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NASA NTRS2000

A Low Order and a High Order Solution for a Converging-Diverging Nozzle Problem

The Computational Aeroacoustics Workshops on Benchmark problems are conducted in order to generate solutions with a variety of methods for problems that are chosen both to be representative of significant and relevant acoustic phenomena. It is generally recognized that CAA applications require the resolution in time and in space of solution details over a significantly broader range of scales than typical computational fluid dynamics applications. These requirements are forcing the development of new methodologies for CAA applications. This paper presents numerical results from a third and a seventh order algorithm for the propagation of an acoustic signal through a converging-diverging nozzle. These two algorithms are members of a new family of high accuracy methods that have the same order accuracy in both space and time, and are an extension of previous work for linearized Euler equations to fully nonlinear time dependent problems. The simulations are all with the fully nonlinear quasi-1D Euler equations for the total solution, which includes both the fluid dynamics and the acoustics. The acoustic solution is obtained from the time dependent nonlinear solution by subtracting the steady solution.

Goodrich, John W.↗

NASA NTRS2006

The Scientific and Societal Need for Accurate Global Remote Sensing of Marine Suspended Sediments

Population pressure, commercial development, and climate change are expected to cause continuing alteration of the vital oceanic coastal zone environment. These pressures will influence both the geology and biology of the littoral, nearshore, and continental shelf regions. A pressing need for global observation of coastal change processes is an accurate remotely-sensed data product for marine suspended sediments. The concentration, delivery, transport, and deposition of sediments is strongly relevant to coastal primary production, inland and coastal hydrology, coastal erosion, and loss of fragile wetland and island habitats. Sediment transport and deposition is also related to anthropogenic activities including agriculture, fisheries, aquaculture, harbor and port commerce, and military operations. Because accurate estimation of marine suspended sediment concentrations requires advanced ocean optical analysis, a focused collaborative program of algorithm development and assessment is recommended, following the successful experience of data refinement for remotely-sensed global ocean chlorophyll concentrations.

Acker, James G.↗

NASA NTRS2012

Prognostics for Microgrid Components

Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

Saxena, Abhinav↗

NASA NTRS2014

RITRACKS: A Software for Simulation of Stochastic Radiation Track Structure, Micro and Nanodosimetry, Radiation Chemistry and DNA Damage for Heavy Ions

The code RITRACKS (Relativistic Ion Tracks) has been developed over the last few years at the NASA Johnson Space Center to simulate the effects of ionizing radiations at the microscopic scale, to understand the effects of space radiation at the biological level. The fundamental part of this code is the stochastic simulation of radiation track structure of heavy ions, an important component of space radiations. The code can calculate many relevant quantities such as the radial dose, voxel dose, and may also be used to calculate the dose in spherical and cylindrical targets of various sizes. Recently, we have incorporated DNA structure and damage simulations at the molecular scale in RITRACKS. The direct effect of radiations is simulated by introducing a slight modification of the existing particle transport algorithms, using the Binary‐Encounter‐Bethe model of ionization cross sections for each molecular orbitals of DNA. The simulation of radiation chemistry is done by a step‐by‐step diffusion‐reaction program based on the Green's functions of the diffusion equation]. This approach is also used to simulate the indirect effect of ionizing radiation on DNA. The software can be installed independently on PC and tablets using the Windows operating system and does not require any coding from the user. It includes a Graphic User Interface (GUI) and a 3D OpenGL visualization interface. The calculations are executed simultaneously (in parallel) on multiple CPUs. The main features of the software will be presented.

Plante, I↗

NASA NTRS2005

Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging

The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research periods is provided in Section 5. This research also resulted in the generation of intellectual property.

Rahman, Zia-ur↗

NASA NTRS2022

VIPRE: A Tool Aiding the Design for Entry Probe Missions

Exploring planetary atmospheres uncovers important information for how our solar system formed and evolved. While remote sensing is extensively used, some crucial observations require in-situ measurements by an atmospheric probe. Given their scientific importance, probe missions to Saturn, Uranus and Neptune are considered for the coming decades. In anticipation of future probe missions, the software tool VIPRE was developed as proof-of-concept to facilitate selection of probe entry locations. Currently, there is no analytical way to identify which interplanetary trajectory from thousands of feasible launch opportunities is optimal for a considered mission concept. The search and decision process for that solution is complex and relies on the intuition of mission designers, who focus on a subset of trajectories to make the trade space manageable. The idea of VIPRE is to (1) generate a multi-dimensional data cube showing relevant engineering and science parameters simultaneously for thousands of trajectories, and (2) visualize the data for all entry sites over the body's envelope. VIPRE lays the foundation to make the data available for browsing in a 3-D visualization to identify the best family of solutions for a given mission. The paper introduces the validated and verified core algorithms of VIPRE, published on GitHub. VIPRE serves as a basic framework to be used and extended for different purposes. The paper presents the motivation for the development and algorithms. It explains the computation and data visualization strategy, and gives a list of suggested functionalities to extend and further develop VIPRE to fully leverage its potential.

Ice Giants↗

NASA NTRS2014

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations Using a Piloted Aircraft

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority.

pilot ratings↗

NASA NTRS2015

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations of Adverse Interactions Using a Piloted Aircraft

manual steering mode↗

NASA NTRS1993

MAMS: High resolution atmospheric/surface properties

The Multispectral Atmospheric Mapping Sensor (MAMS) has been used for a number of investigations over the last 8 years. It has served as the basis for retrieval technique development, for atmospheric process studies, and to retrieve geophysical parameters at the surface (land and ocean). It was used most recently to collect high resolution visible and infrared imagery for the CaPE and STORMFEST experiments during FY91 and FY92. The Wildfire spectrometer (similar to MAMS but with different infrared channels) was also used during STORMFEST. The goals of MAMS during CaPE were: (1) to collect MAMS data to support the overall CaPE science objectives; (2) refine techniques for the retrieval of atmospheric moisture and surface geophysical parameters; (3) map the moisture distributions associated with the sea breeze front over Florida with MAMS ancillary satellite data on a case study basis; (4) identify surface features which may serve as local sources of heat and moisture and influence preferential convective regions over Florida, and (5) process MAMS data and derived relevant geophysical parameters to support other CaPE investigators. For STORMFEST both the MAMS and Wildfire spectrometers were used to collect unique multispectral data to study atmospheric processes. The Wildfire objectives were: (1) to collect high quality Wildfire data in conjunction with other in situ and remote measurements available during the STORMFEST field phase (1 February - 15 March 1992); (2) to develop algorithms to retrieve total ozone content and compare with those from TOMS and HIRS (IR); and (3) along with water vapor imagery, use the ozone data to better understand the 3-dimensional structure and dynamics of jet streaks and frontal systems in a case study investigation. The MAMS objectives were: (1) collect MAMS data to support a GSFC investigation of gravity waves; and (2) process the MAMS data to locate gravity wave features, and produce various moisture products in support of the gravity wave investigation. The research activities over the last year are presented and they focused on analyzing the CaPE data sets and collecting and starting preliminary analysis of the STORMFEST MAMS and Wildfire data.

Jedlovec, Gary J.↗

NASA NTRS2018

Future of Big Earth Data Analytics

The state of the art of Big Earth Data Analytics can be expected to evolve rapidly in the coming years. The forces driving evolution come from both growth in the data and advancement in the field of data analytics. In the data area, advances in sensor instrumentation and platform miniaturization are increasing both data resolution and coverage, resulting in enormous growth in data Volume. Increases in temporal resolution in particular also generate demands for higher data Velocity. At the same time, the proliferation of instruments and the platforms on which they reside is increasing the Variety of datasets. The Variety increase in turn leads to questions about the Veracity of the data. In the algorithm area, powerful machine learning methods are coming to the fore, particularly Deep Neural Networks. These are powerful at detecting interesting features in the data, integrating many different measurements (i.e., data fusion), and classification problems. However, they are still challenging when seeking explanations of how natural or socio-economic phenomena work using Earth Observations. Thus, classical analysis techniques will remain relevant when the emphasis is on forming or testing explanations, as well as to support interactive data exploration.

Lynnes, Christopher↗

NASA NTRS2006

Time Relevance of Convective Weather Forecast for Air Traffic Automation

The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

Chan, William N.↗

NASA NTRS2010

Confidence-Based Feature Acquisition

Confidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).

Wagstaff, Kiri L.↗

NASA NTRS2010

Visualization of Traffic Accidents

Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.

Wang, Jie↗

NASA NTRS2012

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

forecasting↗

NASA NTRS2015

Launch Vehicle Manual Steering with Adaptive Augmenting Control:In-Flight Evaluations of Adverse Interactions Using a Piloted Aircraft

An Adaptive Augmenting Control (AAC) algorithm for the Space Launch System (SLS) has been developed at the Marshall Space Flight Center (MSFC) as part of the launch vehicle's baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a potential manual steering mode were also investigated by giving the pilot trajectory deviation cues and pitch rate command authority, which is the subject of this paper. Two NASA research pilots flew a total of 25 constant pitch rate trajectories using a prototype manual steering mode with and without adaptive control, evaluating six different nominal and off-nominal test case scenarios. Pilot comments and PIO ratings were given following each trajectory and correlated with aircraft state data and internal controller signals post-flight.

adaptive control↗

NASA NTRS2011

A Deterministic Electron, Photon, Proton and Heavy Ion Radiation Transport Suite for the Study of the Jovian System

A deterministic suite of radiation transport codes, developed at NASA Langley Research Center (LaRC), which describe the transport of electrons, photons, protons, and heavy ions in condensed media is used to simulate exposures from spectral distributions typical of electrons, protons and carbon-oxygen-sulfur (C-O-S) trapped heavy ions in the Jovian radiation environment. The particle transport suite consists of a coupled electron and photon deterministic transport algorithm (CEPTRN) and a coupled light particle and heavy ion deterministic transport algorithm (HZETRN). The primary purpose for the development of the transport suite is to provide a means for the spacecraft design community to rapidly perform numerous repetitive calculations essential for electron, proton and heavy ion radiation exposure assessments in complex space structures. In this paper, the radiation environment of the Galilean satellite Europa is used as a representative boundary condition to show the capabilities of the transport suite. While the transport suite can directly access the output electron spectra of the Jovian environment as generated by the Jet Propulsion Laboratory (JPL) Galileo Interim Radiation Electron (GIRE) model of 2003; for the sake of relevance to the upcoming Europa Jupiter System Mission (EJSM), the 105 days at Europa mission fluence energy spectra provided by JPL is used to produce the corresponding dose-depth curve in silicon behind an aluminum shield of 100 mils ( 0.7 g/sq cm). The transport suite can also accept ray-traced thickness files from a computer-aided design (CAD) package and calculate the total ionizing dose (TID) at a specific target point. In that regard, using a low-fidelity CAD model of the Galileo probe, the transport suite was verified by comparing with Monte Carlo (MC) simulations for orbits JOI--J35 of the Galileo extended mission (1996-2001). For the upcoming EJSM mission with a potential launch date of 2020, the transport suite is used to compute the traditional aluminum-silicon dose-depth calculation as a standard shield-target combination output, as well as the shielding response of high charge (Z) shields such as tantalum (Ta). Finally, a shield optimization algorithm is used to guide the instrument designer with the choice of graded-Z shield analysis.

Norman, Ryan B.↗

NASA NTRS2018

Collaborative Data Curation to Support the Multi-Mission Algorithm and Analysis Platform (MAAP)

Upcoming space-borne missions will offer unprecedented data about Earth but will also feature exponentially high data volumes. These high data volumes will change the way the scientific community works with data and will also create a unique need for improved data sharing and collaboration. NASA and ESA are working together to address these issues by collaboratively developing the Multi-Mission Algorithm and Analysis Platform (MAAP) to improve the understanding of global aboveground terrestrial carbon dynamics. The MAAP will support ESA’s BIOMASS mission, NASA’s GEDI mission and NASA/ISRO’s NISAR mission. The MAAP will be developed in two phases: a pilot phase and a full production phase. The pilot phase will demonstrate collaboration and basic capabilities. The pilot phase will focus on biomass relevant airborne and field campaign data. Two NASA teams are supporting the development of the MAAP. The MAAP engineering team is responsible for the development, maintenance and operations of the MAAP system while the MAAP data team ensures the ongoing quality of the data, metadata and other information provided in the MAAP. The MAAP data team also supports the ingest and archive of identified data to the MAAP platform. This poster describes the use case development process for the pilot MAAP and the data curated in support of those use cases. Additionally, this presentation will outline the pilot MAAP data ingest process and metadata curation effort along with efforts to ensure interoperability between ESA and NASA data and metadata.

Bugbee, Kaylin↗

NASA NTRS1997

Application of Laser Scanning Confocal Microscopy to Heat and Mass Transport Modeling in Porous Microstructures

Laser Scanning Confocal Microscopy (LSCM) has been used to obtain digital images of the complicated 3-D (three-dimensional) microstructures of rigid, fibrous thermal protection system (TPS) materials. These orthotropic materials are comprised of refractory ceramic fibers with diameters in the range of 1 to 10 microns and have open porosities of 0.8 or more. Algorithms are being constructed to extract quantitative microstructural information from the digital data so that it may be applied to specific heat and mass transport modeling efforts; such information includes, for example, the solid and pore volume fractions, the internal surface area per volume, fiber diameter distributions, and fiber orientation distributions. This type of information is difficult to obtain in general, yet it is directly relevant to many computational efforts which seek to model macroscopic thermophysical phenomena in terms of microscopic mechanisms or interactions. Two such computational efforts for fibrous TPS materials are: i) the calculation of radiative transport properties; ii) the modeling of gas permeabilities.

Marshall, Jochen↗