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NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗

Prediction of coronary artery disease in patients undergoing operations for mitral valve degeneration

OBJECTIVES: We sought to develop and validate a model that estimates the risk of obstructive coronary artery disease in patients undergoing operations for mitral valve degeneration and to demonstrate its potential clinical utility. METHODS: A total of 722 patients (67% men; age, 61 +/- 12 years) without a history of myocardial infarction, ischemic electrocardiographic changes, or angina who underwent routine coronary angiography before mitral valve prolapse operations between 1989 and 1996 were analyzed. A bootstrap-validated logistic regression model on the basis of clinical risk factors was developed to identify low-risk (< or =5%) patients. Obstructive coronary atherosclerosis was defined as 50% or more luminal narrowing in one or more major epicardial vessels, as determined by means of coronary angiography. RESULTS: One hundred thirty-nine (19%) patients had obstructive coronary atherosclerosis. Independent predictors of coronary artery disease include age, male sex, hypertension, diabetes mellitus,and hyperlipidemia. Two hundred twenty patients were designated as low risk according to the logistic model. Of these patients, only 3 (1.3%) had single-vessel disease, and none had multivessel disease. The model showed good discrimination, with an area under the receiver-operating characteristic curve of 0.84. Cost analysis indicated that application of this model could safely eliminate 30% of coronary angiograms, corresponding to cost savings of $430,000 per 1000 patients without missing any case of high-risk coronary artery disease. CONCLUSION: A model with standard clinical predictors can reliably estimate the prevalence of obstructive coronary atherosclerosis in patients undergoing mitral valve prolapse operations. This model can identify low-risk patients in whom routine preoperative angiography may be safely avoided.

Non-NASA Center↗

Circadian rhythms in human performance and mood under constant conditions

This study explored the relationship between circadian performance rhythms and rhythms in rectal temperature, plasma cortisol, plasma melatonin, subjective alertness and well-being. Seventeen healthy young adults were studied under 36 h of 'unmasking' conditions (constant wakeful bedrest, temporal isolation, homogenized 'meals') during which rectal temperatures were measured every minute, and plasma cortisol and plasma melatonin measured every 20 min. Hourly subjective ratings of global vigour (alertness) and affect (well-being) were obtained followed by one of two performance batteries. On odd-numbered hours performance (speed and accuracy) of serial search, verbal reasoning and manual dexterity tasks was assessed. On even-numbered hours, performance (% hits, response speed) was measured at a 25-30 min visual vigilance task. Performance of all tasks (except search accuracy) showed a significant time of day variation usually with a nocturnal trough close to the trough in rectal temperature. Performance rhythms appeared not to reliably differ with working memory load. Within subjects, predominantly positive correlations emerged between good performance and higher temperatures and better subjective alertness; predominantly negative correlations between good performance and higher plasma levels of cortisol and melatonin. Temperature and cortisol rhythms correlated with slightly more performance measures (5/7) than did melatonin rhythms (4/7). Global vigour correlated about as well with performance (5/7) as did temperature, and considerably better than global affect (1/7). In conclusion: (1) between-task heterogeneity in circadian performance rhythms appeared to be absent when the sleep/wake cycle was suspended; (2) temperature (positively), cortisol and melatonin (negatively) appeared equally good as circadian correlates of performance, and (3) subjective alertness correlated with performance rhythms as well as (but not better than) body temperature, suggesting that performance rhythms were not directly mediated by rhythms in subjective alertness.

NASA Discipline Regulatory Physiology↗

Advancements in Spacecraft Brine Water Recovery: Development of a Radial Vaned Capillary Drying Tray

Technology improvements in the recovery of water from brine are critical to establishing closedloop water recovery systems, enabling long duration missions, and achieving a sustained human presence in space. A genre of 'in-place drying' brine water recovery concepts, collectively referred to herein as Brine Residual In-Containment (BRIC), are under development which aim to increase the overall robustness and reliability of the brine recovery process by performing drying inside the container used for final disposal of the solid residual waste. Implementation of in-place drying techniques have been demonstrated for applications where gravity is present and phase separation occurs naturally by buoyancy induced effects. In this work, a microgravity compatible analogue of the gravity-driven phase separation process is considered by exploiting capillarity in the form of surface wetting, surface tension, and container geometry. The proposed design consists of a series of planar radial vanes aligned about a central slotted core. Preliminary testing of the fundamental geometry in a reduced gravity environment has shown the device to spontaneously fill and saturate rapidly creating a free surface from which evaporation and phase separation can occur similar to a 1-g like 'cylindrical pool' of fluid. Mathematical modeling and analysis of the design suggest predictable rates of filling and stability of fluid containment as a function of relevant system dimensions, e.g., number of vanes, vane length, width, and thickness. A description of the proposed capillary design solution is presented along with preliminary results from testing, modeling and analysis of the system.

Callahan, Michael R.↗

Credibility Assessment of Deterministic Computational Models and Simulations for Space Biomedical Research and Operations

Human missions beyond low earth orbit to destinations, such as to Mars and asteroids will expose astronauts to novel operational conditions that may pose health risks that are currently not well understood and perhaps unanticipated. In addition, there are limited clinical and research data to inform development and implementation of health risk countermeasures for these missions. Consequently, NASA's Digital Astronaut Project (DAP) is working to develop and implement computational models and simulations (M&S) to help predict and assess spaceflight health and performance risks, and enhance countermeasure development. In order to effectively accomplish these goals, the DAP evaluates its models and simulations via a rigorous verification, validation and credibility assessment process to ensure that the computational tools are sufficiently reliable to both inform research intended to mitigate potential risk as well as guide countermeasure development. In doing so, DAP works closely with end-users, such as space life science researchers, to establish appropriate M&S credibility thresholds. We will present and demonstrate the process the DAP uses to vet computational M&S for space biomedical analysis using real M&S examples. We will also provide recommendations on how the larger space biomedical community can employ these concepts to enhance the credibility of their M&S codes.

Mulugeta, Lealem↗

Estimation of the oxalate content of foods and daily oxalate intake

BACKGROUND: The amount of oxalate ingested may be an important risk factor in the development of idiopathic calcium oxalate nephrolithiasis. Reliable food tables listing the oxalate content of foods are currently not available. The aim of this research was to develop an accurate and reliable method to measure the food content of oxalate. METHODS: Capillary electrophoresis (CE) and ion chromatography (IC) were compared as direct techniques for the estimation of the oxalate content of foods. Foods were thoroughly homogenized in acid, heat extracted, and clarified by centrifugation and filtration before dilution in water for analysis. Five individuals consuming self-selected diets maintained food records for three days to determine their mean daily oxalate intakes. RESULTS: Both techniques were capable of adequately measuring the oxalate in foods with a significant oxalate content. With foods of very low oxalate content (<1.8 mg/100 g), IC was more reliable than CE. The mean daily intake of oxalate by the five individuals tested was 152 +/- 83 mg, ranging from 44 to 352 mg/day. CONCLUSIONS: CE appears to be the method of choice over IC for estimating the oxalate content of foods with a medium (>10 mg/100 g) to high oxalate content due to a faster analysis time and lower running costs, whereas IC may be better suited for the analysis of foods with a low oxalate content. Accurate estimates of the oxalate content of foods should permit the role of dietary oxalate in urinary oxalate excretion and stone formation to be clarified. Other factors, apart from the amount of oxalate ingested, appear to exert a major influence over the amount of oxalate excreted in the urine.

NASA Discipline Regulatory Physiology↗

Control of the errors of discretization and idealization in finite element analysis

Understanding of the basic principles which control errors of discretization in finite element analysis has increased very substantially since 1980. The main milestones were: (1) development of the theoretical basis of p-extensions (1981); (2) understanding of the proper interplay between mesh design and assignment of polynomial degree to elements. Practical realization of exponential convergence rates, independently of the smoothness of the exact solution (1984); and (3) industrial experience with the new finite element technology known as the p- or hp-version of the finite element method: General Dynamics reported thirty- to forty-fold savings in terms of human time and large savings in computer time (1986). Lockheed reported favorably on their evaluation of error estimation and quality control capabilities of the p-version in industrial settings (1987). The gains in our understanding of how to control the errors of discretization represent only half of the control necessary to ensure that a numerical model is in fact an accurate representation of the corresponding physical system. Control of the errors of idealization is equally important. A brief overview of the main ideas of how to ensure the quality and reliability of mathematical models of structural systems is presented.

Szabo, Barna A.↗

Advances in Spacecraft Brine Water Recovery: Development of a Radial Vaned Capillary Drying Tray

Technology improvements in the recovery of water from brine are critical to establishing closed-loop water recovery systems, enabling long-duration missions, and achieving a sustained human presence in space. A genre of 'in-place drying' brine water recovery concepts, collectively referred to herein as Brine Residual In-Containment, are under development. These brine water recovery concepts aim to increase the overall robustness and reliability of the brine recovery process by performing drying inside the container used for final disposal of the solid residual waste. Implementation of in-place drying techniques have been demonstrated for applications where gravity is present and phase separation occurs naturally by buoyancy-induced effects. In this work, a microgravity-compatible analogue of the gravity-driven phase separation process is considered by exploiting capillarity in the form of surface wetting, surface tension, and container geometry. The proposed design consists of a series of planar radial vanes aligned about a central slotted core. Preliminary testing of the fundamental geometry in a reduced gravity environment has shown the device to spontaneously fill and saturate rapidly, thereby creating a free surface from which evaporation and phase separation can occur similar to a terrestrial-like 'cylindrical pool' of fluid. Mathematical modeling and analysis of the design suggest predictable rates of filling and stability of fluid containment as a function of relevant system dimensions; e.g., number of vanes, vane length, width, and thickness. A description of the proposed capillary design solution is presented along with preliminary results from testing, modeling, and analysis of the system.

Callahan, Michael R.↗

Modeling In-Space Aborts for NASA Human Exploration Missions

NASA is developing new capabilities to send humans beyond low Earth orbit (LEO) for the first time in several decades with the new Multi-purpose Crew Vehicle (MPCV) Orion spacecraft and Space Launch System (SLS) launch vehicle. As part of these capabilities, NASA is developing means to terminate missions prior to reaching mission destinations in order to save the crew in the event of critical life-threatening failures. This abort capability exists for both ascent and in-space operations. While the risk associated with ascent aborts has been modeled in detail, less has been done in the area of in-space aborts (e.g. Apollo 13). Recent efforts have started to better assess the risk associated with in-space aborts. This paper will describe these efforts. The in-space abort model described in this paper is part of a larger Cross-Program PRA (XPRA) model of exploration missions planned in the next few years to the vicinity of the Moon. The model consists of linked event trees and fault trees and associated rules built using the Systems Analysis Program for Hands-On Integrated Reliability Evaluations (SAPHIRE) tool. This model structure is being built with flexibility in mind in order to perform risk trades and further expansion of the model.

Bigler, Mark A.↗

Space Research Project Management Can Benefit from Engineering Technology Selection Methods

Many engineering methods have been developed to help management select technology for a system design or further research. The simplest way to compare technologies is to use a checklist containing all the more or less important selection criteria, so that nothing is overlooked. The criteria usually include cost, safety, reliability and maintainability, and potential problems such as noise generation and microgravity sensitivity. The next step typically is to weight and score all the criteria. The process of weighting and scoring is helpful in bringing out different priorities and reaching a shared point of view. Group technology selection methods are designed to highlight initial disagreements and produce a shared consensus. Often a frank discussion led by management rather than decision analysts can be more effective. The final selection depends on management and engineering judgment and may include programmatic and organizational factors that are beyond the engineering checklist. The objective of engineering technology selection methods is to provide engineering information to assist management in making sound decisions. Project management and technology selection are assumed to use rational engineering analytic methods, but they often do not. The reason is that human insight, intuition, and “gut feel,” rather than logic, more frequently determine our decisions. Project selection and management are strongly influenced by nonrational psychological influences, which can produce unjustified confidence and determination. Nevertheless, there is a strong need for space projects to do rational project analysis and selection. Demonstrating a rational spirit is necessary for a scientific and technical organization. Professional ethics at its best requires an open, honest, and fair process, without damaging politics. Rational analysis can help improve good projects and avoid selecting bad ones. A sanity check using rational analysis guided by a checklist can help avoid egregious and damaging errors.

Jones, Harry W.↗

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring a multitude of capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for a particular mission is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) to defining gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities, gaps, and KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed. The paper will contain a summary of the approximately 60 gaps. Gaps are classified as to their type (architecture, knowledge, technology, developmental, or engineering) depending on the magnitude of the gap. The paper will provide brief overviews of a few major technology challenges and the technologies being considered, but will reference detailed papers for a more thorough treatment of the challenges and state of the art. Data analysis of the gaps is in work and results are not currently available for this abstract. It is anticipated the paper will include examples of select KPPs with descriptions as to why these are the relevant measures. Additionally some KPPs will be graphically presented over time to show progress to date and when performance targets need to be achieved to support exploration missions. Graphical summaries of how gaps closures with near term mission elements support follow-on mission elements will be provided.

Life Support↗

Carbon Dioxide Collection and Purification System for Mars

One of the most abundant resources available on Mars is the atmosphere. The primary constituent, carbon dioxide, can be used to produce a wide variety of consumables including propellants and breathing air. The residual gases can be used for additional pressurization tasks including supplementing the oxygen partial pressure in human habitats. A system is presented that supplies pure, high-pressure carbon dioxide and a separate stream of residual gases ready for further processing. This power-efficient method freezes the carbon dioxide directly from the atmosphere using a pulse-tube cryocooler. The resulting CO2 mass is later thawed in a closed pressure vessel, resulting in a compact source of liquefied gas at the vapor pressure of the bulk fluid. Results from a demonstration system are presented along with analysis and system scaling factors for implementation at larger scales. Trace gases in the Martian atmosphere challenge the system designer for all carbon dioxide acquisitions concepts. The approximately five percent of other gases build up as local concentrations of CO2 are removed, resulting in diminished performance of the collection process. The presented system takes advantage of this fact and draws the concentrated residual gases away as a useful byproduct. The presented system represents an excelient volume and mass solution for collecting and compressing this valuable Martian resource. Recent advances in pulse-tube cryocooler technology have enabled this concept to be realized in a reliable, low power implementation.

Clark, D. Larry↗

Abort Trigger False Positive and False Negative Analysis Methodology for Threshold-Based Abort Detection

This paper describes a quantitative methodology for bounding the false positive (FP) and false negative (FN) probabilities associated with a human-rated launch vehicle abort trigger (AT) that includes sensor data qualification (SDQ). In this context, an AT is a hardware and software mechanism designed to detect the existence of a specific abort condition. Also, SDQ is an algorithmic approach used to identify sensor data suspected of being corrupt so that suspect data does not adversely affect an AT's detection capability. The FP and FN methodologies presented here were developed to support estimation of the probabilities of loss of crew and loss of mission for the Space Launch System (SLS) which is being developed by the National Aeronautics and Space Administration (NASA). The paper provides a brief overview of system health management as being an extension of control theory; and describes how ATs and the calculation of FP and FN probabilities relate to this theory. The discussion leads to a detailed presentation of the FP and FN methodology and an example showing how the FP and FN calculations are performed. This detailed presentation includes a methodology for calculating the change in FP and FN probabilities that result from including SDQ in the AT architecture. To avoid proprietary and sensitive data issues, the example incorporates a mixture of open literature and fictitious reliability data. Results presented in the paper demonstrate the effectiveness of the approach in providing quantitative estimates that bound the probability of a FP or FN abort determination.

risk assessment↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA’s near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center’s (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC’s Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA’s CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

Hong Q. Yang↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA's near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center's (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC's Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA's CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

cryogenic fluid management↗

Section on Observed Impacts on El Nino

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. As El Nino climate forecasting grows out of the research mode into operational mode, the research focus shifts to include the design of appropriate modes of utilization. Awareness of and sensitivity to the costs of prediction errors also grow. For example, one major forecasting model failed to predict the very large El Nino event of 1997, when Pacific sea-surface temperatures were the highest on record. Although simple correlations between El Nino events and crop yields may be suggestive, more sophisticated work is needed to understand the subtleties of the interplay among the global climate system, regional climate patterns, and local agricultural systems. Honesty about the limitations of an forecast is essential, especially when human livelihoods are at stake. An end-to-end analysis links tools and expertise from the full sequence of ENSO cause-and-effect processes. Representatives from many disciplines are needed to achieve insights, e.g, oceanographers and atmospheric scientists who predict El Nino events, climatologists who drive global climate models with sea-surface temperature predictions, agronomists who translate regional climate connections in to crop yield forecasts, and economists who analyze market adjustments to the vagaries of climate and determine the value of climate forecasts. Methods include historical studies to understand past patterns and to test hindcasts of the prediction tools, crop modeling, spatial analysis and remote sensing. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional ID forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds. The stability of human enterprises depends on understanding both the potentialities and the limits of predictability. Farmers rely on past experience to anticipate and respond to fluctuations in the biophysical systems on which their livelihoods depend. Now scientists are improving their ability to predict some major elements of climate variability. The improvements in the reliability of El Nino forecasts are encouraging, but seasonal forecasts for agriculture are not, and will probably never be completely infallible, due to the chaotic nature of the climate system. Uncertainties proliferate as we extend beyond Pacific sea-surface temperatures to climate teleconnections and agricultural outcomes. The goal of this research is to shed as a clear light as possible on these inherent uncertainties and thus to contribute to the development of appropriate responses to El Nino and other seasonal forecasts for a range of stakeholders, which, ultimately, includes food consumers everywhere.

Rosenzweig, Cynthia↗

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, Tracie↗

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, T.↗