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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Novel Approach to Simulating Diagnostic Capabilities in Medical Resource Risk Assessment

Diagnostics represent a key subset of medical resources considered for helping mitigate and control spaceflight medical risk. Historically, when modeling the medical risk domain for spaceflight, diagnostic resources have been handled like any other medical resource used for treatment. That is to say, the resource being unavailable will result in the related condition having suboptimal treatment outcomes. However in the real world, should a diagnostic resource be unavailable, a more analogous effect would be that the condition might be misdiagnosed, and thus inappropriate treatment applied. This talk presents an alternative means of representing diagnostic resources within the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) that can simulate the effect both in risk, resource consumption, and competition for resources of a missing or depleted diagnostic. The scenario where a differential diagnosis may not be possible for abdominal conditions that use an ultrasound machine as a diagnostic tool is considered. Two approaches for modeling the effect of not having a diagnostic capability on the medical system are demonstrated. In the “simple” approach, it is assumed that any abdominal condition requiring the ultrasound machine for diagnosis is mis-diagnosed and treated as an appendicitis. This is represented by replacing the treatment for the affected conditions with the treatment for appendicitis, thereby changing the optimized medical set available for treatment for the remainder of the mission. In the “complex” approach, MEDPRAT treatment clusters are utilized to capture and represent overlapping treatment between the misdiagnosed condition and appendicitis. This elicits both the effect that inappropriate treatment is applied, resulting in wasted resource consumption, and that treatment which was truly needed for the misdiagnosed condition was not applied, which reduces the treatment effectiveness. In this talk, results comparing the simple and complex diagnostic capability approach to a baseline where the diagnostic is treated as a traditional resource is presented. Either approach provides an option for a more analogous representation of diagnostic resources and provides insight into how the modeled spaceflight medical resources and outcomes change when that diagnostic is unavailable.

C. M. Gasiewski↗
DOE OSTI2020

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

Abstract The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long‐term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature ( Tmax ) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high‐emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH given Tmax with quantile regression models, using functions of temperature for each city in July for three time periods (1990–2005, 2026–2035, and 2071–2080). Quality‐of‐fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile of Tmax increases from 1990–2005 to 2071–2080, while mean RH decreases modestly. Conditional upon a fixed quantile of Tmax , the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixed Tmax , the high quantiles of RH (and thus of HI and dew point) increase from 1990–2005 to 2071–2080 in all four cities. This result suggests that the heat stress of a day at a given Tmax will increase in a warming climate due to the increase of RH.

Yuan, Jiacan↗
DOE OSTI2018

An Integrated Method of ANFIS and Dempster-Shafer Theory for Fault Diagnosis of Power Transformer

Dissolved gas analysis (DGA) approach is extensively applied to detect incipient faults of power transformers. This paper presents a novel DGA method for power transformer incipient fault diagnosis based on integrated adaptive neuro fuzzy inference system (ANFIS) and Dempster-Shafer Theory (DST). Four out of seven common conventional methods which are studied and compared for better consistency and accuracy, are used to develop new ANFIS based fault diagnosis models. To promote fault diagnostic performance further and make fault decision process more reliable and reasonable, an improved DST is introduced to integrate outputs of each ANFIS based model, and to provide comprehensive and convincing fault diagnosis results. The fault diagnosis capability of the proposed method is validated by a reported fault dataset and 10-fold cross validation experiment. The performance of the proposed method is compared with conventional approaches and ANFIS based models which demonstrate that the proposed method is superior to other methods and is more effective and stable for power transformer fault diagnosis with high accuracy and consistency.

adaptive nuero fuzzy inference system↗
DOE OSTI2018

Relativistic Modeling Capabilities in Perseus Extended MHD Simulation Code for HED Plasmas

This project is submitted in response to DE-FOA-0001153, and will be carried out by Dr. Charles Seyler and Dr. Nathaniel Hamlin as post doc under the direction of Professor Seyler. The objectives are to enable PERSEUS to self-consistently model relativistic high-energy-density (HED) laboratory and astrophysical phenomena. Electrons and ions in a plasma are generally modeled either as fluids using a two-fluid code, like PERSEUS, or as particles using a Particle-In- Cell (PIC) code. Nonrelativistic PERSEUS solves the two-fluid equations, formulated in terms of a generalized Ohm’s law (GOL), so as to model about nine orders of magnitude in density variation using a local semi-implicit method. Relativistic PERSEUS preserves this structure and therefore retains these advantageous properties, enabling it to model a broader range of relativistic HED phenomena than previous codes. We have also overcome a major technical challenge associated with solving a relativistic system of equations relating conserved quantities (momentum, energy, etc.) to primitive variables (density, velocity, and pressure). We have thus far developed a relativistic version of PERSEUS and demonstrated that it recovers expected nonrelativistic results. We are currently using relativistic PERSEUS to model two HED phenomena, namely laser-plasma interactions and X-pinches, both of which show spectroscopic evidence of relativistic electrons. In an X-pinch, a section of wire carrying sufficiently large current forms a plasma column that pinches down to a point-like source, generating X-rays for use in radiographic imaging. Laser-plasma interactions have been simulated using PIC codes, and we use their results as a benchmark for comparison. However, neither PIC codes nor existing two-fluid schemes can simulate X-pinches, due to the broad range of densities which have thus far made such a simulation computationally prohibitive. In both laser-plasma interaction and Xpinch simulations, we have observed relativistic phenomena that PERSEUS could not previously model. This includes relativistic channeling of a laser into an over-dense deuterium gas (i.e. induced transparency), consistent with PIC simulation results, along with energetic electrons and ions following an X-pinch and likely accompanied by strong X-ray emission, consistent with experimental observations of energetic X-rays. This proposal includes our latest simulation results. We will improve computational efficiency with techniques that allow the use of a less refined numerical grid. This will enable extensions to three-dimensional geometries. We will improve modeling of laser-plasma interactions and X-pinches, including radiative transport processes, in order to improve comparisons with PIC simulations and experimental diagnostics. We will also model power loss through electrode surface plasmas in magnetically insulated transmission lines (MITLs). We will model relativistic astrophysical phenomena in both astrophysical and HED regimes, which could shed light on the validity of laboratory astrophysics for certain problems. These phenomena are currently modeled using PIC codes and existing relativistic two-fluid codes, neither of which can model the range of length scales of which relativistic PERSEUS is capable. There is strong potential for this project to have a broad impact on both the astrophysical and laboratory plasma communities. In the laboratory community, our work is applicable to those concerned with laser-plasma interactions such as laser-driven fusion, and those in the dense Z pinch community concerned with X-pinches and electrode surface plasmas. An improved understanding of the mechanisms of hard (i.e. high-energy) X-ray generation will likely make important contributions toward the use of X-pinches for radiography through the harnessing or mitigation of hard X-rays, depending on the application. The modeling of electrode surface plasmas, including vacuum electron flow, will improve our understanding of power loss to various loads.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2003

Tagging Water Sources in Atmospheric Models

Tagging of water sources in atmospheric models allows for quantitative diagnostics of how water is transported from its source region to its sink region. In this presentation, we review how this methodology is applied to global atmospheric models. We will present several applications of the methodology. In one example, the regional sources of water for the North American Monsoon system are evaluated by tagging the surface evaporation. In another example, the tagged water is used to quantify the global water cycling rate and residence time. We will also discuss the need for more research and the importance of these diagnostics in water cycle studies.

Bosilovich, M.↗
NASA NTRS2014

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

propulsion system performance↗
NASA NTRS2014

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

propulsion system performance↗
NASA NTRS2015

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics: Engine Test Results

This paper presents a model-based architecture for performance trend monitoring and gas path fault diagnostics designed for analyzing streaming transient aircraft engine measurement data. The technique analyzes residuals between sensed engine outputs and model predicted outputs for fault detection and isolation purposes. Diagnostic results from the application of the approach to test data acquired from an aircraft turbofan engine are presented. The approach is found to avoid false alarms when presented nominal fault-free data. Additionally, the approach is found to successfully detect and isolate gas path seeded-faults under steady-state operating scenarios although some fault misclassifications are noted during engine transients. Recommendations for follow-on maturation and evaluation of the technique are also presented.

systems health monitoring↗
NASA NTRSDate not supplied

Hybrid Modeling of Unmanned Aerial Vehicle Electric Powertrain for Fault Detection and Diagnostics

This paper shows the application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived principles and empirical equations, as well as fully connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. It has already been applied to Li-ion batteries in the past, and in this work, we extend the applications to other components of an electric powertrain, namely electronic speed controller with pulse-width modulation, and brushless DC motor with connected propeller. Training and testing of the model is carried out using experimental data from Li-ion battery discharge and powertrain testing in a laboratory environment.

Physics-Informed Machine Learning↗
DOE OSTI2019

Modeling and Cost Benefit Analysis to Guide Deployment of POC Diagnostics for Non-typhoidal Salmonella Infections with Antimicrobial Resistance

Invasive non-typhoidal Salmonella (NTS) is among the leading causes of blood stream infections in sub-Saharan Africa and other developing regions, especially among pediatric populations. Invasive NTS can be difficult to treat and have high case-fatality rates, in part due to emergence of strains resistant to broad-spectrum antibiotics. Furthermore, improper treatment contributes to increased antibiotic resistance and death. Point of care (POC) diagnostic tests that rapidly identify invasive NTS infection, and differentiate between resistant and non-resistant strains, may greatly improve patient outcomes and decrease resistance at the community level. Here we present for the first time a model for NTS dynamics in high risk populations that can analyze the potential advantages and disadvantages of four strategies involving POC diagnostic deployment, and the resulting impact on antimicrobial treatment for patients. Our analysis strongly supports the use of POC diagnostics coupled with targeted antibiotic use for patients upon arrival in the clinic for optimal patient and public health outcomes. We show that even the use of imperfect POC diagnostics can significantly reduce total costs and number of deaths, provided that the diagnostic gives results quickly enough that patients are likely to return or stay to receive targeted treatment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Cosmological reconstruction and Om diagnostic analysis of Einstein-Aether theory

In this paper, we analyze the cosmological models in Einstein-Aether gravity, which is a modified theory of gravity in which a time-like vector field breaks the Lorentz symmetry. We use this formalism to analyse different cosmological models with different behavior of the scale factor. In this analysis, we use a certain functional dependence of the Dark Energy (DE) on the Hubble parameter H . It will be demonstrated that the Aether vector field has a non-trivial effect on these cosmological models. We also perform the Om diagnostic in Einstein-Aether gravity and we fit the parameters of the cosmological models using recent observational data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Reconstruction of current profiles from external magnetic and MSE measurements on DIII-D

This work introduces a new current model into the EFIT code for plasma current profile reconstruction. Using this model, edge-localized current density profiles are reconstructed solely from external magnetic measurements. Quantitative comparisons show that edge current profiles obtained with the new current model align closely with those from kinetic equilibrium reconstruction. The new model enables current density reconstruction with fewer diagnostics than kinetic equilibrium reconstruction (Lao et al 1990 Nucl. Fusion 30 1035–49), demonstrating that edge-localized current density information can be obtained from external magnetic measurements only, without the help of kinetic profiles and internal diagnostics, and without using the bootstrap current model. Furthermore, with the constraints of external magnetic and MSE measurements, current profiles in full radius obtained from the new model are in good agreement with the results of kinetic equilibrium reconstruction, which not only improves the efficiency of current reconstruction but also helps avoid possible errors caused by different kinds of diagnoses. Possible applications are also discussed, and a brief analysis of the evolution of the full-radius current density is performed. Noticeable decreases in both the magnitude and gradient of the edge current around the time of ELM bursts are observed. Moreover, analysis of the full radius current density profiles ( ρ N = 0 − 1.0, ρN denotes to square root of the normalized toroidal flux) reveals that as the edge current changes, the inner current also changes following a sinusoidal-like pattern at almost all time slices during four type-I ELMs in discharge 161493. The current evolution in the inner region ( ρ N = 0.2 − 0.6) is synchronized with the boundary region ( ρ N = 0.89 − 1.0), while the intermediate region ( ρ N = 0.6 − 0.89) shows opposite behavior. This sinusoidal-like variations in full-radius current density profile indicates strong core-pedestal coupling, suggesting ELMs significantly affect core plasmas, though current changes manifest differently across radial regions.

EFIT↗
DOE OSTI2026

An Exploration of the Equation of State Dependence of Core-collapse Supernova Explosion Outcomes and Signatures

We explore, using a state-of-the-art simulation code in 3D and late-enough times to witness final observables, the dependence of core-collapse supernova explosions on the nuclear equation of state (EOS). Going beyond questions of explodability, we compare final explosion energies, nucleosynthetic yields, recoil kicks, and gravitational-wave and neutrino signatures using the SFHo and DD2 nuclear EOSs for a 9 M ⊙ /solar-metallicity progenitor star. The DD2 EOS is stiffer and has a lower effective nucleon mass. The result is a more extended protoneutron star (PNS) and lower central densities. As a consequence, the mean neutrino energies, final explosion energy, and recoil kick speed are lower. Moreover, the evolution of PNS convection differs between the two EOS models in significant ways. This translates in part into interestingly altered neutrino “light” curves and noticeably altered gravitational-wave signal strengths and frequency characteristics that may be diagnostic. The faster exploding model (SFHo) yields slightly more neutron-rich ejecta and more species with atomic weights between 60 and 90 and a weak r-process. However, this is merely a preliminary study. The next step is a more comprehensive and multiprogenitor set of 3D supernova simulations for various EOSs to late times when the observables have asymptoted. Such a future investigation will have a direct bearing on the neutron star and black hole birth mass functions and the quest toward a fully quantitative theory of supernova observables.

Rusakov, Aleksandr [Princeton University, NJ (Unit↗
NASA NTRS2001

Plasma Reactor Modeling and Validation Experiments

Plasma processing is a key processing stop in integrated circuit manufacturing. Low pressure, high density plum reactors are widely used for etching and deposition. Inductively coupled plasma (ICP) source has become popular recently in many processing applications. In order to accelerate equipment and process design, an understanding of the physics and chemistry, particularly, plasma power coupling, plasma and processing uniformity and mechanism is important. This understanding is facilitated by comprehensive modeling and simulation as well as plasma diagnostics to provide the necessary data for model validation which are addressed in this presentation. We have developed a complete code for simulating an ICP reactor and the model consists of transport of electrons, ions, and neutrals, Poisson's equation, and Maxwell's equation along with gas flow and energy equations. Results will be presented for chlorine and fluorocarbon plasmas and compared with data from Langmuir probe, mass spectrometry and FTIR.

Meyyappan, M.↗
DOE OSTI2023

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗
NASA NTRS1990

Propulsion simulation for magnetically suspended wind tunnel models

The feasibility of simulating propulsion-induced aerodynamic effects on scaled aircraft models in wind tunnels employing Magnetic Suspension and Balance Systems. The investigation concerned itself with techniques of generating exhaust jets of appropriate characteristics. The objectives were to: (1) define thrust and mass flow requirements of jets; (2) evaluate techniques for generating propulsive gas within volume limitations imposed by magnetically-suspended models; (3) conduct simple diagnostic experiments for techniques involving new concepts; and (4) recommend experiments for demonstration of propulsion simulation techniques. Various techniques of generating exhaust jets of appropriate characteristics were evaluated on scaled aircraft models in wind tunnels with MSBS. Four concepts of remotely-operated propulsion simulators were examined. Three conceptual designs involving innovative adaptation of convenient technologies (compressed gas cylinders, liquid, and solid propellants) were developed. The fourth innovative concept, namely, the laser-assisted thruster, which can potentially simulate both inlet and exhaust flows, was found to require very high power levels for small thrust levels.

Joshi, Prakash B.↗