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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 505 records · Page 28

Generating Safety-Critical PLC Code From a High-Level Application Software Specification

The benefits of automatic-application code generation are widely accepted within the software engineering community. These benefits include raised abstraction level of application programming, shorter product development time, lower maintenance costs, and increased code quality and consistency. Surprisingly, code generation concepts have not yet found wide acceptance and use in the field of programmable logic controller (PLC) software development. Software engineers at Kennedy Space Center recognized the need for PLC code generation while developing the new ground checkout and launch processing system, called the Launch Control System (LCS). Engineers developed a process and a prototype software tool that automatically translates a high-level representation or specification of application software into ladder logic that executes on a PLC. All the computer hardware in the LCS is planned to be commercial off the shelf (COTS), including industrial controllers or PLCs that are connected to the sensors and end items out in the field. Most of the software in LCS is also planned to be COTS, with only small adapter software modules that must be developed in order to interface between the various COTS software products. A domain-specific language (DSL) is a programming language designed to perform tasks and to solve problems in a particular domain, such as ground processing of launch vehicles. The LCS engineers created a DSL for developing test sequences of ground checkout and launch operations of future launch vehicle and spacecraft elements, and they are developing a tabular specification format that uses the DSL keywords and functions familiar to the ground and flight system users. The tabular specification format, or tabular spec, allows most ground and flight system users to document how the application software is intended to function and requires little or no software programming knowledge or experience. A small sample from a prototype tabular spec application is shown.

Source record↗

Slicing AADL Specifications for Model Checking

To combat the state-space explosion problem in model checking larger systems, abstraction techniques can be employed. Here, methods that operate on the system specification before constructing its state space are preferable to those that try to minimize the resulting transition system as they generally reduce peak memory requirements. We sketch a slicing algorithm for system specifications written in (a variant of) the Architecture Analysis and Design Language (AADL). Given a specification and a property to be verified, it automatically removes those parts of the specification that are irrelevant for model checking the property, thus reducing the size of the corresponding transition system. The applicability and effectiveness of our approach is demonstrated by analyzing the state-space reduction for an example, employing a translator from AADL to Promela, the input language of the SPIN model checker.

Odenbrett, Maximilian↗

From Goal-Oriented Requirements to Event-B Specifications

In goal-oriented requirements engineering methodologies, goals are structured into refinement trees from high-level system-wide goals down to fine-grained requirements assigned to specific software/ hardware/human agents that can realise them. Functional goals assigned to software agents need to be operationalised into specification of services that the agent should provide to realise those requirements. In this paper, we propose an approach for operationalising requirements into specifications expressed in the Event-B formalism. Our approach has the benefit of aiding software designers by bridging the gap between declarative requirements and operational system specifications in a rigorous manner, enabling powerful correctness proofs and allowing further refinements down to the implementation level. Our solution is based on verifying that a consistent Event-B machine exhibits properties corresponding to requirements.

Aziz, Benjamin↗

Modular Integrated Stackable Layers (MISL) 1.1 Design Specification

This document establishes the design guideline of the Modular Instrumentation Data Acquisition (MI‐DAQ) system in utilization of several designs available in EV. The MI‐ DAQ provides the options to the customers depending on their system requirements i.e. a 28V interface power supply, a low power battery operated system, a low power microcontroller, a higher performance microcontroller, a USB interface, a Ethernet interface, a wireless communication, various sensor interfaces, etc. Depending on customer's requirements, the each functional board can be stacked up from a bottom level of power supply to a higher level of stack to provide user interfaces. The stack up of boards are accomplished by a predefined and standardized power bus and data bus connections which are included in this document along with other physical and electrical guidelines. This guideline also provides information for a new design options. This specification is the product of a collaboration between NASA/JSC/EV and Texas A&M University. The goal of the collaboration is to open source the specification and allow outside entities to design, build, and market modules that are compatible with the specification. NASA has designed and is using numerous modules that are compatible to this specification. A limited number of these modules will also be released as open source designs to support the collaboration. The released designs are listed in the Applicable Documents.

Yim, Hester J.↗

Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Chl-a↗

SLS-SPEC-159 Cross-Program Design Specification for Natural Environments (DSNE) Revision E

The DSNE completes environment-related specifications for architecture, system-level, and lower-tier documents by specifying the ranges of environmental conditions that must be accounted for by NASA ESD Programs. To assure clarity and consistency, and to prevent requirements documents from becoming cluttered with extensive amounts of technical material, natural environment specifications have been compiled into this document. The intent is to keep a unified specification for natural environments that each Program calls out for appropriate application. This document defines the natural environments parameter limits (maximum and minimum values, energy spectra, or precise model inputs, assumptions, model options, etc.), for all ESD Programs. These environments are developed by the NASA Marshall Space Flight Center (MSFC) Natural Environments Branch (MSFC organization code: EV44). Many of the parameter limits are based on experience with previous programs, such as the Space Shuttle Program. The parameter limits contain no margin and are meant to be evaluated individually to ensure they are reasonable (i.e., do not apply unrealistic extreme-on-extreme conditions). The natural environments specifications in this document should be accounted for by robust design of the flight vehicle and support systems. However, it is understood that in some cases the Programs will find it more effective to account for portions of the environment ranges by operational mitigation or acceptance of risk in accordance with an appropriate program risk management plan and/or hazard analysis process. The DSNE is not intended as a definition of operational models or operational constraints, nor is it adequate, alone, for ground facilities which may have additional requirements (for example, building codes and local environmental constraints). "Natural environments," as the term is used here, refers to the environments that are not the result of intended human activity or intervention. It consists of a variety of external environmental factors (most of natural origin and a few of human origin) which impose restrictions or otherwise impact the development or operation of flight vehicles and destination surface systems.

Roberts, Barry C.↗

Improved Rice Residue Burning Emissions Estimates: Accounting for Practice-Specific Emission Factors in Air Pollution Assessments of Vietnam

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for Particulate Matter less than 2.5 microns (PM2.5). We found significant differences in the resulting burning-practice specific emission factors, with 16.9 grams per square kilogram (plus or minus 6.9) for pile burning and 8.8 grams per square kilogram (plus or minus 3.5) for non-pile burning. We calculated burning practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 gigagrams of PM2.5 result from the pile burning method and 130 gigagrams result from non-pile burning method, with the most-likely current emission scenario of 150 gigagrams PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 gigagrams PM2.5, which is only 44 percent of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18 percent of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

Air Pollution↗

Projecting Power Converter Specific Power Through 2050 for Aerospace Applications

In order to analyze the potential fuel burn benefit from the electrification of aircraft powertrains, it is important to quantify the amount of weight that will be added to the aircraft for each additional component of the electric powertrain. This paper provides a projection of the specific power and efficiency of power converters, (AC-DC, DC-AC, or DC-DC), through the year 2050. Data was first collected on state of the art power converters in multiple application areas, creating a power converter database. Relevant specific powers were added to a set of historical data from 1976-2020, and then three different logistic curves were fit through the historical data to represent S-curve shaped growth through the year 2050. The three curves were differentiated by conservative, nominal, and aggressive assumptions for the year in which the logistic curve begins to bend down towards slower growth. With a 30% knockdown factor accounting for the additional weight required for a high altitude converter, projections range from the aggressive specific power projection of 52.9 kW/kg in 2050 to a much more conservative specific power of 12 kW/kg in which growth is limited due to certifiability concerns. Little historical data was found on converter efficiencies to project efficiency based on historical trends. Projections are based on expert opinion on yearly decreases in converter losses. 2050 projections range from 0.987 to 0.997.

fuel burn↗

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the Aviation Safety Reporting System (ASRS). Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about weather and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

SafeAeroBERT: Towards a Safety-Informed Aerospace-Specific Language Model

As aviation systems continue to operate with high traffic, large amounts of documents containing safety-relevant data continue to be generated via reporting systems such as the ASRS. Advanced natural language processing techniques, specifically pre-trained language models, have shown great success in domain-specific applications; however, the text in aviation safety reports is inundated with jargon and thus not fully utilized by general pre-trained models. In this research, we work towards developing a safety-informed aerospace-specific language model by pre-training a Bidirectional Encoder Representations from Transformer (BERT) model on reports from the Aviation Safety Reporting System and the National Transportation Safety Board. The resulting model, called SafeAeroBERT, is fine-tuned for the specific task of document classification, and can be further tuned for named-entity recognition, relation detection, information retrieval, and summarization. Results from the classification task are compared between SafeAeroBERT, the base BERT, and SciBERT models and show SafeAeroBERT outperforms the general BERT and SciBERT on classifying reports about human factors, aircraft, and procedure. SafeAeroBERT can be used on custom tasks, not limited to document classification, and is intended to aid an intelligent knowledge manager for safety report repositories.

Aviation↗

Feature identification or classification using task-specific metadata

Innovations in the identification or classification of features in a data set are described, such as a data set representing measurements taken by a scientific instrument. For example, a task-specific processing component, such as a video encoder, is used to generate task-specific metadata. When the data set includes video frames, metadata can include information regarding motion of image elements between frames, or other differences between frames. A feature of the data set, such as an event, can be identified or classified based on the metadata. For example, an event can be identified when metadata for one or more elements of the data set exceed one or more threshold values. When the feature is identified or classified, an output, such as a display or notification, can be generated. Although the metadata may be useable to generate a task-specific output, such as compressed video data, the identifying or classifying is not used solely in production of, or the creation of an association with, the task-specific output.

Teuton, Jeremy R.↗

Feature identification or classification using task-specific metadata

Innovations in the identification or classification of features in a data set are described, such as a data set representing measurements taken by a scientific instrument. For example, a task-specific processing component, such as a video encoder, is used to generate task-specific metadata. When the data set includes video frames, metadata can include information regarding motion of image elements between frames, or other differences between frames. A feature of the data set, such as an event, can be identified or classified based on the metadata. For example, an event can be identified when metadata for one or more elements of the data set exceed one or more threshold values. When the feature is identified or classified, an output, such as a display or notification, can be generated. Although the metadata may be useable to generate a task-specific output, such as compressed video data, the identifying or classifying is not used solely in production of, or the creation of an association with, the task-specific output.

Teuton, Jeremy R.↗

SPC-70692 Rev 0 MARVEL B4C Powder Specification

A. Idaho National Laboratory (INL) is developing a microreactor to produce electrical power utilizing a small nuclear core and Stirling engines under the Microreactor Application Research Validation and Evaluation (MARVEL) program. This procurement specification defines the requirements for procurement of the B4C Powder. B. Any conflict between this specification and referenced Codes and Standards, or any supplementary specifications in the procurement documents requires written clarification from the Contractor prior to proceeding with any work. Any deviation from the procurement documents requires approval by the Contractor with the change request process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Cushing's syndrome mutant PKA L205R exhibits altered substrate specificity

The PKA L205R hotspot mutation has been implicated in Cushing's syndrome through hyperactive gain-of-function PKA signaling; however, its influence on substrate specificity has not been investigated. Here, we employ the Proteomic Peptide Library (ProPeL) approach to create high-resolution models for PKA WT and PKA L205R substrate specificity. We reveal that the L205R mutation reduces canonical hydrophobic preference at the substrate P + 1 position, and increases acidic preference in downstream positions. Using these models, we designed peptide substrates that exhibit altered selectivity for specific PKA variants, and demonstrate the feasibility of selective PKA L205R loss-of-function signaling. Through these results, we suggest that substrate rewiring may contribute to Cushing's syndrome disease etiology, and introduce a powerful new paradigm for investigating mutation-induced kinase substrate rewiring in human disease.

59 BASIC BIOLOGICAL SCIENCES↗

Thermophysical Properties of Cold- and Vacuum Plasma-Sprayed Cu-Cr-X Alloys, NiAl and NiCrAlY Coatings II: Specific Heat Capacity

Part I of the paper discussed the temperature dependencies of the electrical resistivities, thermal conductivities, thermal diffusivities and total hemispherical emissivities of several vacuum plasma-sprayed (VPS) and cold-sprayed (CS) copper alloy monolithic coatings, VPS NiAl, VPS NiCrAlY, extruded GRCop-84 and as-cast Cu-17(wt.%)Cr-5%Al. Part II discusses the temperature dependencies of the constant-pressure specific heat capacities, C{sub P}, of these coatings. The data were empirically regression-fitted with the equation: C{sub P}=AT{sup 4}+BT{sup 3}+CT{sup 2}+DT+Ewhere T is the absolute temperature and A, B, C, D and E are regression constants. The temperature dependencies of the molar enthalpy, molar entropy and Gibbs molar free energy determined from experimental values of molar specific heat capacity are reported. Calculated values of C{sub P} using the Neumann–Kopp (NK) rule were in poor agreement with experimental data. Instead, a modification of the NK rule was found to predict values closer to the experimental data with an absolute deviation less than 6.5%. The specific molar heat capacities for all the alloys did not agree with the Dulong–Petit law, and C{sub P} > 3R, where R is the universal gas constant, were measured for all the alloys except NiAl for which C{sub P} < 3R at all temperatures.

36 MATERIALS SCIENCE↗

On the Size Dependence of Molar and Specific Properties of Independent Nano-phases and Those in Contact with Other Phases

Nano-materials are materials with at least one nano-phase. A nano-phase is a phase with at least one of its dimensions below 100 nm. It is shown here that nano-phases have at least 1% of their atoms along their surface layer. The ratio of surface atoms is proportional to the specific surface area of the phase, defined as the ratio of its surface area to its volume. Each specific/molar property has its bulk value and its surface value for the given phase, being always different, as the energetic states of the atoms in the bulk and in the surface layer of a phase are different. The average specific/molar property of a nano-phase is modeled here as a linear combination of the bulk and surface values of the same property, scaled with the ratio of the surface atoms. That makes the performance of all nano-phases proportional to their specific surface area. As the characteristic size of the nano-phase is inversely proportional to its specific surface area, all specific/molar properties of nano-phases are inversely proportional to the characteristic size of the phase. This is applied to the size dependence of the molar Gibbs energy of the nano-phase, which appears to be in agreement with the thermodynamics of Gibbs. This agreement proves the general validity of the present model on the size dependence of the specific/molar properties of independent nano-phases. It is shown that the properties of nano-phases are different for independent nano-phases (surrounded only by their equilibrium vapor phase) and for nano-phases in multi-phase situations, such as a liquid nano-droplet in the sessile drop configuration.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

EnZymClass: Substrate specificity prediction tool of plant acyl-ACP thioesterases based on ensemble learning

Characterizing the functional properties of plant acyl-ACP thioesterases (TEs), a key enzyme class used in the production of renewable oleochemicals in microbial hosts, experimentally, can be an expensive and time consuming process since it requires manual screening of thousands of candidates in a database. Using amino acid sequence to computationally predict an enzyme’s function might accelerate this process; however obtaining the necessary amount of information on previously characterized enzymes and their respective sequences required by standard Machine Learning (ML) based approaches to accurately infer sequence-function relationships can be prohibitive, especially with a low-throughput testing cycle. Experimental noise, unbalanced dataset where high sequence similarity does not always imply identical functional properties will further prevent robust prediction performance. Herein we present a ML method, Ensemble method for enZyme Classification (EnZymClass), that is specifically designed to address these issues. We used EnZymClass to classify TEs into short, long and mixed free fatty acid substrate specificity categories. While general guidelines for inferring substrate specificity have been proposed before, prediction of chain-length preference from primary sequence has remained elusive for plant acyl-ACP TEs. By applying EnZymClass to a subset of TEs in the ThYme database, we identified two medium chain TEs, ClFatB3 and CwFatB2, with previously uncharacterized activity in E. coli fatty acid production hosts.

59 BASIC BIOLOGICAL SCIENCES↗

Automated bidirectional coupling of multiscale models of aerosol dosimetry: Validation with subject-specific deposition data

Assessing the toxicity of airborne particulate matter or the efficacy of inhaled drug depends upon accurate estimates of deposited fraction of inhaled materials. In silico approaches can provide important insights into site- or airway-specific deposition of inhaled aerosols in the respiratory system. In this study, we improved on our recently developed 3D/1D model that simulate aerosol transport and deposition in the whole lung over multiple breath cycles. A subject-specific multiscale lung model of a healthy male subject using computational fluid-particle dynamics (CFPD) in a 3D model of the oral cavity through the large bronchial airways entering each lobe was bidirectionally coupled with a recently improved Multiple Path Particle Dosimetry (MPPD) model to predict aerosol deposition over the entire respiratory tract over multiple breaths for four conditions matching experimental aerosol exposures in the same subject from which the model was developed. These include two particle sizes (1 and 2.9 μm) and two subject-specific breathing rates of ~300 ml/s (slow breathing) and ~750 ml/s (fast breathing) at a target tidal volume of 1 L. In silico predictions of retained fraction were 0.31 and 0.29 for 1 μm and 0.66 and 0.62 for 2.9 μm during slow and fast breathing, respectively, and compared well with experimental data (1 μm: 0.31 ± 0.01 (slow) and 0.27 ± 0.01 (fast), 2.9 μm: 0.63 ± 0.03 (slow) and 0.68 ± 0.02 (fast)). Furthermore, these results provide a great deal of confidence in the validity and reliability of our approach.

60 APPLIED LIFE SCIENCES↗