack path was also observed as the overall failure mode for all panels tested. When comparing test data to the pre-test analysis results, both damage models with shell element models were considered adequate for predicting the behavior and failure load of both the small and intermediate panels when tested in compression. However, for the tension load cases, larger differences were observed between the test and analysis results. When comparing test data to the post-test analysis performed using the COSTR damage model, better correlation was observed. However, large discrepancies were still observed for the tension load cases. Consequently, a higher fidelity finite element model including solid elements for sub-laminates and the modeling of cohesive layers between sub-laminate layers is recommended for tension loading of notched composite laminates.

Damage Model,Progressive Failure Analysis,Open Hol↗
NASA NTRSDate not supplied

Composite Progressive Delamination Analysis of Thin Ply Buckling

The NASA Advanced Composites Project is a multi-year consortium of government, industry and academia to develop and validate technology that will reduce development and certification of advanced composite materials for aircraft structures. One of its tasks is to simulate and predict composite damage progression accurately through high fidelity finite element models. It included a subtask to verify an approach based on the Virtual Crack Closure Technology (VCCT) as well as Floating Node Method (FNM). This paper discusses predicted damage onset and growth in a thin-ply buckling problem. Sensitivity of the simulations to various initial crack length is studied. The compressive load-displacement curves are plotted and the crack growth critical load is predicted. Overall, the crack progression follows simulation benchmarks well. However, the critical-load overshoot phenomenon is observed in both VCCT and FNM, suggesting further investigation may be worth pursuing.

damage progression↗
NASA NTRS2023

Progressive Damage and Failure Analysis of Thermoplastic Composites in Low Velocity Impact Using MAT299

As part of the NASA Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project, state-of-the-art progressive damage and failure analysis (PDFA) tools developed for use with thermosets are being evaluated for use in modeling alternative material systems, like thermoplastics. Experimental low-velocity impact data of a thermoplastic material system, AS4D/PEKK-FC, is presented and includes characterization of the impact damage mechanisms as well as associated load and displacement data. Following the presentation of experimental results, two simulation approaches using the PDFA tool MAT299 in the commercial off-the-shelf finite element software LS-DYNA are employed to predict damage area and force-displacement responses of thermoplastic panels subjected to various impact energies. The first modeling method uses solid elements with a high-density mesh and a ply-by-ply modeling approach similar to previously published work for thermosets. This method has the capability of capturing individual crack development, progression, and delamination on a per ply basis. The second modeling method uses TSHELL elements that have in-plane dimensions that are an order of magnitude larger than the elements used in the solid element approach and reduces the number of elements through the thickness of the laminate. The second method produces a lower-fidelity model with reduced run times that is incapable of monitoring every delamination plane and damage within each ply. Results from both simulation methods are compared to experiment, and limitations of the methods are discussed.

Composite material↗
NASA NTRS2023

Progressive Damage and Failure Analysis of Thermoplastic Composites in Low Velocity Impact Using MAT299

As part of the NASA Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project, state-of-the-art progressive damage and failure analysis (PDFA) tools developed for use with thermosets are being evaluated for use in modeling alternative material systems, like thermoplastics. Experimental low-velocity impact data of a thermoplastic material system, AS4D/PEKK-FC, is presented and includes characterization of the impact damage mechanisms as well as associated load and displacement data. Following the presentation of experimental results, two simulation approaches using the PDFA tool MAT299 in the commercial off-the-shelf finite element software LS-DYNA are employed to predict damage area and force-displacement responses of thermoplastic panels subjected to various impact energies. The first modeling method uses solid elements with a high-density mesh and a ply-by-ply modeling approach similar to previously published work for thermosets. This method has the capability of capturing individual crack development, progression, and delamination on a per ply basis. The second modeling method uses TSHELL elements that have in-plane dimensions that are an order of magnitude larger than the elements used in the solid element approach and reduces the number of elements through the thickness of the laminate. The second method produces a lower-fidelity model with reduced run times that is incapable of monitoring every delamination plane and damage within each ply. Results from both simulation methods are compared to experiment, and limitations of the methods are discussed.

Composite material↗
DOE OSTI2020

A Progress Report on Metal–Sulfur Batteries

Nonaqueous conversion-reaction sulfur chemistry has been attracting increasing attention over the past decade for the development of next-generation lithium-based batteries. Li–S batteries are currently approaching a nexus stage from lab-scale experiments to possible pragmatic applications. Inspired by the success of Li–S chemistry, other metal–sulfur batteries with a variety of metallic anodes, such as sodium, potassium, magnesium, calcium, and aluminum, have also started to attract attention. In comparison to lithium, Na, Mg, Al, K, and Ca are naturally more abundant and affordable. The Na-S, Mg-S, Al-S, K-S, and Ca-S battery systems provide a great potential for improving the volumetric energy density of sulfur-based batteries. The multivalent metal-sulfur systems, Mg-S, Al-S, and Ca-S, offer better safety features as well. However, the research and development on Na-S, Mg-S, Al-S, K-S, and Ca-S batteries is far behind the Li–S system due to many critical challenges. In this progress report, the fundamental principles of various metal–sulfur chemistries are first presented and compared. Then, the historical progress, recent advances, and key challenges of the Li–S, Na-S, Mg-S, Al-S, K-S, and Ca-S systems are summarized and discussed. Finally, future efforts and directions for both the fundamental and practical research are prospected.

25 ENERGY STORAGE↗
DOE OSTI2021

Progress in Epitaxial Thin-Film Na 3 Bi as a Topological Electronic Material

Trisodium bismuthide (Na 3 Bi) is the first experimentally verified topological Dirac semimetal, and is a 3D analogue of graphene hosting relativistic Dirac fermions. Its unconventional momentum-energy relationship is interesting from a fundamental perspective, yielding exciting physical properties such as chiral charge carriers, the chiral anomaly, and weak anti-localization. It also shows promise for realizing topological electronic devices such as topological transistors. Herein, an overview of the substantial progress achieved in the last few years on Na 3 Bi is presented, with a focus on technologically relevant large-area thin films synthesized via molecular beam epitaxy. Key theoretical aspects underpinning the unique electronic properties of Na 3 Bi are introduced. Next, the growth process on different substrates is reviewed. Spectroscopic and microscopic features are illustrated, and an analysis of semiclassical and quantum transport phenomena in different doping regimes is provided. Furthermore, the emergent properties arising from confinement in two dimensions, including thickness-dependent and electric-field-driven topological phase transitions, are addressed, with an outlook toward current challenges and expected future progress.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Research Progress towards Understanding the Unique Interfaces between Concentrated Electrolytes and Electrodes for Energy Storage Applications

The electrolyte is an indispensable component in all electrochemical energy storage and conversion devices with batteries being a prime example. While most research efforts have been pursued on the materials side, the progress for the electrolyte is slow due to the decomposition of salts and solvents at low potentials, not to mention their complicated interactions with the electrode materials. The general properties of bulk electrolytes such as ionic conductivity, viscosity, and stability all affect the cell performance. However, for a specific electrochemical cell in which the cathode, anode, and electrolyte are optimized, it is the interface between the solid electrode and the liquid electrolyte, generally referred to as the solid electrolyte interphase (SEI), that dictates the rate of ion flow in the system. The commonly used electrolyte is within the range of 1–1.2 m based on the prior optimization experience, leaving the high concentration region insufficiently recognized. Recently, electrolytes with increased concentration (>1.0 m ) have received intensive attention due to quite a few interesting discoveries in cells containing concentrated electrolytes. The formation mechanism and the nature of the SEI layers derived from concentrated electrolytes could be fundamentally distinct from those of the traditional SEI and thus enable unusual functions that cannot be realized using regular electrolytes. In this article, we provide an overview on the recent progress of high concentration electrolytes in different battery chemistries. The experimentally observed phenomena and their underlying fundamental mechanisms are discussed. New insights and perspectives are proposed to inspire more revolutionary solutions to address the interfacial challenges.

25 ENERGY STORAGE↗
DOE OSTI2024

Variation in the contribution of macroinvertebrates to wood decomposition as it progresses

Abstract Although necromass decay rates are limited by the slowest portions to decompose, most decomposition studies examine only the earliest stage of decay. As such, these studies run the risk of yielding misleading results regarding the relative contributions of different decomposers. For example, the contributions of macroinvertebrates to wood decomposition remain mostly unknown beyond the first 50% of mass lost, despite drastic changes in substrate conditions over time. We sought to clarify how the macroinvertebrate contribution to decay changes over the course of wood decomposition in the Southeastern United States—a region with a long history of wood decomposition research. To this end, we (1) compiled data from published studies comparing wood decay with and without macroinvertebrates; and (2) conducted a field study assessing wood mass loss, with and without macroinvertebrate access, at three sites across the region over four years. With these combined data, we analyzed macroinvertebrate contribution as decay progressed, revealing a quadratic relationship, wherein macroinvertebrate contribution increased early in decomposition and then began to decline as decay progressed. Strong local site effects, particularly the abundance and activity of termites, determine the time required for wood to reach this point of mass loss.

Environmental Sciences & Ecology↗
DOE OSTI2021

Progress Towards a Comprehensive Approach for Habitat Restoration in the Columbia Basin: Case Study in the Grande Ronde River

Abstract Despite immense resources directed towards habitat restoration, recovering fish populations remains a daunting and perplexing issue. In 2015, recommendations for a comprehensive approach to habitat restoration in the Columbia River basin were published in Fisheries, which included elements of landscape ecology and resilience, broad public support, governance for collaboration and integration, and capacity for learning and adaptation. Using the Grande Ronde River basin as a case study, we convened a working group consisting of local restoration practitioners, managers, and researchers involved in habitat restoration research, monitoring, and evaluation to assess progress towards meeting these recommendations. We concluded that partnerships and collaborations in governance have been formed and research using a landscape perspective has been integrated into decision making, but efforts would benefit from gaining broader public support, formalizing an adaptive management strategy, and defining objectives and indicators for biological and ecological diversity. Continued progress will require consistent policy and funding support from the broader region. We envision this self-assessment at the 5-year milestone would be helpful to other groups facing similar challenges.

White, Seth M. (ORCID:0000000349186865)↗
DOE OSTI2018

Distinct progression pattern of susceptibility MRI in the substantia nigra of Parkinson's patients

Abstract Background: Susceptibility MRI may capture Parkinson's disease‐related pathology. This study delineated longitudinal changes in different substantia nigra regions. Methods: Seventy‐two PD patients and 62 controls were studied at both baseline and after 18 months with MRI. R2* and quantitative susceptibility mapping values from the substantia nigra pars compacta and substantia nigra pars reticulata were calculated. Mixed‐effects models compared controls with PD or PD subgroups having different disease durations: early (<1 year), middle (<5 years, middle‐stage PD), and late (>5 years, late‐stage PD). Pearson's correlation assessed associations between imaging and clinical measures. Results: At baseline, R2* and quantitative susceptibility mapping were higher in both the substantia nigra pars compacta and substantia nigra pars reticulata in all PD patients (group effect, P ≤ 0.003). Longitudinally, the substantia nigra pars compacta R2* showed a faster increase in PD compared with controls (time × group, P = 0.002), whereas quantitative susceptibility mapping did not ( P = 0.668). The substantia nigra pars reticulata R2* and quantitative susceptibility mapping did not differ between PD and controls (time × group, P ≥ 0.084), although both decreased longitudinally (time effect, P ≤ 0.004). Baseline substantia nigra pars compacta R2* was higher in all PD subgroups (group, P ≤ 0.006), but showed a significantly faster increase only in later‐stage PD (time × group, P < 0.0001) that correlated with changes in nonmotor symptoms ( r = 0.746, P = 0.002). Baseline substantia nigra pars reticulata quantitative susceptibility mapping was higher in middle‐stage PD and later‐stage PD (group, P ≤ 0.002), but showed a longitudinal decrease (time × group, P = 0.004) only in later‐stage PD that correlated with changes in motor signs ( r = 0.837, P < 0.001). Conclusion: Susceptibility MRI revealed distinct patterns of PD progression in the substantia nigra pars compacta and substantia nigra pars reticulata. The different patterns are particularly clear in later‐stage patients. These findings may resolve past controversies and have implications in the pathophysiological processes during PD progression. © 2018 International Parkinson and Movement Disorder Society

Du, Guangwei↗
DOE OSTI2017

Photovoltaic Devices Based on Colloidal PbX Quantum Dots: Progress and Prospects

Here, a certified power conversion efficiency (PCE) of 12.0% and an outstanding air stability has been achieved for PbX quantum dots (QDs) solar cells, indicating strong potential for next generation low-cost solution-processed photovoltaics. Similar progress has been made in several other solar cell architectures employing PbX QD absorbers. This article aims to review the recent progress in understanding the photovoltaic-relevant properties of PbX QDs and highlight their application in various types of photovoltaic devices. In doing so, we hope that the unique properties of PbX QDs can be better understood in a broader context, and their potential can be fully realized with the aiding of other photovoltaic materials and novel device structures.

14 SOLAR ENERGY↗
DOE OSTI2023

Targeted mutagenesis with sequence–specific nucleases for accelerated improvement of polyploid crops: Progress, challenges, and prospects

Many of the world's most important crops are polyploid. The presence of more than two sets of chromosomes within their nuclei and frequently aberrant reproductive biology in polyploids present obstacles to conventional breeding. The presence of a larger number of homoeologous copies of each gene makes random mutation breeding a daunting task for polyploids. Genome editing has revolutionized improvement of polyploid crops as multiple gene copies and/or alleles can be edited simultaneously while preserving the key attributes of elite cultivars. Most genome–editing platforms employ sequence–specific nucleases (SSNs) to generate DNA double–stranded breaks at their target gene. Such DNA breaks are typically repaired via the error–prone nonhomologous end–joining process, which often leads to frame shift mutations, causing loss of gene function. Genome editing has enhanced the disease resistance, yield components, and end–use quality of polyploid crops. However, identification of candidate targets, genotyping, and requirement of high mutagenesis efficiency remain bottlenecks for targeted mutagenesis in polyploids. In this review, we will survey the tremendous progress of SSN–mediated targeted mutagenesis in polyploid crop improvement, discuss its challenges, and identify optimizations needed to sustain further progress.

60 APPLIED LIFE SCIENCES↗