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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Generation of attenuation corrected images from lidar data

The interpretation of data generated by aerosol backscatter lidars is often facilitated by presentation of RHI and PPI images. These pictures are especially useful in studies of atmospheric boundary layer structure where convective elements, stratifications and aerosol laden plumes can be easily delineated. Procedures used at the University of Wisconsin to generate lidar images on a color enhanced raster scan display are described.

Eloranta, E. W.↗
NASA NTRSDate not supplied

Genesis Solar Wind Sample Curation Documentation

Introduction: A scientist with experience as a sample science analyst, provider of flight hardware for multiple missions, and senior engineer in an ISO 2000-rated manufacturing plant has described the timeline of key participants in any PI-led sample return mission, the breadth of the organizations involved [1,2], and, of interest to this meeting, choosing the types of data to preserve and issues of future data accessibility. This work broadens that perspective by giving similar lessons from Genesis sample curation point-of-view. Curation participation regarding data gathering was part of the mission review process from the beginning. Genesis’ story illustrates outcome of several choices about types of data to record and preserve. Precision analysis of solar wind atoms captured in pure, ultraclean substrates is the driving science goal; therefore, detailed documentation was captured from all mission and curation phases and from investigator laboratories because these processes affect the final analytical results [3]. Pre-flight: Design and fabrication of the spacecraft. Like many modern small sample return missions, Genesis was a tightly managed team integrated across science, engineering and curation. Communication across the team was excellent, and, for the most part, the hands-on engineering technicians understood the impacts of “small choices” they routinely make, and the eyes-on oversight of manufacturing processes by scientists was mindful of details. The payload was designed by the Jet Propulsion Laboratory and the spacecraft by Lockheed Martin. Solar wind collectors and instruments were fabricated by multiple vendors and laboratories. The main portion of the payload was assembled at JSC. Fabrication procedures and contamination-control data (with witness coupons) were stored primarily at JSC. The original composition, dimensions and configuration of components, results of thermal testing, etc. are still needed for interpretation of analytical data. At times, these must be estimated from secondary information acquired pre-flight. Moreover, some files (e.g., original 3-D models and early Powerpoint) cannot be opened using software. Archived curation data includes 2-D drawings, material usage lists, QA documentation and analyses of consumables used during fabrication. Important chemical information still resides in archived hardware, paints and lubricants, material coupons, cleaning coupons, environmental witness plates and reference materials from manufacturing facilities. Purity and cleanliness of collector substrates. Semi-conductor vendors provided surface cleanliness data and some purity data. Purity for specific elements of interest was verified by science team members in their laboratories [4]. Curation archived procurement and shipping records, analysis reports, and non-proprietary fabrication data. A physical archive of flight collector reference materials is maintained for future use so additional data can be collected as analytical techniques improve. These are of increased value due to the hard landing upon re-entry. Cleaning and cleanliness assessments of flight hardware. Cleaning of the science canister payload was performed at JSC in a dedicated ISO 4 cleanroom using ultrapure water (UPW). The cleanliness of this UPW was monitored throughout processing. The archive for the clean lab also includes airborne particle counts, airborne molecular and inorganic contamination measurements as well as cleanroom construction material coupons and witness coupons. Hardware cleanliness was assessed by particle counts in rinse water batches. This information is recorded in batch cleaning forms and logbooks, and are, perhaps, of decreased value due to the hard landing. Post-flight: Curation-generated data. The curation handling history of each Genesis sample is documented in a typical astromaterials sample database which captures sample location, physical description and characterization data. Samples have a “shelf life”. Crucial to the preservation of samples is ongoing documentation of the sample environment, initially under curatorial control but is now a separate facility function with requires coordination. PI-generated data. Data on sample characterization and cleaning techniques continues to be generated by sample users [5]. These are often captured in LPSC abstracts, but these “engineering” results often are not publishable as stand-alone papers. We are actively looking for ways to make this information more accessible to users. Ion implants into samples have aided science return and can be shared among investigators. These (and similar) materials should be added to the curatorial collection with appropriate process and characterization data generated externally. Summary: Complete data archives for returned astromaterial samples must be broad in types and formats, and inclusive of environmental monitoring.

Genesis↗
DOE OSTI2021

Multi-barrier wellbore integrity inspection system with eccentricity correction

A downhole inspection system includes a neutron imaging device operable to generate data for detecting potential wellbore anomalies and an electromagnetic imaging device operable to generate data for detecting potential wellbore eccentricity. The neutron imaging device includes a neutron generator operable to emit neutrons, and a neutron detector fixed relative to the neutron generation unit and operable to detect backscattered neutrons from a surrounding environment. The electromagnetic imaging device includes at least one transmitter for generating electromagnetic pulse, and at least one receiver for detecting returning electromagnetic pulse. Correlation of the neutron imaging data with the electromagnetic imaging data provides additional data regarding the potential wellbore anomalies.

Kasten, Ansas Matthias↗
DOE OSTI2016

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the true positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report

Constructing accurate statistical models of critical system responses typically requires an enormous amount of data from physical experiments or numerical simulations. Unfortunately, data generation is often expensive and time consuming. To streamline the data generation process, optimal experimental design determines the 'best' allocation of experiments with respect to a criterion that measures the ability to estimate some important aspect of an assumed statistical model. While optimal design has a vast literature, few researchers have developed design paradigms targeting tail statistics, such as quantiles. In this project, we tailored and extended traditional design paradigms to target distribution tails. Our approach included (i) the development of new optimality criteria to shape the distribution of prediction variances, (ii) the development of novel risk-adapted surrogate models that provably overestimate certain statistics including the probability of exceeding a threshold, and (iii) the asymptotic analysis of regression approaches that target tail statistics such as superquantile regression. To accompany our theoretical contributions, we released implementations of our methods for surrogate modeling and design of experiments in two complementary open source software packages, the ROL/OED Toolkit and PyApprox.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Effect of Environment on Fatigue Behavior of a Nicalon(TM)/Si-N-C Ceramic Matrix Composite

The effect of environmental exposure on the fatigue life of Nicalon(TM) /Si-N-C composite was investigated in this study. Test specimens with arrays of 1.8 mm diameter holes and two different open areas, 25 and 35%, were machined. Three environmental conditions were studied: 1) continuous fatigue cycling in air, 2) fatigue cycling in air alternating with humidity exposure, and 3) fatigue cycling in air alternating with exposure to a salt-fog environment. All fatigue testing on specimens with holes was performed with a load ratio, R = 0.05, and at a temperature of 910 C. In general, fatigue lives were shortest for specimens subjected to salt-fog exposure and longest for specimens subjected to continuous fatigue cycling in air. The fatigue data generated on the specimens with holes were compared with fatigue data generated in air on specimens with no holes. Fatigue strength reduction factors for different environmental conditions and open areas investigated in the study were calculated for the Nicalon(TM) /Si-N-C composite.

Kalluri, Sreeramesh↗
DOE OSTI2025

Data-Driven State of Health Estimation for Second-Life Batteries Using Interpolated Synthetic Data and Feature Selection

Accurate estimation of the State of Health (SOH) for second-life batteries (SLBs) is crucial given their increasing use in energy storage applications. Precise SOH prediction is essential for safe operation and robust battery management systems. A major challenge is the limited availability of datasets for building reliable degradation models. To address this, synthetic data generation through linear interpolation is performed to extend the available data, making it more representative of real-world battery operating conditions. By analyzing feature correlation with SOH, the most relevant features are selected for the model. The proposed approach employs a convolutional neural network (CNN) model trained on this interpolated, feature-selected dataset, using time series data of voltage, temperature, and current over a cycle. By focusing on highly correlated features, the model achieves over 95% accuracy, with mean absolute error and root mean squared error up to 2.27% and 2.64%, respectively, in SOH estimation for two battery datasets tested. These results highlight the potential of combining synthetic data generation and feature selection to enhance SOH predictions, showcasing the superior performance of the proposed CNN model for both new batteries and SLBs.

feature selection↗
NASA NTRS2002

Reproducibility and Repeatability of Tensile and Low-Cycle Fatigue Properties in Propulsion Grade Hydrogen

Hydrogen has the potential of increased use in the future as an environmentally friendly fuel. It has, however, shown a tendency to embrittle some materials. To be used in a safe manner and to exploit its full potential, it will be necessary to develop a database of material properties in hydrogen environment. The tests needed to produce this data are costly to perform (tensile test cost 25 times more and low cycle fatigue test are 55 times as expensive). Moreover, there is presently a lack of universal test methods to ensure standardized data within the hydrogen community. Each of the industries that work with hydrogen (aerospace, petroleum, fuel cells, etc.) performs tests by their own laboratory-developed methods, thus rendering cross- comparisons of material property data highly questionable. It is extremely important that data generated in a hydrogen environment be done to a standard that reduces variance to a minimum and allows direct comparison of test results from different laboratories. Doing so will assure that all data generated can be used to further our understanding of the hydrogen effects and to make sure components/products designed for hydrogen are the safest and most reliable possible. This paper reviews the results of two 'round-robin' programs conducted by NASA-MSFC. These two programs examined the reproducibility and repeatability of tensile and low-cycle fatigue test results in high-pressure hydrogen environments. The studies indicated that even with the tightest controls available from current commercial standards, the reproducibility (between different laboratories) and repeatability (within a laboratory) results of the tensile tests exhibited five times the variance as in standard ambient air tests. The variance with the LCF tests were on the same order as with air tests, but that was due to the large variation present in the last Interlaboratory air program. The paper concludes with a recommendation for a program that would allow the development of improved test methods, leading to lower variance in the generation of mechanical property data in the future.

Vesely, E. J.↗
DOE OSTI2014

The OME Framework for genome-scale systems biology

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Adaptive Generation of Training Data for ML Reduced Model Creation

Machine learning proxy models are often used to speed up or completely replace complex computational models. The greatly reduced and deterministic computational costs enable new use cases such as digital twin control systems and global optimization. The challenge of building these proxy models is generating the training data. A naive uniform sampling of the input space can result in a non-uniform sampling of the output space of a model. This can cause gaps in the training data coverage that can miss finer scale details resulting in poor accuracy. While larger and larger data sets could eventually fill in these gaps, the computational burden of full-scale simulation codes can make this prohibitive. In this paper, we present an adaptive data generation method that utilizes uncertainty estimation to identify regions where training data should be augmented. By targeting data generation to areas of need, representative data sets can be generated efficiently. The effectiveness of this method will be demonstrated on a simple one-dimensional function and a complex multidimensional physics model.

Cianciosa, Mark↗
NASA NTRS1988

Modeling and data analysis of the NASA-WSTF frictional heating apparatus - Effects of test parameters on friction coefficient

A theoretical model is being developed jointly by the NASA White Sands Test Facility (WSTF) and the University of California at Santa Barbara (UCSB) to analyze data generated from the WSTF frictional heating test facility. Analyses of the data generated in the first seconds of the frictional heating test are shown to be effective in determining the friction coefficient between the rubbing interfaces. Different friction coefficients for carobn steel and Monel K-500 are observed. The initial condition of the surface is shown to affect only the initial value of the friction coefficient but to have no significant influence on the average steady-state friction coefficient. Rotational speed and the formation of oxide film on the rotating surfaces are shown to have a significant effect on the friction coefficient.

Zhu, Sheng-Hu↗
DOE OSTI2023

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗
DOE OSTI2023

ORNL_AISD_NiPt_108atoms

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for crystal structures with 108 atoms with 1,900 configurations. The data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system 'MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001' [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in a compressed zipped folders atoms108.zip. The zipped folder contains the data structured in the following way: - Ni_ground_state.cfg --> atomic configuration for the pure nickel - Pt_ground_state.cfg --> atomic configuration for the pure platinum - Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder - Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms108.zip is 66,132. This dataset is an extension to the dataset ORNL_AISD_NiPt [5] that has been previously released with crystal structures of 256 atoms, 864 atoms, and 2,048 atoms, with the same methodology for data collection. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D [5] M. Karabin, M. Lupo Pasini, and M. Eisenbach. ORNL_AISD_NiPt. United States: N. p., 2023. Web. doi:10.13139/OLCF/1958172.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pooling Data Improves Multimodel IDF Estimates over Median-Based IDF Estimates: Analysis over the Susquehanna and Florida

Traditional multimodel methods for estimating future changes in precipitation intensity, duration, and frequency (IDF) curves rely on mean or median of models’ IDF estimates. Such multimodel estimates are impaired by large estimation uncertainty, shadowing their efficacy in planning efforts. Here, assuming that each climate model is one representation of the underlying data generating process, i.e., the Earth system, we propose a novel extension of current methods through pooling model data: (i) evaluate performance of climate models in simulating the spatial and temporal variability of the observed annual maximum precipitation (AMP), (ii) bias-correct and pool historical and future AMP data of reasonably performing models, and (iii) compute IDF estimates in a nonstationary framework from pooled historical and future model data. Pooling enhances fitting of the extreme value distribution to the data and assumes that data from reasonably performing models represent samples from the “true” underlying data generating distribution. Through Monte Carlo simulations with synthetic data, we show that return periods derived from pooled data have smaller biases and lesser uncertainty than those derived from ensembles of individual model data. We apply this method to NA-CORDEX models to estimate changes in 24-h precipitation intensity–frequency (PIF) estimates over the Susquehanna watershed and Florida peninsula. Our approach identifies significant future changes at more stations compared to median-based PIF estimates. The analysis suggests that almost all stations over the Susquehanna and at least two-thirds of the stations over the Florida peninsula will observe significant increases in 24-h precipitation for 2–100-yr return periods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Effects of nonlinear aerodynamics and static aeroelasticity on mission performance calculations for a fighter aircraft

During conceptual design studies of advanced aircraft, the usual practice is to use linear theory to calculate the aerodynamic characteristics of candidate rigid (nonflexible) geometric external shapes. Recent developments and improvements in computational methods, especially computational fluid dynamics (CFD), provide significantly improved capability to generate detailed analysis data for the use of all disciplines involved in the evaluation of a proposed aircraft design. A multidisciplinary application of such analysis methods to calculate the effects of nonlinear aerodynamics and static aeroelasticity on the mission performance of a fighter aircraft concept is described. The aircraft configuration selected for study was defined in a previous study using linear aerodynamics and rigid geometry. The results from the previous study are used as a basis of comparison for the data generated herein. Aerodynamic characteristics are calculated using two different nonlinear theories, potential flow and rotational (Euler) flow. The aerodynamic calculations are performed in an iterative procedure with an equivalent plate structural analysis method to obtain lift and drag data for a flexible (nonrigid) aircraft. These static aeroelastic data are then used in calculating the combat and mission performance characteristics of the aircraft.

Giles, Gary L.↗
DOE OSTI2017

Event generator tuning using Bayesian optimization

Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.

47 OTHER INSTRUMENTATION↗
NASA NTRS1981

An algorithm to generate input data from meteorological and space shuttle observations to validate a CH4-CO model

Objective procedures to analyze data from meteorological and space shuttle observations to validate a three dimensional model were investigated. The transport and chemistry of carbon monoxide and methane in the troposphere were studied. Four aspects were examined: (1) detailed evaluation of the variational calculus procedure, with the equation of continuity as a strong constraint, for adjustment of global tropospheric wind fields; (2) reduction of the National Meteorological Center (NMC) data tapes for data input to the OSTA-1/MAPS Experiment; (3) interpolation of the NMC Data for input to the CH4-CO model; and (4) temporal and spatial interpolation procedures of the CO measurements from the OSTA-1/MAPS Experiment to generate usable contours of the data.

Peters, L. K.↗
NASA NTRS2011

Ares I-X Range Safety Simulation and Analysis IV and V

NASA s Ares I-X vehicle launched on a suborbital test flight from the Eastern Range in Florida on October 28, 2009. NASA generated a Range Safety (RS) product data package to meet the RS trajectory data requirements defined in the Air Force Space Command Manual (AFSPCMAN) 91-710. Some products included were a nominal ascent trajectory, ascent flight envelopes, and malfunction turn data. These products are used by the Air Force s 45th Space Wing (45SW) to ensure public safety and to make flight termination decisions on launch day. Due to the criticality of the RS data, an independent validation and verification (IV&V) effort was undertaken to accompany the data generation analyses to ensure utmost data quality and correct adherence to requirements. As a result of the IV&V efforts, the RS product package was delivered with confidence that two independent organizations using separate simulation software generated data to meet the range requirements and yielded similar results. This document captures the Ares I-X RS product IV&V analysis, including the methodology used to verify inputs, simulation, and output data for certain RS products. Additionally a discussion of lessons learned is presented to capture advantages and disadvantages to the IV&V processes used.

Merry, Carl M.↗