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At least 685 records · Page 38

Containerless processing technologies at the Jet Propulsion Laboratory

Acoustic and electrostatic levitation (EL) techniques for maintaining sample-wall distance in order to ensure contamination-free conditions during microgravity materials science experiments on board the Shuttle are examined. A laboratory model for acoustic containerless (AC) processing is described, noting the use of three commercially available drivers for sample levitation. The arrangement of the speakers results in a point node to which a liquid drop sample migrates. Varying the field through manipulation of the dB levels and phase of the drivers' outputs permits control of sample position and movement. Rotation of a styrofoam ball at 2000 rpm has been achieved. Oscillations can also be induced. An advanced version of the AC system is analytically defined, with further studies mentioned for stable levitation modes using a cylindrical chamber and optimizing acoustic power transfer between hot and cold regions. A tetrahedral EL system has proven to work in a reduced gravity environment. El involves imparting an electrical charge to an object and then positioning and maintaining it through use of EM fields. The presence of human operators to perform the processing on the Shuttle is mentioned as offering real-time capability of altering the experimental conditions.

Wang, T. G.↗

CIRCA 2000 operations criteria

The current Shuttle Program was used as a working model and certified data source in the identification of Space Transportation System (STS) operational cost drivers. Changes to flight hardware, processing methodologies, and identification of automation applications that would reduce costs were derived by reference to that data. The CIRCA 2000 Criteria were developed using these critical analyses of the on-going Shuttle Program. Several innovative suggestions are reviewed.

Scholz, Arthur L.↗

Experimental Study of a Three-Dimensional Shear-Driven Turbulent Boundary Layer with Streamwise Adverse Pressure Gradient

The effects of a strong adverse pressure gradient on a three-dimensional turbulent boundary layer are studied in an axisymmetric spinning cylinder geometry. Velocity measurements made with a three-component laser Doppler velocimeter include all three mean flow components, all six Reynolds stress components, and all ten triple-product correlations. Reynolds stress diminishes as the flow becomes three-dimensional. Lower levels of shear stress were seen to persist under adverse pressure gradient conditions. This low level of stress was seen to roughly correlate with the magnitude of cross-flow (relative to free stream flow) for this experiment as well as most of the other experiments in the literature. Variations in pressure gradient do not appear to alter this correlation. For this reason, it is hypothesized that a three-dimensional boundary layer is more prone to separate than a two-dimensional boundary layer, although it could not be directly shown here. None of the computations performed with either a Prandtl mixing length, k-epsilon, or a Launder-Reece-Rodi full Reynolds-stress model were able to predict the reduction in Reynolds stress.

Driver, David M.↗

Models of thermal/chemical boundary layer convection: Potential application to Venus

The upper boundary layer of Venus is comprised of at least two distinct chemical components, mantle and crust. Fluid dynamical models of convection within Venus' mantle were primarily of the thermal boundary layer type. Models assessing the ability of convective mantle flows to deform the crust were undertaken, but models exploring the effects of a variable thickness crust on mantle convection were largely lacking. A Venusian crust of variable thickness could couple back into, and alter, the mantle flow patterns that helped create it, leading to deformation mechanisms not predicted by purely thermal boundary layer convection models. This possibility is explored through a finite element model of thermal/chemical boundary layer convection. Model results suggest that a crust of variable thickness can serve as a mantle flow driver by perturbing lateral temperature gradients in the upper mantle. Resulting mantle flow is driven by the combination of free convective and nonuniform crustal distribution. This combination can lead to a flow instability manifest in the occurrence of episodic mantle lithosphere subduction initiated at the periphery of a crustal plateau. The ability of a light, near surface, chemical layer to potentially alter mantle flow patterns suggest that mantle convection and the creation and/or deformation of such a chemical layer may be highly nonseparable problems on time scales of 10(exp 8) years.

Lenardic, A.↗

Mars Global Reference Atmospheric Model (Mars-GRAM 3.34): Programmer's Guide

This is a programmer's guide for the Mars Global Reference Atmospheric Model (Mars-GRAM 3.34). Included are a brief history and review of the model since its origin in 1988 and a technical discussion of recent additions and modifications. Examples of how to run both the interactive and batch (subroutine) forms are presented. Instructions are provided on how to customize output of the model for various parameters of the Mars atmosphere. Detailed descriptions are given of the main driver programs, subroutines, and associated computational methods. Lists and descriptions include input, output, and local variables in the programs. These descriptions give a summary of program steps and 'map' of calling relationships among the subroutines. Definitions are provided for the variables passed between subroutines through common lists. Explanations are provided for all diagnostic and progress messages generated during execution of the program. A brief outline of future plans for Mars-GRAM is also presented.

Justus, C. G.↗

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

PRedictors↗

Irrigation Water Demand Sensitivity to Climate Variability across the Contiguous United States

Climate variability is an important driver of irrigation water use in many regions. Efforts to anticipate climate change impacts on future water availability can benefit from understanding how irrigation water demand has responded to these drivers to date. Here we apply satellite derived data, meteorological reanalysis, an advanced land surface model, and available state level reports to quantify irrigation demand sensitivities to temperature and precipitation across the Contiguous United States, for the period of 2002-2017. As expected, strong negative correlations are found between precipitation and irrigation withdrawals, both simulated and reported. Temperature sensitivities, however, vary by region and season, as do the interactive effects of temperature and precipitation on irrigation. Climate-induced irrigation variability is largest in transitional climate zones. These transitional zones are generally separate from the regions where rates of irrigation withdrawals are greatest, such that climate-induced variability in irrigation demand represents a water resource consideration that is distinct from chronic over pumping.

Wanshu Nie↗

Global benefits of non-continuous flooding to reduce greenhouse gases and irrigation water use without rice yield penalty

Non-continuous flooding is an effective practice for reducing greenhouse gas emissions (GHGs) and irrigation water use (IRR) in rice fields. However, advancing global implementation is hampered by the lack of comprehensive understanding of GHGs and IRR reduction benefits without compromising rice yield. Here, we present the largest observational data set for such effects as of yet. By using Random Forest regression models based on 636 field trials at 105 globally georeferenced sites, we identified the key drivers of effects of non-continuous flooding practices and mapped maximum GHGs or IRR reduction benefits under optimal non-continuous flooding strategies. The results show that variation in effects of non-continuous flooding practices are primarily explained by the UnFlooded days Ratio (UFR, that is the ratio of the number of days without standing water in the field to total days of the growing period). Non-continuous flooding practices could be feasible to be adopted in 76% of global rice harvested areas. This would reduce the global warming potential (GWP) of CH4 and N2O combined from rice production by 47% or the total GWP by 7% and alleviate irrigation water use by 25%, while maintaining yield levels. The identified UFR targets far exceed currently observed levels particularly in South and Southeast Asia, suggesting large opportunities for climate mitigation and water use conservation, associated with the rigorous implementation of non-continuous flooding practices in global rice cultivation.

climate change mitigation↗

Energy Impact of Connected and Automated Vehicle Technologies. Final report

The overarching goal of this project is to understand the potential impact of connected and automated vehicles. The goal was achieved through data collection, model development, algorithm designs, simulations, and limited field tests. The main outcomes from this project include: (1) we collected energy consumption and GPS data from 500 vehicles over one year, with a total mileage of 8 million miles; (2) Based on the collected data and other datasets collected at the University of Michigan, we developed a calibrated Ann Arbor model in Polaris (model developed by ANL), and the fuel economy accuracy was found to be around 3.9% by comparison with field collected data; (3) An open-source SUMO model of Ann Arbor was developed; (4) Eco-Routing algorithms in Ann Arbor using the SUMO model shows 6% fuel saving potential; (5) Experiments conducted at the Mcity test facility shows that human drivers roughly follow the Eco-driving suggestions roughly 70% of the time; (6) Based in the Ann Arbor travel patterns, we found that each shared automated vehicle can replace around 4 individually owned vehicles; and (7) Adaptive Traffic Signal Control Algorithm developed through this project has been validated both in simulations and preliminary test results. For connected and automated vehicles, on average the performance is 13% delay reduction, and 10% fuel reduction. While connected and automated vehicles are in their early stage of deployment, the results from this project confirm that there is significant potential for energy saving if the technologies are developed and used properly. The three main technologies studied in this project include eco-routing, shared autonomous rides, and adaptive traffic signal controls. The data collected and model developed through the project can be used to study many other connected and automated vehicle technologies.

02 PETROLEUM↗

Towards A Model-Based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Celaya, Jose R.↗

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Electrolytic capacitors↗

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗

Model-Based Engineering Design for Trade Space Exploration throughout the Design Cycle

This paper presents ongoing work to standardize model-based system engineering as a complement to point design development in the conceptual design phase of deep space missions. It summarizes two first steps towards practical application of this capability within the framework of concurrent engineering design teams and their customers. The first step is standard generation of system sensitivities models as the output of concurrent engineering design sessions, representing the local trade space around a point design. A review of the chosen model development process, and the results of three case study examples, demonstrate that a simple update to the concurrent engineering design process can easily capture sensitivities to key requirements. It can serve as a valuable tool to analyze design drivers and uncover breakpoints in the design. The second step is development of rough-order- of-magnitude, broad-range-of-validity design models for rapid exploration of the trade space, before selection of a point design. At least one case study demonstrated the feasibility to generate such models in a concurrent engineering session. The experiment indicated that such a capability could yield valid system-level conclusions for a trade space composed of understood elements. Ongoing efforts are assessing the practicality of developing end-to-end system-level design models for use before even convening the first concurrent engineering session, starting with modeling an end-to-end Mars architecture.

models↗

Will Anthropogenic Warming Increase Evapotranspiration? Examining Irrigation Water Demand Implications of Climate Change in California

Abstract Climate modeling studies and observations do not fully agree on the implications of anthropogenic warming for evapotranspiration (ET), a major component of the water cycle and driver of irrigation water demand. Here, we use California as a testbed to assess the ET impacts of changing atmospheric conditions induced by climate change on irrigated systems. Our analysis of irrigated agricultural and urban regions shows that warmer atmospheric temperatures have minimal implications for ET rates and irrigation water demands—about one percent change per degree Celsius warming (∼1% °C −1 ). By explicitly modeling irrigation, we control for the confounding effect of climate‐driven soil moisture changes and directly estimate water demand implications. Our attribution analysis of the drivers of ET response to global anthropogenic warming shows that as the atmospheric temperature and vapor pressure deficit depart from the ideal conditions for transpiration, regulation of stomata resistance by stressed vegetation almost completely offsets the expected increase in ET rates that would otherwise result from abiotic processes alone. We further show that anthropogenic warming of the atmosphere has minimal implications for mean relative humidity (<1.7% °C −1 ) and the surface available energy (<0.2% °C −1 ), which are critical drivers of ET. This study corroborates the growing evidence that plant physiological changes moderate the degree to which changes in potential ET are realized as actual ET.

54 ENVIRONMENTAL SCIENCES↗

MSD CoP Webinar: Representing Climate Impacts in Scenaros

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Scenarios of future emissions and land use have been most commonly produced without accounting for the effects that climate impacts linked to those emissions and land use changes may have. The questions of how important such impacts could be, at the regional or global scale, has become an increasingly cogent one. Using the Global Change Analysis Model (GCAM), we implement climate impacts on water supply, agricultural productivity, and energy demand driven by climatic impact drivers whose evolution over the 21st century is representative of a climate consistent with GCAM's reference scenario and compare the output to the reference at both regional and global scales. We show that the impacts from the version of GCAM that uses GDP as an exogenous input are not sufficient to bend emission pathways at the global scale. However, we see effects emerge at the regional scale in terms of emissions, among other metrics linked to water, land and energy. We expect the impacts to become more significant at an aggregate, global scale in a forthcoming version of the model with endogenous GDP. Meanwhile, we document the mechanisms that drive the difference at regional scales which could still be significant in their impacts for individual economies and populations. Presenters: Dr. Claudia Tebaldi (Joint Global Change Research Institute, Pacific Northwest National Laboratory) Moderator(s): Jennifer Morris (MSD CoP SSG member), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 5, 2024 from 1 PM - 2:15 PM ET

Climate Scenarios↗

Space Weathering Investigations Enabled by NASA's Virtual Heliophysical Observatories

Structural and chemical impact of the heliospheric space environment on exposed planetary surfaces and interplanetary dust grains may be generally defined as space weathering . In the inner solar system, from the asteroid belt inwards towards the Sun, the surface regolith structures of airless bodies are primarily determined by cumulative meteoritic impacts over billions of years, but the molecular composition to meters in depth can be substantially modified by irradiation effects. Plasma ions at eV to keV energies may both erode uppermost surfaces by sputtering, and implant or locally produce exogenic material, e.g. He-3 and H2O, while more energetic ions drive molecular change through electronic ionization. Galactic cosmic ray ions and more energetic solar ions can impact chemistry to meters in depth. High energy cosmic ray interactions produce showers of secondary particles and energetic photons that present hazards for robotic and human exploration missions but also enable detection of potentially useable resources such as water ice, oxygen, and many other elements. Surface sputtering also makes ejected elemental and molecular species accessible for in-situ compositional analysis by spacecraft with ion and neutral mass spectrometers. Modeling of relative impacts for these various space weathering processes requires knowledge of the incident species-resolved ion flux spectra at plasma to cosmic ray energies and as integrated over varying time scales. Although the main drivers for investigations of these processes come from NASA's planetary science and human exploration programs, the NASA heliophysics program provides the requisite data measurement and modeling resources to enable specification of the field & plasma and energetic particle irradiation environments for application to space weather and surface weathering investigations. The Virtual Heliospheric Observatory (VHO), Virtual Energetic Particle Observatory (VEPO), Lunar Solar Origins Exploration (LunaSOX), and Space Physics Data Facility (SPDF) services now provide a wide range of inner heliospheric spacecraft data that can be applied to space weathering of potential exploration destinations including the Moon, asteroids, and the moons of Mars, as well to radiation hazard assessment for the spacecraft and human explorers. For example, the new VEPO service for time-averaging of multi-source ion flux spectra enables the specification of composite flux spectra from a variety of ongoing and legacy missions for applications to surface interaction modeling. Apollo to Artemis data resources of LunaSOX enable specific space weathering investigations for the Moon, while VHO more generally covers the space field and plasma environments of the inner and outer solar system from the sunward-most perihelia of the twin Helios spacecraft to the ongoing heliosheath passages of the twin Voyagers. Composite multi-source spectra from VEPO can also be applied to the continuing compilation of accumulated 1-AU fluence spectra, mostly contributed by solar wind plasma and energetic particle events, for determination of time-averaged particle compositional and kinetic energy output from the Sun and for modeling of long-term irradiation impacts on planetary surfaces.

Cooper, John F.↗

VESIcal: A Critical Approach to Volatile Solubility Modelling Using the Open-Source Engine Vesical

Accurate models of H(2)O and CO(2) solubility in silicate melts are vital for understanding volcanic plumbing systems. These models are used to estimate the depths of magma storage regions from melt inclusion volatile contents, investigate the role of volatile exsolution as a driver of volcanic eruptions, and track the degassing path followed by a magma ascending to the surface. However, despite the large increase in the number of experimental constraints over the last two decades, many recent studies still utilize an earlier generation of models which were calibrated on experimental datasets with restricted compositional ranges. This may be because many of the available tools for more recent models require large numbers of input parameters to be hand-typed (e.g., temperature, concentrations of H(2)O, CO(2), and 8–14 oxides), making them difficult to implement on large datasets. Here, we use a new open-source Python3 tool, VESIcal, to critically evaluate the behaviors and sensitivities of different solubility models for a range of melt compositions. Using literature datasets of andesitic-dacitic experimental products and melt inclusions as case studies, we illustrate the importance of evaluating the calibration dataset of each model. Finally, we highlight the limitations of particular data presentation methods, such as isobar diagrams, and provide suggestions for alternatives, and best practices regarding the presentation and archiving of data. This review will aid the selection of the most applicable solubility model for different melt compositions, and identifies areas where additional experimental constraints on volatile solubility are required.

magma↗

Hydrological connectivity: a review and emerging strategies for integrating measurement, modeling, and management

This review synthesizes methods for measuring, modeling, and managing hydrologic connectivity, offering pathways to improve practices and address environmental challenges (e.g., climate change) and sustainability. As a key driver of water movement and nutrient cycling, hydrologic connectivity influences flood mitigation, water quality regulation, and biodiversity conservation. However, traditional field-based methods (e.g., dye tracing), indirect measurements (e.g., runoff analysis), and remote sensing techniques (e.g., InSAR) often struggle to capture the complexity of catchment-scale interactions. Similarly, modeling approaches—including process-based and percolation theory-based models, graph theory, and entropy-based metrics—face limitations in fully representing these interconnected processes. Both modeling and measurement techniques are constrained by inadequate spatial and temporal coverage, high data demands, computational complexity, and difficulties in representing subsurface connectivity. Subsequently, we critique current management practices that prioritize isolated variables (e.g., streamflow, sediment transport) over system-wide strategies and emphasize the need for adaptive, connectivity-based approaches in water resource planning and restoration. Moving forward, we highlight the importance of interdisciplinary collaboration, technological innovations (e.g., AI-driven modeling, real-time monitoring), and integrated frameworks to improve connectivity measurement, modeling, and adaptive management to restore fragmented hydrologic networks. This integrated approach sets the stage for transformative water resource management, fostering proactive policy development and stakeholder engagement.

Dwivedi, Dipankar↗