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At least 757 records · Page 42

A Novel Bone Marrow Single Cell Atlas of Mechanotransduction in Microgravity, Normal Gravity, Exercise, and Hindlimb Unloading for WT and CDKN1A-Null Regenerative Mice

Mechanical loading of adult stem cell progenitors is a key factor in modulating their proliferation, differentiation, and tissue regenerative potential, with loading generally promoting tissue formation and unloading mediating tissue loss. To address the role of mechanotransduction in maintaining stem cell-based tissue regenerative health, we generated a single cell transcriptomic atlas mapping responses of femur bone marrow mesenchymal and hematopoietic lineages to a range of altered mechanical loading conditions, both in WT B1629SF2/J mice as well as the p21/CDKN1A-null regenerative mice. We selected the femur marrow compartment as a model because of the diversity and high numbers of stem cell progenitor stages present, and because it undergoes static and cyclic hydrostatic pressure loading associated with weight-bearing and ambulation. Our study included normally loaded mice at 1g, unloading in microgravity during spaceflight as well as tail suspension hindlimb unloading, and voluntary running wheel exercise. Basal, one-year natural aging, and habitat controls were also conducted. Overall, the atlas encompasses 18 different experimental conditions with N=3 mice per condition and includes more than 500,000 single cell expressomes. Key specific findings include: increased mature reticulocyte populations in aging and unloading mice compared to active mice; greater hematopoietic and mesenchymal differentiating progenitors cluster identification in CDKN1A-null samples, especially the exercise model; distinct pseudotime cell trajectory shifts in the hematopoietic lineage for spaceflight and unloaded mice; and shifts in monocytic cell populations toward osteoclastic bone degenerative lineages in unloading and spaceflight samples. Overall mechanical loading shows increased marrow progenitor population differentiation while unloading is associated with increased CDKN1A expression and maintenance of marrow population stemness. Deletion of CDKN1A appears to remove a negative check on progenitor lineages commitment to differentiation. Finally, the Bone Marrow Mechanotransduction Single Cell Atlas will serve as a reference tool for studying marrow regenerative responses across a range of mechanical environments as they relate to CDKN1A status.

single-cell↗

Creep anisotropy modeling and uncertainty quantification of an additively manufactured Ni-based superalloy

The advantages offered by additive manufacturing over traditional processes has driven a great deal of industrial and academic interest in recent years. However, the process is relatively new and requires additional investigation to become sufficiently mature for wide scale industrial adoption. Electron beam melting powder bed fusion is one technology that has shown promise for fabricating high temperature resistant materials such as nickel based superalloys. The resulting microstructures typically exhibit a strong fiber texture in the build direction giving rise to anisotropic time-dependent deformation behavior. In order to accelerate the qualification of these materials for industrial adoption accurate numerical models are needed for simulating their behavior. In this work a crystal plasticity model including non-Schmid effects is presented for capturing creep anisotropy observed in additively manufactured IN738LC. The model is calibrated via a probabilistic framework where model parameters are treated as random variables. An iterative sequential design strategy is utilized to efficiently identify the probability density of the unknown model parameters. As a case study the model is utilized to investigate the behavior of randomly oriented equiaxed grain clusters sometimes observed embedded in the additively manufactured columnar structure. A synthetic realization is simulated and uncertainty is propagated through to the full-field response. Results indicate that these features are the source of significant creep relaxation and strain accumulation which partially explains observed grain boundary decohesion at these locations.

36 MATERIALS SCIENCE↗

Soot-particle core-shell and fractal structures from small-angle X-ray scattering measurements in a flame

We have characterized soot particles measured in situ in a laminar co-flow ethylene-air diffusion flame using small-angle X-ray scattering (SAXS). The analysis includes temperature measurements made with coherent anti-Stokes Raman spectroscopy (CARS) and complements soot volume-fraction and maturity measurements made with laser-induced incandescence (LII). We compared the results of fits to the SAXS measurements using a unified model and a fractal core-shell model. Power-law parameters yielded by the unified model indicate that aggregates of primary particles are in the mass-fractal regime, whereas the primary particles are in the surface-fractal regime in the middle of the flame. Higher and lower in the flame, the primary-particle power-law parameter approaches 4, suggesting smooth primary particles. Furthermore, these trends are consistent with fits using the fractal core-shell model, which indicate that particles have an established core-shell structure in the middle of the flame and are internally homogeneous at higher and lower heights in the flame. Primary-particle size distributions derived using the fractal core-shell model demonstrate excellent agreement with distributions inferred from transmission electron microscopy (TEM) images in the middle of the flame. Higher in the flame, a second small mode appears in the size distributions, suggesting particle fragmentation during oxidation. Surface oxidation would explain (1) aggregate fragmentation and (2) loss of core-shell structure leading to smoother primary-particle surfaces by removal of carbon overlayers. SAXS measurements are much more sensitive to incipient and young soot particles than LII and demonstrate significant volume fraction from particles low in the flame where the LII signal is negligible.

42 ENGINEERING↗

Bovine eggs release zinc in response to parthenogenetic and sperm-induced egg activation

Upon fertilization or parthenogenesis, zinc is released into the extracellular space through a series of exocytic events termed zinc sparks, which are tightly coordinated with intracellular calcium transients. The zinc spark reduces the total amount of intracellular zinc, and this reduction is necessary and sufficient to induce egg activation even in the absence of calcium transients. In addition, this zinc release contributes to the block to polyspermy through modification of the zona pellucida. The zinc spark has been documented in all organisms examined to date including the mouse, two species of nonhuman primates, and human. Here we determined whether zinc sparks occur in the bovine, an important model of gamete development in mono-ovulatory mammalian species. We obtained metaphase II-arrested (MII) bovine eggs following in vitro maturation. Total zinc, assessed in single cells using X-Ray Fluorescence Microscopy, was significantly more abundant in the bovine egg compared to iron and copper. Studies with intracellular fluorescent probes revealed that labile zinc pools are localized to discrete cytoplasmic punctae enriched at the cortex. To determine whether zinc undergoes dynamic fluxes during egg activation, we parthenogenetically activated bovine eggs using two approaches: ionomycin or bovine phospholipase C zeta (b Plc ζ) Both these methods induced zinc sparks coordinately with intracellular calcium transients. The zinc spark was also observed in bovine eggs following intracytoplasmic sperm injection. Furthermore, these results establish that zinc is the most abundant transition metal in the bovine egg, and zinc flux during egg activation-induced by chemical activation or sperm-is a highly conserved event across mammalian species.

59 BASIC BIOLOGICAL SCIENCES↗

The role of alanine and aspartate aminotransferases in C 4 photosynthesis

Alanine and aspartate are essential transfer metabolites for C 4 species of the NAD-malic enzyme and the phosphoenolpyruvate carboxykinase subtype. To some degree both amino acids are also part of the metabolite shuttle in NADP-malic enzyme plants. In comparison with C 3 species, the majority of C 4 species are therefore characterised by enhanced expression and activity of alanine and aspartate aminotransferases in the photosynthetically active tissue. Both enzymes exist in multiple copies and have been found in different subcellular compartments. We tested whether different C 4 species show preferential recruitment of enzymes from specific lineages and subcellular compartments. Phylogenetic analysis of alanine and aspartate aminotransferases from a variety of monocot and eudicot C 4 species and their C 3 relatives was combined with subcellular prediction tools and the analysis of the according transcript amounts in mature leaves. Recruitment of aspartate aminotransferases from a specific subcellular compartment was strongly connected to the biochemical subtype. Deviation from the main model was however observed in G. gynandra. The configuration of alanine aminotransferases was generally different in monocot and eudicot species. C 4 monocots recruited an alanine aminotransferase from a specific cytosolic branch, but eudicots use alanine aminotransferase copies from a mitochondrial branch. Generally, plants display high plasticity in the setup of the C 4 pathway. Beside the common models for the different C 4 subtypes, individual solutions were found for plant groups or lineages.

59 BASIC BIOLOGICAL SCIENCES↗

Report From BPTCS Project Team On Evaluation Of Additive Manufacturing For Pressure Retaining Equipment

ASME is evaluating the use of additive manufacturing (AM) for the construction of pressure equipment. The information in this report assesses available AM technologies for direct metal fabrication of pressure equipment. Background information is included in the report to provide context for those not experienced in AM technology. Only commercially available technologies for direct metal fabrication are addressed in the report because these AM methods are the only viable approaches for the construction of pressure equipment. Metal AM technologies can produce near-net shape parts by using multiple layers of material from a three dimensional (3D) design model of the geometry. Additive manufacturing of metal components was developed from polymer based rapid prototyping or 3D printing. At the current maturity level, AM application for pressure equipment has the potential to reduce delivery times and costs for complex shapes. AM will also lead to a reduction in the use of high cost materials, since parts can be created with corrosion resistant layers of high alloy material and structural layers of lower cost materials.

42 ENGINEERING↗

Hydrogen Production Cost from Proton-Conducting Solid Oxide Electrolysis

Rigorous stakeholder-vetted techno-economic analysis (TEA) was conducted to estimate the cost of hydrogen (H 2 ) production using Proton-Conducting Solid Oxide (PSO) electrolysis. The analysis evaluates Current (2025) and Future (2035) technology cases at centralized plant scales of 50 and 500 metric tonnes per day (MTD), assuming electricity, water, and air as the only system inputs. Untaxed, unsubsidized levelized cost of hydrogen (LCOH) is projected to range from 2020 $\$$1.81 to $\$$2.47/kg H 2 at an electricity price of $\$$0.03/kWh and 97% capacity factor under Nth-of-a-kind (NOAK) deployment assumptions. Total installed capital cost was developed using bottom-up Design for Manufacture and Assembly (DFMA) stack cost modeling and detailed balance-of-plant estimates, including mechanical and electrical subsystems, installation, site preparation, engineering, and contingency. Stack performance assumptions include thermoneutral operation, degradation over time, and periodic replacement. LCOH was calculated using the Hydrogen Analysis (H2A) discounted cash flow model in constant 2020 dollars. Results indicate PSO electrolysis has potential for competitive hydrogen production costs under low-cost electricity and mature manufacturing conditions.

08 HYDROGEN↗

State of the art in adaptive control of robotic systems

An up-to-date assessment of adaptive control technology as applied to robotics is presented. Although the field is relatively new and does not yet represent a mature discipline, considerable attention for the design of sophisticated robot controllers has occured. In this presentation, adaptive control methods are divided into model reference adaptive systems and self-tuning regulators, with further definition of various approaches given in each class. The similarity and distinct features of the designed controllers are delineated and tabulated to enhance comparative review.

Tosunoglu, Sabri↗

Integrated System Health Management: Foundational Concepts, Approach, and Implementation

Implementation of integrated system health management (ISHM) capability is fundamentally linked to the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system. It is akin to having a team of experts who are all individually and collectively observing and analyzing a complex system, and communicating effectively with each other in order to arrive to an accurate and reliable assessment of its health. This paper presents concepts, procedures, and a specific approach as a foundation for implementing a credible ISHM capability. The capability stresses integration of DIaK from all elements of a subsystem. The intent is also to make possible implementation of on-board ISHM capability, in contrast to a remote capability. The information presented is the result of many years of research, development, and maturation of technologies, and of prototype implementations in operational systems (rocket engine test facilities). The paper will address the following topics: ISHM Model of a system; detection of anomaly indicators; determination and confirmation of anomalies; diagnostic of causes and determination of effects; consistency checking cycle; sharing of health information; sharing of display information; storage and retrieval of health information; and example implementation.

Figueroa, Fernando↗

Atmospheric Constituents in GEOS-5: Components for an Earth System Model

The GEOS-S model is being developed for weather and climate processes, including the implementation of "Earth System" components. While the stratospheric chemistry capabilities are mature, we are presently extending this to include predictions of the tropospheric composition and chemistry - this includes CO2, CH4, CO, nitrogen species, etc. (Aerosols are also implemented, but are beyond the scope of this paper.) This work will give an overview of our chemistry modules, the approaches taken to represent surface emissions and uptake of chemical species, and some studies of the sensitivity of the atmospheric circulation to changes in atmospheric composition. Results are obtained through focused experiments and multi-decadal simulations.

Pawson, Steven↗

LMI Automated Air Cargo Operations Market Research and Forecast

Air cargo companies and aircraft manufacturers are making significant investments to enable the movement of cargo via various levels of automated aircraft, such as aircraft with simplified operations requiring a pilot, remotely monitored or piloted aircraft, and fully autonomous aircraft. These investments will enable greater utilization of aircraft while unlocking new air markets traditionally served by ground transportation only. Many cargo companies and aerospace experts envision an operating environment where a single pilot can remotely pilot numerous aircraft for significant increases in aircraft utilization. The future operating environment is also expected to include air cargo companies flying smaller aircraft from airports and distribution centers outside of major U.S. cities directly to city centers, avoiding congested roads and increasing the velocity of cargo shipments, particularly those that are high-value, time-sensitive, and security sensitive (e.g., pharmaceuticals). These are just a few benefits and use cases cargo companies and aerospace experts see with the advancement of automated aircraft. To better understand industry’s direction, NASA asked the LMI team to research the forecasted market, timeline, risks, and opportunities for integrating unmanned air cargo vehicles into the National Airspace System (NAS) for the development and prioritization of the NASA Air Traffic Management Exploration’s research portfolio. To begin the market assessment, we gathered data via numerous interviews with key stakeholders and subject matter experts and literature reviews. We then incorporated the data into a custom-developed systems dynamics model and visualization dashboard. The systems dynamics model classifies the size of the market (e.g., overall fleet size of automated aircraft) for four distinct use cases over the next 20 years. The model projects the year in which various types of automated aircraft will enter the commercial cargo market based on our team’s collective research on when the aircraft will become viable due to manufacturing and certification timelines and the lifespan of current, traditional aircraft in service, to name a few factors. While this report defines our team’s estimated timeline of entry and growth, the model is dynamic—it enables NASA users to change variables based on future-year events. If the necessary technology does not mature in accordance with our assumptions, then NASA can change the entry of service point to a future year to evaluate the changes in market size in the out years. This flexibility will be key to deciding when and how NASA should invest in various areas.

air traffic management↗

NASA’s Developments in Cryogenic Fluid Management Technology

NASA has been pursuing the development and demonstration of enabling and enhancing technologies for Cryogenic Fluid Management (CFM) in collaboration with the US industry. NASA’s vision for current and future space exploration requires high-performance chemical and nuclear propulsion solutions that utilize cryogens. The Agency will use cryogenic fluids for Earth-to-orbit transportation, human missions to the Moon and Mars, planetary exploration, and in-situ resource utilization (ISRU) production. All these architectures will require state-of-the-art long-duration storage on the surface and in-space transfer for refueling. This paper focuses on key CFM technology developments completed or ongoing by the Cryogenic Fluid Management Portfolio Office within NASA’s Space Technology Mission Directorate. The CFM Portfolio Office, partnered with US aerospace industry, has invested in CFM technology ground and flight demonstrations, focused on maturing CFM hardware and operations for Artemis and Moon to Mars activities. These demonstrations additionally provide NASA with data to inform numerical modeling activities for verification and validation of design tools and approaches for future missions. This paper includes discussion on remaining high-priority open CFM technology gaps for Mar-forward architectures and initiatives for closure.

Cryogenic Fluid Management↗

Practical challenges of model predictive control (MPC) for grid interactive small and medium commercial buildings

To the urgent call for mitigating climate change, substantial initiatives have been undertaken to deploy grid-interactive heating, ventilation, and air-conditioning (HVAC) controls, such as model predictive control (MPC) for buildings. These efforts typically aim to curtail peak energy demand, shift load and enhance overall energy efficiency. With the recent development of low-cost MPC technologies that don’t require extensive instrumentation or manual modeling, small and medium commercial buildings (SMCBs), which rarely utilize advanced HVAC control systems, have become candidates for grid-interactive efficient buildings (GEBs). However, despite the potential benefits and maturity of the technology itself, several practical challenges remain in real-world implementation. In this paper, we share the practical challenges that we have encountered in implementing and testing three types of MPC solutions (ON/OFF unit, dualfuel, and VRF systems) on multiple SMCB sites. We describe the MPC deployment process and discuss the lessons learned. The site selection, eligibility, and retrofit availability (e.g., utility price structure, thermostat communications, etc.) are the main discussion points at the beginning of the project. Also, the modeling automation and the best practices for interacting with endusers and handling erroneous situations are presented for successful operations.

woo Ham, Sang↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States; NREL (National Renewable Energy Laboratory)

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States: Preprint

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Assurance of Model-Based Fault Diagnosis

Autonomy is an increasingly important technology for robotic scientific and commercial spacecraft. An important motivation for developing onboard autonomy is to enable quick response to dynamic environment and situations, including fault conditions that a spacecraft may encounter. The reliability of such autonomous capabilities depends on the quality of their knowledge of a spacecraft’s health state. Model-based approaches to fault management, i.e. model-based fault diagnosis (MBFD), is one approach to continuously verify correct behavior in addition to diagnosing symptoms to estimate the spacecraft’s health state. The proper functioning of MBFD is dependent on 1) the quality of the model that is analyzed and compared to the outputs of onboard sensors to estimate the system’s health state, and 2) the correct functioning of the diagnosis engine that interrogates the model and compares its analysis to observed system behavior. We are currently developing Verification and Validation (V&V) approaches to provide the necessary confidence that MBFD systems are correctly estimating the health of on-board spacecraft components and systems. Our work is intended to narrow the gap between the rapidly maturing field of ModelBased System Engineering (including MBFD) and the less-well understood area of identifying and applying appropriate V&V techniques to MBFD. Our effort is investigating three areas: 1) developing V&V techniques for the diagnostic model, 2) developing V&V techniques for the diagnostic engine in isolation, and 3) developing V&V techniques for the diagnostic engine and model in combination. This paper describes the work we have completed in the first area. We describe our approach to selecting a system to be represented by a model, the approach to modeling the system, the verification approach we developed for the model, and the results of the verification activity. We conclude with a description of the work remaining in the last two areas, which will be addressed over the next two years.

Chung, Seung↗

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗