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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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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
DOE OSTI2019

Financial Analysis of Experimental Releases Conducted at Glen Canyon Dam during Water Year 2017

This report examines the financial implications of the high-flow experiment (HFE) conducted at Glen Canyon Dam (GCD) during water year (WY) 2017. It is the eighth in a series of reports examining the financial implications of experimental flows conducted since the 1996 Record of Decision (ROD) was adopted in February 1997 (Reclamation 1996). The 1996 ROD implemented the Modified Low Fluctuating Flow (MLFF) regime. This is the first report since the 2016 ROD was adopted in January 2017 (Reclamation 2016). The 2016 ROD implemented the Long-Term Experimental and Management Plan (LTEMP) regime for monthly water releases, daily and hourly operating criteria, and experimental releases. A report released in January 2011 examined WYs 1997 to 2005 (Veselka et al. 2011); a report released in August 2011 examined WYs 2006 to 2010 (Poch et al. 2011); a report released in June 2012 examined WY 2011 (Poch et al. 2012); a report released in April 2013 examined WY 2012 (Poch et al. 2013); a report released in June 2014 examined WY 2013 (Graziano et al. 2014); a report released in September 2015 examined WY 2014 (Graziano et al. 2015); and a report released in November 2016 examined WY 2015 (Graziano et al. 2016). An experimental release may have either a positive or a negative impact on the financial value of energy production. Only one experimental release was conducted at GCD in WY 2017, specifically, a HFE release in November 2016. For this experimental release, financial costs of approximately $1.15 million were incurred because the HFE required sustained water releases exceeding the power plant’s maximum flow rate. In addition, during the month of the experiment, operators were not allowed to shape GCD power production, neither to follow firm electric service (FES) customer day-ahead energy deliveries nor to respond to market prices. This study identifies the main factors contributing to HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate financial impacts by simulating GCD operations under two scenarios: (1) a Baseline scenario that mimics HFE operations both during the experiment and during the rest of the year when it complies with the 1996 daily/hourly operating criteria and the 2016 ROD monthly water release mandates, and (2) a counterfactual Without Experiments scenario identical to the Baseline scenario except it assumes that the HFE did not occur. The Generation and Transmission Maximization Superlite (GTMax SL) model was the main simulation tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. GCD is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). In the modeling process the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and Western Area Power Administration’s (WAPA’s) power purchase and sale prices. In addition to estimating the financial impact of the HFE, the team used the GTMax SL model to gain insights into the interplay among ROD operating criteria, exceptions made to criteria to accommodate the experimental releases, and WAPA operating practices.

13 HYDRO ENERGY↗
DOE OSTI2023

Coordination and divergence in community assembly processes across co-occurring microbial groups separated by cell size

Setting the pace of life and constraining the role of members in food webs, body size can affect the structure and dynamics of communities across multiple scales of biological organization (e.g., from the individual to the ecosystem). However, its effects on shaping microbial communities, as well as underlying assembly processes, remain poorly known. Here, we analyzed microbial diversity in the largest urban lake in China and disentangled the ecological processes governing microbial eukaryotes and prokaryotes using 16S and 18S amplicon sequencing. We found that pico/nano-eukaryotes (0.22–20 μm) and micro-eukaryotes (20–200 μm) showed significant differences in terms of both community composition and assembly processes even though they were characterized by similar phylotype diversity. We also found scale dependencies whereby micro-eukaryotes were strongly governed by environmental selection at the local scale and dispersal limitation at the regional scale. Interestingly, it was the micro-eukaryotes, rather than the pico/nano-eukaryotes, that shared similar distribution and community assembly patterns with the prokaryotes. This indicated that assembly processes of eukaryotes may be coupled or decoupled from prokaryotes’ assembly processes based on eukaryote cell size. While the results support the important influence of cell size, there may be other factors leading to different levels of assembly process coupling across size classes. Additional studies are needed to quantitatively parse the influence of cell size versus other factors as drivers of coordinated and divergent community assembly processes across microbial groups. Regardless of the governing mechanisms, our results show that there are clear patterns in how assembly processes are coupled across sub-communities defined by cell size. These size-structured patterns could be used to help predict shifts in microbial food webs in response to future disturbance.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Processing TES Level-2 Data

TES Level 2 Subsystem is a set of computer programs that performs functions complementary to those of the program summarized in the immediately preceding article. TES Level-2 data pertain to retrieved species (or temperature) profiles, and errors thereof. Geolocation, quality, and other data (e.g., surface characteristics for nadir observations) are also included. The subsystem processes gridded meteorological information and extracts parameters that can be interpolated to the appropriate latitude, longitude, and pressure level based on the date and time. Radiances are simulated using the aforementioned meteorological information for initial guesses, and spectroscopic-parameter tables are generated. At each step of the retrieval, a nonlinear-least-squares- solving routine is run over multiple iterations, retrieving a subset of atmospheric constituents, and error analysis is performed. Scientific TES Level-2 data products are written in a format known as Hierarchical Data Format Earth Observing System 5 (HDF-EOS 5) for public distribution.

Poosti, Sassaneh↗
DOE OSTI2025

Financial Analysis of the High Flow Experiment conducted at the Glen Canyon Dam during Water Year 2023

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specified criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report examines the financial implications of the high flow experiment (HFE) conducted at GCD during the spring of Water Year (WY) 2023 as required by the LTEMP HFE Protocol. This report is part of a series of reports that describe the financial costs of LTEMP experimental releases since the 2016 ROD was adopted in January 2017. Previous reports analyzed the impact of several past HFEs and Bug Flow Experiments. This report focuses on the HFE conducted in April 2023. For this experimental release, financial costs of approximately $1.33 million were incurred because the HFE required sustained water releases exceeding the power plant’s maximum turbine flow rate. In addition, during the experiment, operators were not allowed to shape GCD power production, either to follow Firm Electric Service (FES) customer day-ahead energy deliveries or to respond to market prices. This study identifies the main factors contributing to the HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate Western Area Power Administration (WAPA) financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the operations that actually occurred and (2) a “Without Experiment” case that simulates operations under the assumption that the HFE did not occur. The “With Experiment” case mimics operations during the HFE and the entire month the HFE occurred. It complies with LTEMP hourly and daily operating criteria. The “Without Experiment” case assumes that the HFE did not occur. The monthly water release volume is assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices. In addition to estimating the financial impact of the HFE, the team used the CRiSPPy model to gain insights into the interplay among ROD operating criteria, exceptions made to criteria to accommodate the HFE, and WAPA operating practices.

13 HYDRO ENERGY↗
DOE OSTI2021

Curating a comprehensive set of enzymatic reaction rules for efficient novel biosynthetic pathway design

Enzyme substrate promiscuity has significant implications for metabolic engineering. The ability to predict the space of possible enzymatic side reactions is crucial for elucidating underground metabolic networks in microorganisms, as well as harnessing novel biosynthetic capabilities of enzymes to produce desired chemicals. Reaction rule-based cheminformatics platforms have been implemented to computationally enumerate possible promiscuous reactions, relying on existing knowledge of enzymatic transformations to inform novel reactions. However, past versions of curated reaction rules have been limited by a lack of comprehensiveness in representing all possible transformations, as well as the need to prune rules to enhance computational efficiency in pathway expansion. To this end, we curated a set of 1224 most generalized reaction rules, automatically abstracted from atom-mapped MetaCyc reactions and verified to uniquely cover all common enzymatic transformations. Additionally, we developed a framework to systematically identify and correct redundancies and errors in the curation process, resulting in a minimal, yet comprehensive, rule set. These reaction rules were capable of reproducing more than 85% of all reactions in the KEGG and BRENDA databases, for which a large fraction of reactions is not present in MetaCyc. Our rules exceed all previously published rule sets for which reproduction was possible in this coverage analysis, which allows for the exploration of a larger space of known enzymatic transformations. By leveraging the entire knowledge of possible metabolic reactions through generalized enzymatic reaction rules, we are able to better utilize underground metabolic pathways and accelerate novel biosynthetic pathway design to enable bioproduction towards a wider range of new molecules.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

Validation of SAM 2 and SAGE satellite

Presented are the results of a validation study of data obtained by the Stratospheric Aerosol and Gas Experiment I (SAGE I) and Stratospheric Aerosol Measurement II (SAM II) satellite experiments. The study includes the entire SAGE I data set (February 1979 - November 1981) and the first four and one-half years of SAM II data (October 1978 - February 1983). These data sets have been validated by their use in the analysis of dynamical, physical and chemical processes in the stratosphere. They have been compared with other existing data sets and the SAGE I and SAM II data sets intercompared where possible. The study has shown the data to be of great value in the study of the climatological behavior of stratospheric aerosols and ozone. Several scientific publications and user-oriented data summaries have appeared as a result of the work carried out under this contract.

Kent, G. S.↗
NASA NTRS1993

PILOT: An intelligent distributed operations support system

The Real-Time Data System (RTDS) project is exploring the application of advanced technologies to the real-time flight operations environment of the Mission Control Centers at NASA's Johnson Space Center. The system, based on a network of engineering workstations, provides services such as delivery of real time telemetry data to flight control applications. To automate the operation of this complex distributed environment, a facility called PILOT (Process Integrity Level and Operation Tracker) is being developed. PILOT comprises a set of distributed agents cooperating with a rule-based expert system; together they monitor process operation and data flows throughout the RTDS network. The goal of PILOT is to provide unattended management and automated operation under user control.

Rasmussen, Arthur N.↗
NASA NTRS2003

2XXX Aluminum Self Reacting Friction Stir Weld Development

Weld process development are: (1) Execute a two-phased design of experiment (DOE) approach: process DOE to establish rotation and travel speeds and forge load;set-up DOE to establish allowable gap and centerline offset. (2) Determine the effect of process parameters on strength and weld quality: room and -320 deg F tensile testing; metalllurgical and NDE evaluation. (3) Weld quality goals: visual and radiographic acceptable; room temperature ultimate strength.

Brown, Randy J.↗
NASA NTRS2021

Compositional Realizability Checking within FRET

A set of requirements for a reactive system is realizable if, for any sequence of inputs that satisfy the assumptions on the environment, the guarantees always hold. Realizability checking is essential to ensure that an implementation can be constructed that satisfies the requirements. We propose a framework that supports users in the non-trivial task of developing realizable requirements. Our framework uses architectural information to automatically de-compose a set of requirements into subsets that can be analyzed separately, and therefore more efficiently. It then integrates existing algorithms in order to detect unrealizability, identify minimal sets of conflicting requirements, and compute counterexamples. The capability to focus on minimal conflict sets is key for localizing and correcting the sources of unrealizability. Our approach supports this process by enabling users to interactively visualize and explore the produced conflict sets and counterexamples. We have implemented our framework in the open-source Formal Requirements Elicitation Tool (FRET), and have used it on a variety of industrial-level case studies, showcasing the strengths of our approach in terms of raw performance, as well as diagnostic potential.

FRET↗
NASA NTRSDate not supplied

Performance of Coupled Physics Solvers for Multidisciplinary Hypersonic Flow Simulations on Several Classes of Computer Architectures

The application of hypersonic flow simulation tools to realistic flight scenarios will require the coupling of multiple physical effects to the baseline fluid dynamics. Such multiphysics effects can include the aerooelastic response of the airframe or engine components, dynamic transport of atmospheric particles, the deformation of solid-fluid interfaces that can ablate, pyrolyze, or erode, as well as a host of other processes, all of which are governed by unique sets of physical equations and models. Coupling multiple (and potentially disparate) physics solvers to a robust compressible flow solver poses additional challenges related to the stability, performance and scalability of the combined solver. The choices made during the software design process can therefore lead to a variation in simulation efficiency across different computer architectures. In this paper, we will consider two representative multiphysics hypersonic flow scenarios: the interaction of solid particulates with the flow field created by a hypersonic lifting body and the aerooelastic deformation of a model airframe under high-Mach-number flow conditions. For these simulations we explore the behavior of several hypersonic simulation tools, including Kestrel, FUN3D, US3D, and JENRE multiphysics framework, on several high performance computing systems containing various CPU and GPU architectures.

architecture↗
NASA NTRS1979

Data analysis software for the autoradiographic enhancement process. Volumes 1, 2, and 3, and appendix

The computer software developed to set up a method for Wiener spectrum analysis of photographic films is presented. This method is used for the quantitative analysis of the autoradiographic enhancement process. The software requirements and design for the autoradiographic enhancement process are given along with the program listings and the users manual. A software description and program listings modification of the data analysis software are included.

Singh, S. P.↗
NASA NTRS2015

Development of a Premixed Combustion Capability for Scramjet Combustion Experiments

Hypersonic air-breathing engines rely on scramjet combustion processes, which involve high speed, compressible, and highly turbulent flows. The combustion environment and the turbulent flames at the heart of these engines are difficult to simulate and study in the laboratory under well controlled conditions. Typically, wind-tunnel testing is performed that more closely approximates engine testing rather than a careful investigation of the underlying physics that drives the combustion process. The experiments described in this paper, along with companion data sets being developed separately, aim to isolate the chemical kinetic effects from the fuel-air mixing process in a dual-mode scramjet combustion environment. A unique fuel injection approach is taken that produces a nearly uniform fuel-air mixture at the entrance to the combustor. This approach relies on the precombustion shock train upstream of the dual-mode scramjet combustor. A stable ethylene flame anchored on a cavity flameholder with a uniformly mixed combustor inflow has been achieved in these experiments allowing numerous companion studies involving coherent anti-Stokes Raman scattering (CARS), particle image velocimetry (PIV), and planar laser induced fluorescence (PLIF) to be performed.

Rockwell, Robert D.↗
NASA NTRS2012

Elements of Nondestructive Examination for the Visual Inspection of Composite Structures

Visual inspection (VI) of composite structures provides an effective, wide field survey to ensure design and material compliance is maintained for the entire service life of the manufactured component. Visual inspection is one of the most commonly used nondestructive inspection methods to assess surface defects on composites. By applying visual inspection elements, mechanical damage that could affect component residual strength can be identified and a disposition reached before a potentially catastrophic event occurs. This technique is non-contact and applied at all stages of the composite structure s processing and use. Additionally, VI is required to be performed in all service environments until decommission. By following Level I and Level II damage accept/reject criteria set forth in this document, the material review (MR) process can be initiated. This nondestructive evaluation (NDE) method should be complemented with additional NDE methods to best understand the nature of the observed indications. When VI identification is followed by interrogation using effective complimentary NDE methods, the final Material Review Board (MRB) disposition of the component can be effectively achieved. Although elements of the visual inspection method are discussed and expressly required by the various range standards (KNPR 8715.3 and AFSPCMAN 91-710), emphasis should be placed on supporting the interpretation of recorded visual observations. Sound engineering practices and procedures should be applied with the interpretation of nondestructive testing (NDT) results when the residual strength data specific to a vessel design is incomplete or absent.

Tommy B. Yoder↗
NASA NTRS1995

Design tool for multiprocessor scheduling and evaluation of iterative dataflow algorithms

A graph-theoretic design process and software tool is defined for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.

Jones, Robert L., III↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
DOE OSTI2018

Method of Correlation Coefficient Optimization Used in UV-vis Spectrophotometric Analysis for Effluent in Catalytic Ozonation

A wavelength selection method for spectrophotometric analysis, named correlation coefficient optimization (CCO), was employed for reagent-free analysis of organics (humic acid) in real sewage. The modeling set of CCO uses the effluent in the ozonation process of humic acid (HA) solution. In order to verify the relationship between HA concentration and absorbance at the selected wavelength, HA solutions with different mass concentrations were prepared as a validation set. The study showed that the absorbance at 300 nm could be a good quantitative indication of HA concentration. In addition, the absorbance at 300 nm was applied to analyze the HA concentration in the ozonation process. The decomposition of HA fits the pseudo-first-order kinetic model and has a linear relationship with pH and (T – 20){sup 2} (T is reaction temperature).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2014

Exploration Systems Development (ESD) Approach to Enterprise Risk Management

The National Aeronautics and Space Administration (NASA) Exploration Systems Development (ESD) Division has implemented an innovative approach to Enterprise Risk Management under a unique governance structure and streamlined integration model. ESD's mission is to design and build the capability to extend human existence to deep space. The Enterprise consists of three Programs: Space Launch System (SLS), Orion, and Ground Systems Development and Operations (GSDO). The SLS is a rocket and launch system that will be capable of powering humans, habitats, and support systems to deep space. Orion will be the first spacecraft in history capable of taking humans to multiple destinations within deep space. GSDO is modernizing Kennedy's spaceport to launch spacecraft built and designed by both NASA and private industry. ESD's approach to Enterprise Risk Management is commensurate with affordability and a streamlined management philosophy. ESD Enterprise Risk Management leverages off of the primary mechanisms for integration within the Enterprise. The Enterprise integration approach emphasizes delegation of authority to manage and execute the majority of cross-program activities and products to the individual Programs, while maintaining the overall responsibility for all cross-program activities at the Division. The intent of the ESD Enterprise Risk Management approach is to improve risk communication, to avoid replication and/or contradictory strategies, and to minimize overhead process burden. This is accomplished by the facilitation and integration of risk information within ESD. The ESD Division risks, Orion risks, SLS risks, and GSDO risks are owned and managed by the applicable Program. When the Programs have shared risks with multiple consequences, they are jointly owned and managed. When a risk is associated with the integrated system that involves more than one Program in condition, consequence, or mitigation plan, it is considered an Exploration Systems Integration (ESI) Risk. An ESI risk may require visibility and risk handling by multiple organizations. The Integrated Risk Working Group (IRWG) is a small team of Risk experts that are responsible for collaborating and communicating best practices. In addition, the forum facilitates proper integration of risks across the Enterprise. The IRWG uses a Continuous Risk Management approach for facilitating the identification, analysis, planning, tracking, and controlling of ESI Risks. The ESD Division, Programs, and Integrated Task Teams identify ESI Risks. The IRWG maintains a set of metrics for understanding Enterprise Risk process and the overall Risk Posture. The team is also actively involved in the modeling of risk for Enterprise Performance Management. With the Enterprise being constrained in Schedule and Budget, and with significant technical complexity, the appropriate use of Risk Management techniques is crucial to the success of the Enterprise. The IRWG achieves this through the modified approach, providing a forum for collaboration on risks that cross boundaries between the separate entities.

Bauder, Stephen P.↗