Results for “expanded analysis” — Page 23

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRS2018

Improved Mars Helicopter Aerodynamic Rotor Model for Comprehensive Analyses

The Mars Helicopter is part of the NASA Mars 2020 rover mission scheduled to launch in July of 2020. Its goal is to demonstrate the viability and potential of heavier-than-air vehicles in the Martian atmosphere. Ultimately, it aims to bridge the resolution gap between orbiters and the rover as well as allow access to otherwise inaccessible regions. The low density of the Martian atmosphere and the relatively small-scale rotor result in very low Reynolds number flows. The low density and low Reynolds numbers reduce the lifting force and lifting efficiency, respectively. This paper describes the generation of the improved Mars Helicopter aerodynamic rotor model. The goal is to generate a performance model for the Mars Helicopter rotor using a free wake analysis, since this has a low computational cost for design. The improvements in the analysis are two-fold and are expanded on from two prior publications. First, the fidelity of the simulations is increased by performing higher-order two-dimensional time-accurate OVERFLOW simulations allowing for higher accuracy aerodynamic coefficients and a better understanding of the boundary layer behavior as well as its transient features. Second, a version of the model is generated to duplicate the exact testing conditions in the 25–ft. diameter Space Simulator at the Jet Propulsion Laboratory, which allows for better correlation of rotor performance figures. Previous work correlated performance with that test, but did not consider the higher temperatures in the experiment compared to those of the Martian atmosphere. The higher temperatures in the experiment are expected to give conservative performance estimates, as they give rise to an increase in speed of sound and decrease in observed Reynolds numbers.

Grip, Håvard F.↗

NASA NTRSDate not supplied

Modeling and Visualization of Geomagnetic Storms at the CCMC

The Community Coordinated Modeling Center is greatly expanding activities in geospace in recent years, including the addition of new models or outputs (including WACCM-X, SAMI3-TIEGCM, HYPERS, GAMERA test runs and WAM-IPE real time outputs) that expand the range of available views or analysis activities in geospace during the upcoming Solar Maximum and Heliophysics Big Year. We are now routinely adding to a library of geomagnetic storms using anew request interface for the Space Weather Modeling Framework(SWMF). We are placing continuous run model simulation outputs as run series onto the CCMC web site where look at quick-look graphics, perform online visualization and request outputs for any day covered by the results.We demonstrate examples and results of online visualization and analysis tools that are also placed onto the cloud to support Open Science and collaborative research.

Lutz Rastaetter↗

DOE OSTI2015

Fissile material found in electrical junction box at nuclear fuel services, Inc. - 14569

On October 29, 2014 at Nuclear Fuel Services, Inc., while troubleshooting a failed heater control circuit, fissile material was found in a small electrical junction box that contained a Resistance Temperature Detector (RTD). The RTD was mounted inside a stainless steel thermowell located in a uranium recovery boildown loop. Over time, the end of the thermowell had become pitted allowing fissile solution to penetrate the thermowell and collect in the electrical junction box. Conduit connected the small electrical junction box to an unfavorable geometry electrical panel, providing a credible scenario where an unsafe volume of fissile liquid could potentially collect in an unfavorable geometry. This postulated upset scenario had not been analyzed by Nuclear Criticality Safety (NCS). Prior to restart of the operation, a corrective action was taken to replace the damaged thermowell. Additionally, a review of other fissile systems was completed to identify all unfavorable geometry electrical panels where the potential for a similar accident scenario existed. Drain holes were drilled in the bottom of all those identified. Analysis of the damaged thermowell is ongoing. Expanded details of the incident, the short term and planned long term corrective actions, and lessons learned are discussed. (authors)

42 ENGINEERING↗

DOE OSTI2015

Life-cycle Analysis of Bioproducts and Their Conventional Counterparts in GREET

To further expand upon the literature in this field and to develop a platform for bioproduct LCA, we developed LCA results for ten bioproducts produced either from algal glycerol or from corn stover-derived sugars. We used Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREETTM) model as the platform for this study. The data and calculations reported herein are available to GREET users in a bioproducts module included in the fall 2015 GREET release. This report documents our approach to this analysis and the results. In Chapter 2, we review the process we underwent to select the bioproducts for analysis based on market and technology readiness criteria. In Chapter 3, we review key parameters for production of the two feedstocks we considered: corn stover and algae. Given the lack of publicly available information about the production of bioproducts, which is caused in large part by the emerging nature of the industry, we developed Aspen Plus® simulations of the processes that could be used to produce each bioproduct. From these simulations, we extracted the energy and material flows of these processes, which were important inputs to the GREET bioproducts module. Chapter 4 provides the details of these Aspen Plus simulations. It is important to compare the LCA results for bioproducts to those for their petroleum counterparts. We therefore also developed material and energy flow data for conventional products based mostly on the literature. These data are described in Chapter 5 and are also included in the GREET bioproducts module. In Chapter 6, we present results from this analysis and examine areas for refinement and future research.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2016

Empirical Analysis and Automated Classification of Security Bug Reports

With the ever expanding amount of sensitive data being placed into computer systems, the need for effective cybersecurity is of utmost importance. However, there is a shortage of detailed empirical studies of security vulnerabilities from which cybersecurity metrics and best practices could be determined. This thesis has two main research goals: (1) to explore the distribution and characteristics of security vulnerabilities based on the information provided in bug tracking systems and (2) to develop data analytics approaches for automatic classification of bug reports as security or non-security related. This work is based on using three NASA datasets as case studies. The empirical analysis showed that the majority of software vulnerabilities belong only to a small number of types. Addressing these types of vulnerabilities will consequently lead to cost efficient improvement of software security. Since this analysis requires labeling of each bug report in the bug tracking system, we explored using machine learning to automate the classification of each bug report as a security or non-security related (two-class classification), as well as each security related bug report as specific security type (multiclass classification). In addition to using supervised machine learning algorithms, a novel unsupervised machine learning approach is proposed. An ac- curacy of 92%, recall of 96%, precision of 92%, probability of false alarm of 4%, F-Score of 81% and G-Score of 90% were the best results achieved during two-class classification. Furthermore, an accuracy of 80%, recall of 80%, precision of 94%, and F-score of 85% were the best results achieved during multiclass classification.

Cybersecurity↗

NASA NTRS1982

IDIMS/GEOPAK: Users manual for a geophysical data display and analysis system

The application of an existing image analysis system to the display and analysis of geophysical data is described, the potential for expanding the capabilities of such a system toward more advanced computer analytic and modeling functions is investigated. The major features of the IDIMS (Interactive Display and Image Manipulation System) and its applicability for image type analysis of geophysical data are described. Development of a basic geophysical data processing system to permit the image representation, coloring, interdisplay and comparison of geophysical data sets using existing IDIMS functions and to provide for the production of hard copies of processed images was described. An instruction manual and documentation for the GEOPAK subsystem was produced. A training course for personnel in the use of the IDIMS/GEOPAK was conducted. The effectiveness of the current IDIMS/GEOPAK system for geophysical data analysis was evaluated.

Libert, J. M.↗

DOE OSTI2016

Stability of stagnation via an expanding accretion shock wave

Stagnation of a cold plasma streaming to the center or axis of symmetry via an expanding accretion shock wave is ubiquitous in inertial confinement fusion (ICF) and high-energy-density plasma physics, the examples ranging from plasma flows in x-ray-generating Z pinches [Maron et al., Phys. Rev. Lett. 111, 035001 (2013)] to the experiments in support of the recently suggested concept of impact ignition in ICF [Azechi et al., Phys. Rev. Lett. 102, 235002 (2009); Murakami et al., Nucl. Fusion 54, 054007 (2014)]. Some experimental evidence indicates that stagnation via an expanding shock wave is stable, but its stability has never been studied theoretically. We present such analysis for the stagnation that does not involve a rarefaction wave behind the expanding shock front and is described by the classic ideal-gas Noh solution in spherical and cylindrical geometry. In either case, the stagnated flow has been demonstrated to be stable, initial perturbations exhibiting a power-law, oscillatory or monotonic, decay with time for all the eigenmodes. This conclusion has been supported by our simulations done both on a Cartesian grid and on a curvilinear grid in spherical coordinates. Dispersion equation determining the eigenvalues of the problem and explicit formulas for the eigenfunction profiles corresponding to these eigenvalues are presented, making it possible to use the theory for hydrocode verification in two and three dimensions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1980

Orbit transfer vehicle engine study. Volume 2: Technical report

The orbit transfer vehicle (OTV) engine study provided parametric performance, engine programmatic, and cost data on the complete propulsive spectrum that is available for a variety of high energy, space maneuvering missions. Candidate OTV engines from the near term RL 10 (and its derivatives) to advanced high performance expander and staged combustion cycle engines were examined. The RL 10/RL 10 derivative performance, cost and schedule data were updated and provisions defined which would be necessary to accommodate extended low thrust operation. Parametric performance, weight, envelope, and cost data were generated for advanced expander and staged combustion OTV engine concepts. A prepoint design study was conducted to optimize thrust chamber geometry and cooling, engine cycle variations, and controls for an advanced expander engine. Operation at low thrust was defined for the advanced expander engine and the feasibility and design impact of kitting was investigated. An analysis of crew safety and mission reliability was conducted for both the staged combustion and advanced expander OTV engine candidates.

Source record↗

DOE OSTI2024

Mo than meets the eye: genomic insights into molybdoenzyme diversity of Seleniivibrio woodruffii strain S4T

Abstract Seleniivibrio woodruffii strain S4T is an obligate anaerobe belonging to the phylum Deferribacterota. It was isolated for its ability to respire selenate and was also found to respire arsenate. The high-quality draft genome of this bacterium is 2.9 Mbp, has a G+C content of 48%, 2762 predicted genes of which 2709 are protein-coding, and 53 RNA genes. An analysis of the genome focusing on the genes encoding for molybdenum-containing enzymes (molybdoenzymes) uncovered a remarkable number of genes encoding for members of the dimethylsulfoxide reductase family of proteins (DMSOR), including putative reductases for selenate and arsenate respiration, as well as genes for nitrogen fixation. Respiratory molybdoenzymes catalyze redox reactions that transfer electrons to a variety of substrates that can act as terminal electron acceptors for energy generation. Seleniivibrio woodruffii strain S4T also has essential genes for molybdate transporters and the biosynthesis of the molybdopterin guanine dinucleotide cofactors characteristic of the active centers of DMSORs. Phylogenetic analysis revealed candidate respiratory DMSORs spanning nine subfamilies encoded within the genome. Our analysis revealed the untapped potential of this interesting microorganism and expanded our knowledge of molybdoenzyme co-occurrence.

Louie, Tiffany S.↗

NASA NTRS2015

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

Knowledge domain↗

NASA NTRS2009

Evaluating Effectiveness of Modeling Motion System Feedback in the Enhanced Hess Structural Model of the Human Operator

In order to use the Hess Structural Model to predict the need for certain cueing systems, George and Cardullo significantly expanded it by adding motion feedback to the model and incorporating models of the motion system dynamics, motion cueing algorithm and a vestibular system. This paper proposes a methodology to evaluate effectiveness of these innovations by performing a comparison analysis of the model performance with and without the expanded motion feedback. The proposed methodology is composed of two stages. The first stage involves fine-tuning parameters of the original Hess structural model in order to match the actual control behavior recorded during the experiments at NASA Visual Motion Simulator (VMS) facility. The parameter tuning procedure utilizes a new automated parameter identification technique, which was developed at the Man-Machine Systems Lab at SUNY Binghamton. In the second stage of the proposed methodology, an expanded motion feedback is added to the structural model. The resulting performance of the model is then compared to that of the original one. As proposed by Hess, metrics to evaluate the performance of the models include comparison against the crossover models standards imposed on the crossover frequency and phase margin of the overall man-machine system. Preliminary results indicate the advantage of having the model of the motion system and motion cueing incorporated into the model of the human operator. It is also demonstrated that the crossover frequency and the phase margin of the expanded model are well within the limits imposed by the crossover model.

Zaychik, Kirill↗

DOE OSTI2015

ß-delayed γ-proton decay in ⁵⁶Zn: Analysis of the charged-particle spectrum

A study of the β decay of the proton-rich T z = –2 nucleus ⁵⁶Zn has been reported in a recent publication. A rare and exotic decay mode, β-de-layed γ-proton decay, has been observed there for the first time in the fp shell. Here, we expand on some of the details of the data analysis, focusing on the charged particle spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Genome sequence, phylogenetic analysis, and structure-based annotation reveal metabolic potential of Chlorella sp. SLA-04

Algae are a broad class of photosynthetic eukaryotes that are phylogenetically and physiologically diverse. Most of the phylogenetic diversity has been inferred from 18S rDNA sequencing since there are only a few complete genomes available in public databases. Here we use ultra-long-read Nanopore sequencing to determine a gapless, telomere-to-telomere complete genome sequence of Chlorella sp. SLA-04, previously described as Chlorella sorokiniana SLA-04. Chlorella sp. SLA-04 is a green alga that grows to high cell density in a wide variety of environments - high and neutral pH, high and low alkalinity, and high and low salinity. SLA-04's ability to grow in high pH and high alkalinity media without external CO 2 supply is favorable for large-scale algal biomass production. Phylogenetic analysis performed using ribosomal DNA and conserved protein sequences consistently reveal that Chlorella sp. SLA-04 forms a distinct lineage from other strains of Chlorella sorokiniana. We complement traditional genome annotation methods with high throughput structural predictions and demonstrate that this approach expands functional prediction of the SLA-04 proteome. Genomic analysis of the SLA-04 genome identifies the genes capable of utilizing TCA cycle intermediates to replenish cytosolic acetyl-CoA pools for lipid production. We also identify a complete metabolic pathway for sphingolipid anabolism that may allow SLA-04 to readily adapt to changing environmental conditions and facilitate robust cultivation in mass production systems. Altogether, this work clarifies the phylogeny of Chlorella sp. SLA-04 within Trebouxiophyceae and demonstrates how structural predictions can be used to improve annotation beyond sequencebased methods.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning

Abstract Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of XAS/EELS data often relies on matching an unknown experimental sample to a series of simulated or experimental standard samples. This limits analysis throughput and the ability to extract quantitative information from a sample. In this work, we have trained a random forest model capable of predicting the oxidation state of copper based on its L-edge spectrum. Our model attains an R 2 score of 0.85 and a root mean square error of 0.24 on simulated data. It has also successfully predicted experimental L-edge EELS spectra taken in this work and XAS spectra extracted from the literature. We further demonstrate the utility of this model by predicting simulated and experimental spectra of mixed valence samples generated by this work. This model can be integrated into a real-time EELS/XAS analysis pipeline on mixtures of copper-containing materials of unknown composition and oxidation state. By expanding the training data, this methodology can be extended to data-driven spectral analysis of a broad range of materials.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

NASA SPoRT Land Information System Products for Soil Moisture Analysis

The NASA Short-term Prediction Research and Transition (SPoRT) Program has been producing a near real-time instance of NASA’s Land Information System (hereafter known as SPoRT-LIS) since 2010, which contains output of soil moisture and temperature at layered depths. The unique configuration of the SPoRT-LIS enables decision-making on operational timescales since it assimilates near real-time observations such as Green Vegetation Fraction from the Visible Infrared Imaging Radiometer Suite and Quantitative Precipitation Estimates from the Multi-Radar Multi-Sensor System. The SPoRT-LIS was developed initially to provide land surface initialization variables for local numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model. The earliest documented uses of the SPoRT-LIS as a tool for local drought analysis came from the National Weather Service Office in Huntsville, AL in 2011, in which data were used to provide recommendations for drought category changes to the U.S. Drought Monitor. Through engagement with SPoRT collaborative partners, use of the SPoRT-LIS has gradually expanded in recent years as a component of drought analysis and feedback to the U.S. Drought Monitor. This effort was aided by feedback from end users who expressed needs for specific soil moisture variables, which led to increased applicability for analysis by others in the drought community. This presentation will provide information on the SPoRT-LIS for drought analysis and the collaborative process that has led to changes in product output to meet user needs, with focus in the Southern Appalachian region. However, applications for hydrology and fire weather will also be discussed.

Land surface modeling↗

DOE OSTI2024

Schema Elements for Granta Annual Report: FY2024

Granta: Materials Intelligence (Granta: MI) is a commercial database software distributed by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. Lack of standard and well-documented database schema is the primary obstacle to an NSE materials data management solution, so the objective of this project is to create and document such a schema. In FY21, an approach for designing, documenting, and managing a standard database schema was described based on the creation of schema elements (collections of attributes used to describe particular aspects of the data) to be used as building blocks for creating various database tables without duplication. In FY22, these methods were applied through a multi-site collaboration to create and document the schema elements necessary to build a thermogravimetric analysis (TGA) testing table. In FY23 the schema was expanded to include elements for a differential scanning calorimetry (DSC) table, along with schema for supporting metadata tables including Instruments, Projects, Documents, and Testing Series. In FY24 the following progress was made, again through multi-site collaboration: • The existing schema elements were modified to accommodate thermomechanical analysis (TMA) data, and a table, Test Data: TMA, was created for managing TMA data. • The elements necessary for the following additive manufacturing (AM) data tables (directed at data specific to selective laser sintering AM technology) were created: • AM Builds • AM Processes • AM Part Designs • Built AM Parts • AM Feedstock Materials • AM Feedstock Material Batches • The elements necessary for creating a Calibrated Material Models table were created, and the Calibrated Material Models table was created. In FY25 the existing schema will be deployed on the production enterprise Granta instance on the enterprise secure network. Schema elements will be appended, and new elements created as necessary, to allow the creation of tables specifically to support materials testing, AM process development, and design and analysis for modernization programs.

36 MATERIALS SCIENCE↗