Search NASA⌕ Search

SEARCH · Search NASA

Results for “Additive Process Modeling”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

One of the proposed concepts for mitigating the warming effect of increasing greenhouse gases is seeding cirrus cloud with ice nuclei (IN) in order to reduce the lifetime and coverage of cold cirrus that have a net warming impact on the earth's surface. Global model simulations of the net impact of changing upper tropospheric IN have given widely disparate results, partly as a result of poor understanding of ice nucleation processes in the current atmosphere, and partly as a result of poor representation of these processes in global models. Here, we present detailed process-model simulations of tropical tropopause layer (TTL) transport and cirrus formation with ice nuclei properties based on recent laboratory nucleation experiments and field measurements of aerosol composition. The model is used to assess the sensitivity of TTL cirrus occurrence frequency and microphysical properties to the abundance and efficacy of ice nuclei. The simulated cloud properties compared with recent high-altitude aircraft measurements of TTL cirrus and ice supersaturation. We find that abundant effective IN (either from glassy organic aerosols or crystalline ammonium sulfate with concentrations greater than about 100/L) prevent the occurrences of large ice concentration and large ice supersaturations, both of which are clearly indicated by the in situ observations. We find that concentrations of effective ice nuclei larger than about 50/L can drive significant changes in cirrus microphysical properties and occurrence frequency. However, the cloud occurrence frequency can either increase or decrease, depending on the efficacy and abundance of IN added to the TTL. We suggest that our lack of information about ice nuclei properties in the current atmosphere, as well as uncertainties in ice nucleation processes and their representations in global models, preclude meaningful estimates of climate impacts associated with addition of ice nuclei in the upper troposphere. We will briefly discuss the key field measurements needed to constrain ice nucleation processes.

Jensen, Eric↗
NASA NTRS2008

Using LDPC Code Constraints to Aid Recovery of Symbol Timing

A method of utilizing information available in the constraints imposed by a low-density parity-check (LDPC) code has been proposed as a means of aiding the recovery of symbol timing in the reception of a binary-phase-shift-keying (BPSK) signal representing such a code in the presence of noise, timing error, and/or Doppler shift between the transmitter and the receiver. This method and the receiver architecture in which it would be implemented belong to a class of timing-recovery methods and corresponding receiver architectures characterized as pilotless in that they do not require transmission and reception of pilot signals. Acquisition and tracking of a signal of the type described above have traditionally been performed upstream of, and independently of, decoding and have typically involved utilization of a phase-locked loop (PLL). However, the LDPC decoding process, which is iterative, provides information that can be fed back to the timing-recovery receiver circuits to improve performance significantly over that attainable in the absence of such feedback. Prior methods of coupling LDPC decoding with timing recovery had focused on the use of output code words produced as the iterations progress. In contrast, in the present method, one exploits the information available from the metrics computed for the constraint nodes of an LDPC code during the decoding process. In addition, the method involves the use of a waveform model that captures, better than do the waveform models of the prior methods, distortions introduced by receiver timing errors and transmitter/ receiver motions. An LDPC code is commonly represented by use of a bipartite graph containing two sets of nodes. In the graph corresponding to an (n,k) code, the n variable nodes correspond to the code word symbols and the n-k constraint nodes represent the constraints that the code places on the variable nodes in order for them to form a valid code word. The decoding procedure involves iterative computation of values associated with these nodes. A constraint node represents a parity-check equation using a set of variable nodes as inputs. A valid decoded code word is obtained if all parity-check equations are satisfied. After each iteration, the metrics associated with each constraint node can be evaluated to determine the status of the associated parity check. Heretofore, normally, these metrics would be utilized only within the LDPC decoding process to assess whether or not variable nodes had converged to a codeword. In the present method, it is recognized that these metrics can be used to determine accuracy of the timing estimates used in acquiring the sampled data that constitute the input to the LDPC decoder. In fact, the number of constraints that are satisfied exhibits a peak near the optimal timing estimate. Coarse timing estimation (or first-stage estimation as described below) is found via a parametric search for this peak. The present method calls for a two-stage receiver architecture illustrated in the figure. The first stage would correct large time delays and frequency offsets; the second stage would track random walks and correct residual time and frequency offsets. In the first stage, constraint-node feedback from the LDPC decoder would be employed in a search algorithm in which the searches would be performed in successively narrower windows to find the correct time delay and/or frequency offset. The second stage would include a conventional first-order PLL with a decision-aided timing-error detector that would utilize, as its decision aid, decoded symbols from the LDPC decoder. The method has been tested by means of computational simulations in cases involving various timing and frequency errors. The results of the simulations ined in the ideal case of perfect timing in the receiver.

Jones, Christopher↗
NASA NTRS1993

Balloon-borne in situ measurements of ClO and ozone - Implications for heterogeneous chemistry and mid-latitude ozone loss

In situ measurements of chlorine oxide (ClO) obtained on 31 March 1991 with a new balloon-borne instrument are compared to results from a photochemical model which incorporates hydrolysis of N2O5 on sulfate aerosols. With the addition of this process, there is better agreement between calculation and measurement over most of the profile, except below 20 km where observed ClO is greater by as much as a factor of four. In a model which is constrained to reproduce the observed ClO below 20 km, ozone loss by catalytic cycles involving halogen oxides becomes larger than that from NO(x), which would dominate under gas-phase or standard heterogeneous conditions.

Avallone, L. M.↗
DOE OSTI2024

Modeling with uncertainty quantification reveals the essentials of a non-canonical algal carbon-concentrating mechanism

The thermoacidophilic red alga Cyanidioschyzon merolae survives its challenging environment likely in part by operating a carbon-concentrating mechanism (CCM). Here, we demonstrated that C. merolae 's cellular affinity for CO 2 is stronger than the affinity of its rubisco for CO 2 . This finding provided additional evidence that C. merolae operates a CCM while lacking the structures and functions characteristic of CCMs in other organisms. To test how such a CCM could function, we created a mathematical compartmental model of a simple CCM, distinct from those we have seen previously described in detail. The results of our modeling supported the feasibility of this proposed minimal and non-canonical CCM in C. merolae . To facilitate the robust modeling of this process, we measured and incorporated physiological and enzymatic parameters into the model. Additionally, we trained a surrogate machine-learning model to emulate the mechanistic model and characterized the effects of model parameters on key outputs. This parameter exploration enabled us to identify model features that influenced whether the model met the experimentally derived criteria for functional carbon concentration and efficient energy usage. Such parameters included cytosolic pH, bicarbonate pumping cost and kinetics, cell radius, carboxylation velocity, number of thylakoid membranes, and CO 2 membrane permeability. Our exploration thus suggested that a non-canonical CCM could exist in C. merolae and illuminated the essential features generally necessary for CCMs to function.

Steensma, Anne K. [Michigan State Univ., East Lans↗
DOE OSTI2026

A mathematical design framework for membrane pre-concentration in energy-efficient recovery of fermentation products

Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.

09 BIOMASS FUELS↗
NASA NTRS1980

Estimation of Kalman filter model parameters from an ensemble of tests

A methodology for estimating initial mean and covariance parameters in a Kalman filter model from an ensemble of nonidentical tests is presented. In addition, the problem of estimating time constants and process noise levels is addressed. Practical problems such as developing and validating inertial instrument error models from laboratory test data or developing error models of individual phases of a test are generally considered.

Gibbs, B. P.↗
NASA NTRSDate not supplied

Overview of the NASA Terrestrial Environments Support Role: Data and Applications

This presentation focuses on the terrestrial environment component of the Natural Environments Branch’s (NEB’s) support role and highlights the instrumentation and data sources used, how the data are quality controlled and archived, and the analyses and use-cases of these datasets. A detailed overview is provided about some individual data sources that are used by the branch, which includes a network of instruments (e.g., wind towers, balloons, and profilers) and models, such as the Earth Global Reference Atmospheric Model (Earth-GRAM). Additionally, the data archival and quality control processes that maintain the high-quality climatological datasets from these sources are discussed, as are the implemented and pending updates to this process. Examples of the different applications for these datasets are presented to showcase the analytical and operational capabilities of the NEB and demonstrate the culmination of the entire process. This includes the Range Reference Atmospheres created and maintained by the NEB, sea-state analyses for crewed return, certification of observation systems for space flight, and the day-of-launch support process. The NEB at NASA Marshall Space Flight Center (MSFC) supports the NASA Engineering Directorate (ED) and Exploration Systems Development Mission Directorate (ESDMD) by providing the necessary environmental constraints to facilitate the safe design and operation of assets required for space travel. This includes, but is not limited to, the environmental considerations for assets residing at the launch sites, temporarily stationed at a launch site, traversing the [extra-]terrestrial atmosphere and open space, and arriving at their destination. As such, the Terrestrial and Planetary Environments Team within the NEB is but a part of the whole, delegated to quantify the environment that assets may encounter whilst on Earth and within its atmosphere. However, nearly all ESDMD assets are subjected to terrestrial conditions, which cover a diverse range of meteorological regimes and extremes. The team also supports day-of-launch operations for the Space Launch System (SLS), providing real-time monitoring of the winds and thermodynamics along the launch path using an amalgamation of observed, remotely sensed, and modeled output.

Systems Engineering↗
NASA NTRS2024

Effects of Alloying Elements on Twinning in Ni-Based Superalloys

Micro-twinning is the major creep deformation mechanism in Ni-based superalloys at temperatures above 700 C. Recent experiments suggest that superlattice stacking faults in   phase may serve as the precursors to twin formation. Segregation of alloying elements to these precursors may have a significant effect on formation and extension of micro-twins. Using atomistic modeling we investigate and explain the effects of Cr and Nb alloying additions on these processes. Our results help to rationalize the experimentally observed puzzling effects of elemental composition of the alloy on creep resistance.

Ni-based superalloys↗
NASA NTRS1977

Failure detection by pilots during automatic landing - Models and experiments

A model is proposed to describe the pilot as a monitor of automatic landing systems. The failures treated are equivalent to the addition of a dynamic change in the mean of the observation process. The failure detection model of the pilot consists of two stages: a linear estimator (Kalman filter) and a decision mechanism based on sequential analysis. The filter equations are derived from a simplified version of the linearized dynamics of the airplane and the control loop. The perceptual observation noise is modified to include the effects of allocation of attention among the several instruments. The final result is a simple model consisting of a high-pass filter to produce the observation residuals and a decision function which is a pure integration of the residuals minus a bias term. The dynamics of a Boeing 707 were used to simulate the fully coupled final approach in a fixed-base simulator. Observers monitored the approaches and detected the failures; their performance was compared with the predictions of the model.

Gai, E. G.↗
NASA NTRSDate not supplied

A Hybrid Approach to Labeling Datasets in Earth Science Publications

NASA Data Centers provide the public with thousands of datasets that result in published papers, reports, and conference proceedings. Collecting accurate metrics on usage of these datasets is key to connecting different areas of knowledge and evaluating the datasets’ impact. While most of the datasets have Digital Object Identifiers (DOIs) assigned, most publications do not cite them hampering the automated search of these publications. Instead, articles mention attributes like organization, instrument, mission, variable, or a publication describing the dataset. Often only domain experts can deduce the dataset that was used in the publication text. The lack of a citation slows the spread of information and reduces the research’s impact. With thousands of papers produced each year, an automated means of labeling datasets is critical. This paper explores a hybrid approach of heuristics and a Natural Language Processing (NLP) Named Entity Recognition (NER) model to find and label the datasets used within Earth Science papers. Heuristics are used to produce the labelled sentences and any potential dataset candidates that can be derived from a sentence. The heuristic labels the sentences with the names of mission, instrument, re-analysis models, and science keywords taken from the Global Change Master Directory (GCMD) ontology. Additionally, it uses those labels to generate the dataset citation candidates. If the mission, instrument, and variable are sufficient to create the citation for the dataset the citation and the label the domain expert reviews the output without going through the NLP model. If the extracted label is not sufficient to label the dataset on its own, the sentence and its associated dataset labels will be inputted into the NER model. The model outputs the labeled sentence and the potential dataset candidates with their associated probabilities. The domain expert then reviews the NER model’s output and the correct labels are determined. The newly labelled papers can then be used as additional training data. This creates an iterative process for the approach to continuously improve. Because all the possible mentions are gathered by the model, the domain expert can quickly and easily label the papers resulting in large time savings.

Jacob Atkins↗
DOE OSTI2026

Data and Scripts Associated with "Modeling Ecohydrological Responses of Vegetation to Urban Microclimates Using the E3SM Land Model"

This dataset supports the study of vegetation ecohydrological responses to urban microclimates using the land component of the Energy Exascale Earth System Model (ELM) at four urban sites in Knoxville, Tennessee, USA. It includes the model inputs, simulation outputs, and associated scripts for running ELM simulations and analyzing the resulting data. The Model_Inputs folder includes static surface data, satellite-derived phenology (i.e., leaf area index), and atmospheric forcing data used to drive ELM simulations. Detailed descriptions of these datasets are provided in Section 2.3.2 of the associated manuscript. The Model_Outputs folder contains simulation results for the baseline, treatment, and ensemble experiments. Outputs from the baseline and treatment simulations are provided as raw ELM NetCDF files. Because the raw outputs from the 4,000-member ensemble are prohibitively large, the ensemble results are provided as summarized CSV files, which also serve as the source data for Figure 5 of the associated manuscript. The Scripts folder contains three components: E3SM, the core codebase of the Energy Exascale Earth System Model (E3SM); elm-olmt, the Offline Land Model Testbed (OLMT) used to perform the simulations; and knoxville_elm, which contains the analysis scripts used to process model outputs and generate the figures and results presented in the associated manuscript. Additional information is provided in Scripts_readme.txt within the Scripts directory.

Lu, Xiaoman [ORNL] (ORCID:0000000306698780)↗
NASA NTRS2009

Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.

Dreher, Joseph G.↗
NASA NTRS1978

Rocket exhaust ground cloud/atmospheric interactions

An attempt to identify and minimize the uncertainties and potential inaccuracies of the NASA Multilayer Diffusion Model (MDM) is performed using data from selected Titan 3 launches. The study is based on detailed parametric calculations using the MDM code and a comparative study of several other diffusion models, the NASA measurements, and the MDM. The results are discussed and evaluated. In addition, the physical/chemical processes taking place during the rocket cloud rise are analyzed. The exhaust properties and the deluge water effects are evaluated. A time-dependent model for two aerosol coagulations is developed and documented. Calculations using this model for dry deposition during cloud rise are made. A simple model for calculating physical properties such as temperature and air mass entrainment during cloud rise is also developed and incorporated with the aerosol model.

Hwang, B.↗
NASA NTRS2010

TEAMS Model Analyzer

The TEAMS model analyzer is a supporting tool developed to work with models created with TEAMS (Testability, Engineering, and Maintenance System), which was developed by QSI. In an effort to reduce the time spent in the manual process that each TEAMS modeler must perform in the preparation of reporting for model reviews, a new tool has been developed as an aid to models developed in TEAMS. The software allows for the viewing, reporting, and checking of TEAMS models that are checked into the TEAMS model database. The software allows the user to selectively model in a hierarchical tree outline view that displays the components, failure modes, and ports. The reporting features allow the user to quickly gather statistics about the model, and generate an input/output report pertaining to all of the components. Rules can be automatically validated against the model, with a report generated containing resulting inconsistencies. In addition to reducing manual effort, this software also provides an automated process framework for the Verification and Validation (V&V) effort that will follow development of these models. The aid of such an automated tool would have a significant impact on the V&V process.

Tijidjian, Raffi P.↗
DOE OSTI2024

Impact of Dilute DIO Additive on Local Microstructure of Fluorinated, pNDI‐Based Polymer Solar Cells

The performance of all‐polymer solar cells is often enhanced by incorporating solvent additives during solution processing. Here, in particular, blends based on the model all‐polymer system PBDBT:N2200 have been shown to have increased short‐circuit current and fill factor when processed with dilute diiodooctane (DIO). However, the morphological mechanism that drives the increase in performance is often not well understood due to limitations in common characterization techniques. In this study, it is shown that a combination of X‐ray techniques with cryogenic high‐resolution transmission electron microscopy (HRTEM) analysis can provide a quantitative and spatially resolved picture of polymer chain orientation and alignment in all‐polymer blends. It is found that DIO induces vertical phase separation in PBDBT‐2F:F‐N2200 and increases donor crystallite thickness in the pi‐stacking direction leading to an acceptor‐rich film surface. However, it is also shown that DIO does not disrupt the formation of face‐on donor–acceptor interfaces. These findings suggest that dilute DIO primarily affects crystalline domain formation in single component regions as opposed to mixed regions; thus, dilute DIO can impact vertical charge transport pathways without sacrificing donor–acceptor interfacial connectivity.

Cheng, Christina↗
DOE OSTI2025

Benchmark Gap Assessment for the Manufacturing of High-Assay Low-Enriched Uranium Fuels

This document develops basic critical conditions for spheres—moderated and unmoderated, as well as reflected and unreflected—in consideration of nuclear criticality safety of a potential fuel production facility producing high-assay low-enriched uranium (HALEU) fuel of several different types like tristructural-isotropic (TRISO), uranium metal and alloys, oxide and non-metallic forms. In addition to spherical arrangements, TRISO particle manufacturing process–specific equipment is modeled as it would be for the criticality safety analysis. The objective is to develop representative systems that can then be used for comparison with existing benchmarks. SCALE/TSUNAMI is used to assess the similarity index between these systems to assess validation gaps for possible fuel production applications of proposed advanced reactors. Several different fuel types were evaluated, including TRISO, uranium metal, uranium molybdenum, uranium zirconium, uranium dioxide, uranium nitride, uranium hydride, U-ZrH, and uranium chloride. This selection of fuel types covers a breadth of proposed reactor types, as well as intermediate steps in the production and fabrication of the fuel

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1977

ALTKAL: An optimum linear filter for GEOS-3 altimeter data

ALTKAL is a computer program designed to smooth sea surface height data obtained from the GEOS 3 altimeter, and to produce minimum variance estimates of sea surface height and sea surface slopes, along with their standard derivations. The program operates by processing the data through a Kalman filter in both the forward and backward directions, and optimally combining the results. The sea surface height signal is considered to have a geoid signal, modeled by a third order Gauss-Markov process, corrupted by additive white noise. The governing parameters for the signal and noise processes are the signal correlation length and the signal-to-noise ratio. Mathematical derivations of the filtering and smoothing algorithms are presented. The smoother characteristics are illustrated by giving the frequency response, the data weighting sequence and the transfer function of a realistic steady-state smoother example. Based on nominal estimates for geoidal undulation amplitude and correlation length, standard deviations for the estimated sea surface height and slope are 12 cm and 3 arc seconds, respectively.

Fang, B. T.↗
NASA NTRS1985

Zr-Hf-Ta fractionation during lunar evolution

Zr/Hf ratios and other elemental data in 68 samples of various mare basalts, KREEP units, and lunar glasses have been determined using instrumental neutron activation analysis coupled with coincidence-anticoincidence counting for greater precision. The data are presented in order to quantify further the amount of Zr/Hf fractionation that has occurred during primordial crystallization and cumulate remelting or by any other process. Models of Zr-Hf evolution are developed to place additional constraints on the bulk lunar composition and on the effects of minor phases that may be responsible for the observed fractionations. The Hf-Ta fractionation in lunar compositions is also reviewed in order to characterize normal Hf(4+) versus Ta(4+) behavior and to delineate possible effects due to the oxidation of Ta(4+) to Ta(5+) during late-stage ilmenite crystallization.

Hughes, S. S.↗