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At least 937 records · Page 52

The Discharging of Roving Objects in the Lunar Polar Regions

In 2007, the National Academy of Sciences identified the lunar polar regions as special environments: very cold locations where resources can be trapped and accumulated. These accumulated resources not only provide a natural reservoir for human explorers, but their very presence may provide a history of lunar impact events and possibly an indication of ongoing surface reactive chemistry. The recent LCROSS impacts confirm that polar crater floors are rich in material including approx 5%wt of water. An integral part of the special lunar polar environment is the solar wind plasma. Solar wind protons and electrons propagate outward from the Sun, and at the Moon's position have a nominal density of 5 el/cubic cm, flow speed of 400 km/sec, and temperature of 10 eV (approx. equal 116000K). At the sub-solar point, the flow of this plasma is effectively vertically incident at the surface. However, at the poles and along the lunar terminator region, the flow is effectively horizontal over the surface. As recently described, in these regions, local topography has a significant effect on the solar wind flow. Specifically, as the solar wind passes over topographic features like polar mountains and craters, the plasma flow is obstructed and creates a distinct plasma void in the downstream region behind the obstacle. An ion sonic wake structure forms behind the obstacle, not unlike that which forms behind a space shuttle. In the downstream region where flow is obstructed, the faster moving solar wind electrons move into the void region ahead of the more massive ions, thereby creating an ambipolar electric field pointing into the void region. This electric field then deflects ion trajectories into the void region by acting as a vertical inward force that draws ions to the surface. This solar wind 'orographic' effect is somewhat analogous to that occurring with terrestrial mountains. However, in the solar wind, the ambipolar E-field operating in the collision less plasma replaces the gradient in pressure that would act in a collisional neutral gas. Human systems (roving astronauts or robotic systems created by humans) may be required to gain access to the crater floor to collect resources such as water and other cold-trapped material. However, these human systems are also exposed to the above-described harsh thermal and electrical environments in the region. Thus, the objective of this work is to determine the nature of charging and discharging for a roving object in the cold, plasma-starved lunar polar regions. To accomplish this objective, we first define the electrical charging environment within polar craters. We then describe the subsequent charging of a moving object near and within such craters. We apply a model of an astronaut moving in periodic steps/cadence over a surface regolith. In fact the astronaut can be considered an analog for any kind of moving human system. An astronaut stepping over the surface accumulates charge via contact electrification (tribocharging) v.lith the lunar regolith. We present a model of this tribo-charge build-up. Given the environmental plasma in the region, we determine herein the dissipation time for the astronaut to bleed off its excess charge into the surrounding plasma.

Jackson, T. L.↗

Exploration Systems Development (ESD) Approach to Enterprise Risk Management

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

Bauder, Stephen P.↗

Pilot-aircraft system reponse to wind shear

The nonlinear aircraft motion and automatic control model is expanded to incorporate the human pilot into simulations of aircraft response to wind to wind shear. The human pilot is described by a constant gains lag filter. Two runs are carried out using pilot transfer functions. Fixed-stick, autopilot, and manned computer simulations are made with an aircraft having characteristics of a small commuter type aircraft flown through longitudinal winds measured by a Doppler radar beamed along the glide slope. Simulations are also made flying an aircraft through sinusoidal head wind and tail wind shears at the phugoid frequency to evaluate the response of manned aircraft in thunderstorm wind environments.

Turkel, B. S.↗

Use of DES Modeling for Determining Launch Availability for SLS

(1) NASA is developing a new heavy lift launch system for human and scientific exploration beyond Earth orbit comprising of the Space Launch System (SLS), Orion Multi-Purpose Crew Vehicle (MPCV), and Ground Systems Development and Operations (GSDO); (2) The desire of the system is to ensure a high confidence of successfully launching the exploration missions, especially those that require multiple launches, have a narrow Earth departure window, and high investment costs; and (3) This presentation discusses the process used by a Cross-Program team to develop the Exploration Systems Development (ESD) Launch Availability (LA) Technical Performance Measure (TPM) and allocate it to each of the Programs through the use of Discrete Event Simulations (DES).

Watson, Michael↗

Advancing Air Mobility: Few-Shot Learning in Airspace Research and Development

The advancement of Air Mobility, particularly in the context of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM), represents a transformative shift in aviation's role in modern society. A comprehensive understanding of requirement consistency is paramount for fostering interoperability, standardization, and cost-effectiveness within airspace systems. This paper introduces a novel approach utilizing a pretrained Sentence Transformers model and few-shot learning to address this crucial aspect task of flagging potentially inconsistent requirements. Few-shot learning supports the development of this future through ensuring the accuracy and consistency of identified requirements with little human oversight. This approach offers a promising solution to the challenges of requirement consistency identification in airspace systems. By harnessing the power of advanced NLP techniques with fine-tuned models, stakeholders can enhance efficiency, accuracy, and scalability; ultimately fostering improved interoperability, standardization, and cost-effectiveness in airspace management.

Natural Language Processing↗

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗

CELSS experiment model and design concept of gas recycle system

In order to prolong the duration of manned missions around the Earth and to expand the human existing region from the Earth to other planets such as a Lunar Base or a manned Mars flight mission, the controlled ecological life support system (CELSS) becomes an essential factor of the future technology to be developed through utilization of space station. The preliminary system engineering and integration efforts regarding CELSS have been carried out by the Japanese CELSS concept study group for clarifying the feasibility of hardware development for Space station experiments and for getting the time phased mission sets after FY 1992. The results of these studies are briefly summarized and the design and utilization methods of a Gas Recycle System for CELSS experiments are discussed.

Nitta, K.↗

Learning from learning machines: improving the predictive power of energy-water-land nexus models with insights from complex measured and simulated data

Focal Area(s): Insights gleaned from complex data (observed and simulated) using AI; Predictive modeling through the use of AI techniques and AI-derived model components, including physics- and knowledge-informed models; Energy-water-land nexus and integrated energy systems – models of MultiSector dynamics. Science Challenge: Scientific communities are in need of tools for the computational integration of physics-based models, experimental data, and empirical/observational studies across a broad range of temporal and spatial scales to explore and meet EESSD grand challenges. We require AI algorithms for the discovery of process-drivers in the Earth-energy-human system and to link them with complex measured and simulated data. We aim to understand the energy-water-land nexus, particularly under extreme forcing scenarios and rare events, leveraging scale-aware AI process models, including probabilistic uncertainties, and benefiting from the emerging 5G-enabled landscape-scale sensing and edge computing capabilities. These models are needed to identify instabilities and tipping points that manifest extreme system behaviors with consequences for integrated energy systems and the environment. This work requires fundamental advances in uncertainty quantification, in particular, to identify and model unlikely but catastrophic outliers. Specifically, we need models that are interpretable to domain scientists and, essentially, explainable to public and private stake holders.

54 ENVIRONMENTAL SCIENCES↗

A framework to implement human reliability analysis during early design stages of advanced reactors

Nuclear power plants require human actions throughout their lifecycle from design, construction, operation, and decommissioning. However, for advanced reactors (e.g., Generation IV), the reliance on human intervention in safety-related actions is expected to be reduced or completely replaced by automated actions. The Probabilistic Risk Assessment (PRA) Standard for Advanced Non-LWR Nuclear Power Plants requires that the impacts of all operator actions are captured and incorporated in the risk of the modeled plant. Moreover, the Modernization of Technical Requirements for Licensing Advanced Reactors requires human reliability analysis (HRA) to be included throughout all design and PRA development stages. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in later design stages, though it may be adequate in capturing pre-, at-, and post-initiators comes short of informing the design itself in the iterative design lifecycle. Hence, this paper presents a framework to include HRA during the design's early stages, pre-conceptual or conceptual. The proposed framework provides a process for the removal of operator actions that do not contribute to the risk and the identification of all key operator actions that are critical to the safety of the design. The results of this framework are then used to inform the design of those safety-related operator actions to update the design further. Then, using information from the updated design, this framework can be reapplied to investigate the impact of the design update on human reliability. The PRA model of the X-energy's pre-conceptual Xe-100 high-temperature gas-cooled pebble-bed reactor (HTGR-PB) design is used to demonstrate the approach. In the pre-conceptual Xe-100 PRA model, also called Phase 0 PRA model, human actions were considered an integral part of analyzing the plant response to different initiating events. Hence, in this paper, all possible human actions in the Xe-100 PRA model are identified, analyzed, and removed to emulate a design relying only on the available automated control systems. The preliminary results of this assessment show how safe the Xe-100 design is even without crediting any human actions. The results also list necessary sequences in which operator actions are critical to the risk profile of the design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling the Economic and Environmental Impacts of Land Scarcity Under Deep Uncertainty

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

54 ENVIRONMENTAL SCIENCES↗

Derivation of Boundary Manikins: A Principal Component Analysis

When designing any human-system interface, it is critical to provide realistic anthropometry to properly represent how a person fits within a given space. This study aimed to identify a minimum number of boundary manikins or representative models of subjects anthropometry from a target population, which would realistically represent the population. The boundary manikin anthropometry was derived using, Principal Component Analysis (PCA). PCA is a statistical approach to reduce a multi-dimensional dataset using eigenvectors and eigenvalues. The measurements used in the PCA were identified as those measurements critical for suit and cockpit design. The PCA yielded a total of 26 manikins per gender, as well as their anthropometry from the target population. Reduction techniques were implemented to reduce this number further with a final result of 20 female and 22 male subjects. The anthropometry of the boundary manikins was then be used to create 3D digital models (to be discussed in subsequent papers) intended for use by designers to test components of their space suit design, to verify that the requirements specified in the Human Systems Integration Requirements (HSIR) document are met. The end-goal is to allow for designers to generate suits which accommodate the diverse anthropometry of the user population.

Young, Karen↗

Optimal cooperative control synthesis of active displays

The utility of augmenting displays to aid the human operator in controlling high order complex systems is well known. Analytical evaluations of various display designs for a simple k/s-squared plant in a compensatory tracking task using an Optimal Control Model (OCM) of human behavior is carried out. This analysis reveals that significant improvement in performance should be obtained by skillful integration of key information into the display dynamics. The cooperative control synthesis technique previously developed to design pilot-optimal control augmentation is extended to incorporate the simultaneous design of performance enhancing augmented displays. The application of the cooperative control synthesis technique to the design of augmented displays is discussed for the simple k/s-squared plant. This technique is intended to provide a systematic approach to design optimally augmented displays tailored for specific tasks.

Garg, S.↗

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spatially random models, estimation theory, and robot arm dynamics

Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.

Rodriguez, G.↗

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1–2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. In conclusion, this platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

59 BASIC BIOLOGICAL SCIENCES↗

Industrial emission inventories of iron and phosphorus for past, present and future

Global emission inventories of aerosol iron by species, and of phosphorus, were developed for inclusion in Earth system modeling that includes atmospheric transport. The time period covered was 1850-2010 to evaluate human influence. A variety of approaches to compare measured and modeled values of aerosol iron was synthesized to estimate how well anthropogenic emissions are known. Anthropogenic emissions are constrained within a factor of two and if there is a bias, it is an overestimation. The exception is shipping emissions, which may be underestimated. Direct radiative forcing by iron aerosol is small in the global average (0.02 W m -2 ) but reaches 0.25 W m -2 around source regions. Regions of high direct radiative forcing are poorly constrained by observations. The central value of change in oceanic net primary productivity due to iron deposition is about 0.26 PgC yr -1 , also highly localized. This leads to a decrease in atmospheric CO2 accumulation that corresponds to a forcing of 0.008 W m -2 since 1850 (0.003-0.18 W m -2 ). Emissions of particulate matter to 2050 were estimated in response to different policy scenarios, including the need for renewable energy installations under decarbonization scenarios. Under the business-as-usual scenario, the total metal demand is 195 Mt/yr in 2020, peaking at 270 Mt/yr in years 2040-2045; under the Rapid Decarbonization scenario, total metal demand is nearly doubled at its peak: 480 Mt/yr in year 2040. Primary particulate matter emissions attributable to processing metals for renewable energy are also amplified under rapid decarbonization, but total atmospheric emissions are much lower because of the shift away from combustion.

58 GEOSCIENCES↗

Development of Skylab experiment T-013 crew/vehicle disturbances

A Skylab experiment to determine the characteristics and effects of crew-motion disturbances was developed. The experiment will correlate data from histories of specified astronaut body motions, the disturbance forces and torques produced by these motions, and the resultant spacecraft control system response to the disturbances. Primary application of crew-motion disturbance data will be to the sizing and design of future manned spacecraft control and stabilization systems. The development of the crew/vehicle disturbances experiment is described, and a mathematical model of human body motion which may be used for analysis of a variety of man-motion activities is derived.

Conway, B. A.↗