Search NASA⌕ Search

SEARCH · Search NASA

Results for “Fine Guiding”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Sub-mm Scale Fiber Guided Deep/Vacuum Ultra-Violet Optical Source for Trapped Mercury Ion Clocks

We demonstrate the functionality of a mercury capillary lamp with a diameter in the sub-mm range and deep ultraviolet (DUV)/ vacuum ultraviolet (VUV) radiation delivery via an optical fiber integrated with the capillary. DUV spectrum control is observed by varying the fabrication parameters such as buffer gas type and pressure, capillary diameter, electrical resonator design, and temperature. We also show spectroscopic data of the 199Hg+ hyper-fine transition at 40.5GHz when applying the above fiber optical design. We present efforts toward micro-plasma generation in hollow-core photonic crystal fiber with related optical design and theoretical estimations. This new approach towards a more practical DUV optical interface could benefit trapped ion clock developments for future ultra-stable frequency reference and time-keeping applications.

lamps↗
DOE OSTI2023

Integrating plant physiology into simulation of fire behavior and effects

Summary Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine‐scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine‐scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process‐based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Space telescope astrometry

A description of instruments used for astrometric observations are examined with special emphasis on the Fine Guidance Systems of the space telescope. The telescope consists of a 2.4 meter diameter primary and a secondary figured to the Ritchey-Chretien design that yields a f/24 focal plane. The function of the FGS is to keep the total guidance jitter within the ST requirement of + or - 0.0007 rms, and to maximize the probability of finding suitable guide stars with the available 210 arcmin. Attention is given to the focal plane arrangement and to the ray paths and output images from the Koester's prisms. Some projected scientific uses of the space telescope are given as well as beneficial areas of close cooperation between the space telescope and the ESA.

Van Altena, W.↗
DOE OSTI2023

Porous Semiconducting K–Sn–Mo–S Aerogel: Synthesis, Local Structure, and Ion-Exchange Properties

Chalcogenide-based aerogels are emerging porous semiconducting nanomaterials that appeal to applications in clean energy and the environment. Here, we report a novel gel, potassium–tin–molybdenum–sulfides (KTMS), that integrates the electrostatically bound K + ions in the covalent network of Sn–Mo–S. Its gelation requires a concurrent reduction of Mo 6+ → Mo 4+/5+ and the oxidation of S 2– → Sn – (n ≈ 1) and Sn 2+ → Sn 4+ . KTMS is an amorphous semiconductor showing quantum confinement effects on band gap energies, 2.1 → 1.4 → 0.9 eV for its wet- → aero- → xerogels. Synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS) revealed a complex local structure of KTMS consisting of molecular Mo 2 (S 2 ) 6 and Mo 3 S(S 2 ) 6 clusters. In addition, the Sn–S coordination is related to crystalline Na4Sn3S8 and SnS2. KTMS also demonstrated the removal of the radionuclides of Cs + , Sr 2+ , and UO 2 2+ from ppm to ppb levels with distribution constants (Kd) up to ≥104 mL/g. Notably, despite the lack of atomic periodicity in the amorphous KTMS, the K+ ion is ion-exchangeable with chemically diverse Sr 2+ , Cs + , and UO 2 2+ in aqueous solutions; especially the ion-exchange properties of Sr 2+ and UO 2 2+ ≡(O=U=O) 2+ is not known to any chalcogels known to date. The sequestration of Cs + and Sr 2+ was achieved by the exchange of K + in the amorphous KTMS, and the removal of [O=U 6+ =O] 2+ synergistically involves surface sorption via -S····U 6+ =O 2 2+ covalent interactions and ion-exchange via the hard–soft Lewis acid–base paradigm. Overall, cooperative roles played by the diverse bonding motifs, surface-exposed Lewis basic frameworks, and polarizability of the (poly)sulfides make it an exceptional adsorbent for chemically diverse radioactive species. This finding will guide the design of superior sorbents for chemically distinct metal ion separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

SPRUCE Root Production Assessed with Manual Minirhizotrons Resolved to Plant Functional Type, 2015-2021

This dataset contains raw root length and diameter for individual roots and estimated root population production measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements started at the beginning of whole ecosystem warming manipulations in 2015 through 2021 (2015-05-26 to 2021-09-01). Root morphology and estimated production were quantified throughout the peat profile with manual minirhizotrons deployed within SPRUCE plots. Images were processed using commercial software to quantify the length and diameter of individual roots. Roots were visually assigned to a plant functional type (PFT) of either (ericaceous) shrub, herb (sedges and Maianthemum trifolium), or tree (Larix laricina, Picea mariana) based on expert opinion. The biomass of individual roots was estimated using PFT-specific allometric equations (Iversen et al., 2018). Production per day was estimated as the length of new roots produced between imaging sessions, divided by the number of days between imaging sessions. These values were placed on a m2 aboveground area basis and scaled to a standard depth of 1m (roots are not evenly distributed with depth, do not interpret value as being on a m3 basis). Maximum and average (weighted by production length) depth of each PFT were also estimated within each minirhizotron tube. Annual production was interpolated as the average of four methods to scale these data (see Weber et al, 2026). Standing crop of roots was estimated for each tube as the maximum visible amount (both length and mass) of roots of that PFT for that year. These data expand the ability of researchers to accurately estimate the belowground dynamics of peatland vegetation, as well as the role that fine roots may play in impacting the fluxes of carbon within peatlands. This dataset contains three data files in comma-separate values (*.csv) format. This dataset contains one data file in comma-separate values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I–VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers’ views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Artificial Graphene Nanoribbons: A Test Bed for Topology and Low-Dimensional Dirac Physics

Here, we synthesize artificial graphene nanoribbons by positioning carbon monoxide molecules on a copper surface to confine its surface state electrons into artificial atoms positioned to emulate the low-energy electronic structure of graphene derivatives. We demonstrate that the dimensionality of artificial graphene can be reduced to one dimension with proper "edge" passivation, with the emergence of an effectively gapped one-dimensional nanoribbon structure. These one-dimensional structures show evidence of topological effects analogous to graphene nanoribbons. Guided by first-principles calculations, we spatially explore robust, zero-dimensional topological states by altering the topological invariants of quasi-one-dimensional artificial graphene nanostructures. The robustness and flexibility of our platform allow us to toggle the topological invariants between trivial and nontrivial on the same nanostructure. Ultimately, we spatially manipulate the states to understand fundamental coupling between adjacent topological states that are finely engineered and simulate complex Hamiltonians.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Towards philosophical reasoning with agentic LLMs: Socratic method for scientific assistance

As large language models (LLMs) become central tools in science, improving their reasoning capabilities is critical for meaningful and trustworthy applications. We introduce a Socratic agent for scientific reasoning, implemented through a structured system prompt that guides LLMs via classical principles of inquiry. Unlike typical prompt engineering or retrieval-based methods, our approach leverages definition, analogy, hypothesis elimination, and other Socratic techniques to generate more coherent, critical, and domain-aware responses. We evaluate the agent across diverse scientific domains and benchmark it on the abstraction and reasoning corpus challenge dataset, achieving 97.15% under a fixed prompting protocol and without fine-tuning or external tools. Expert evaluation shows improved reasoning depth, clarity, and adaptability over conventional LLM outputs, suggesting that structured prompting rooted in philosophical reasoning can improve the scientific utility of language models.

LLM reasoning↗
NASA NTRS1978

Ion microprobe, electron microprobe and cathodoluminescence data for Allende inclusions with emphasis on plagioclase chemistry

Three Type B inclusions from the Allende meteorite have been analyzed. A grain-to-grain characterization of mineral chemistry and isotopic content was made possible by the use of a range of techniques, including luminescence and scanning electron microscopy and electron and ion microprobe analysis. Cathodoluminescence was used in fine-grained, optically opaque regions to distinguish between sub-micrometer phases, such as garnet and Si-rich material, subsequently identified by electron probe and scanning electron microscope analyses. Four types of luminescence patterns, due to twinning, primary sector zoning, alteration of boundaries and fractures, and shock effects, were identified in Allende plagioclase. Luminescence color exhibited a strong correlation with Mg content and provided a guide for an electron probe quantitative map of Mg and Na distributions. Ion microprobe studies of individual grains revealed large excesses of Mg-26.

Hutcheon, I. D.↗
NASA NTRSDate not supplied

Development of TEMPO Products and Tools to Support Air Quality Management Decisions

The TEMPO mission has been observing air pollutants every hour during the daytime across its Field of Regard (FoR) covering greater North America since First Light on August 2, 2023. The highly anticipated public release of TEMPO data occurred on May 20, 2024, consisting of level 2 and level 3 trace gas data products of nitrogen dioxide, formaldehyde, and ozone. Our project at the NASA SPoRT Center is developing value-added products and tools to support the TEMPO mission and Early Adopters program with special attention on the air quality management community. The initial focus of this project is evaluating the TEMPO products over stakeholder target areas using Pandora and surface monitor observations. Methods for oversampling TEMPO data to 1 km resolution are being applied over the target areas to resolve fine-scale emission sources and pollutant gradients. Machine learning techniques using TEMPO, surface monitor, and model data to estimate surface-level nitrogen dioxide concentrations are being developed over the target areas. Our SPoRT viewer has been updated to include visualizations of the TEMPO products and an ArcGIS dashboard is being designed for enabling air quality management stakeholders to efficiently analyze TEMPO data. Training materials including user guides are being developed to ensure the effective and sustained use of TEMPO data in air quality management applications. The major outcome of this project is to support the inclusion of TEMPO data in exceptional event demonstrations by active engagement with stakeholders and ultimately enable more informed air quality management decisions in the future. This talk will provide an update on our project activities and showcase use cases of TEMPO data for monitoring different emission sources including wildland fire smoke.

air quality↗
NASA NTRSDate not supplied

Transitioning TEMPO Data for Air Quality Management Applications at the NASA SPoRT Center

The TEMPO mission has been observing air pollutants every hour during the daytime across its Field of Regard (FoR) covering greater North America since First Light on August 2, 2023. The highly anticipated public release of TEMPO data occurred on May 20, 2024, consisting of level 2 and level 3 trace gas data products of nitrogen dioxide, formaldehyde, and ozone. The NASA SPoRT Center is developing value-added products and tools to support the TEMPO mission and Early Adopters program with special attention on stakeholder from air agencies. One component of our work is focused on evaluating the TEMPO products over stakeholder target areas using Pandora and surface monitor observations to characterize the uncertainties and develop best practices for processing and analyzing TEMPO data. Methods for oversampling TEMPO data to 1 km resolution are being applied over the target areas to resolve fine-scale emission sources and pollutant gradients. Machine learning techniques using TEMPO, surface monitor, and model data to estimate surface-level nitrogen dioxide concentrations are being developed over the target areas. A SPoRT viewer for TEMPO has been launched for providing visualizations of the TEMPO products and an ArcGIS dashboard is being designed for enabling air agency stakeholders to efficiently analyze TEMPO data. Training materials including user guides are being developed to ensure the effective and sustained use of TEMPO data at our stakeholder agencies. One major goal of our TEMPO initiatives at SPoRT is to better enable the inclusion of TEMPO data in air quality management applications such as exceptional event demonstrations through our close engagement with stakeholders. This talk will provide an update on our SPoRT activities and showcase use cases of TEMPO data for monitoring different emission sources including wildland fire smoke.

Air Quality↗
DOE OSTI2025

Machine learned potential for high-throughput phonon calculations of metal—organic frameworks

Metal–organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phonon-mediated properties in MOFs, like thermal expansion and mechanical stability, remains challenging due to the large number of atoms per unit cell, making traditional Density Functional Theory (DFT) methods impractical for high-throughput screening. Recent advances in machine learning potentials have led to foundation atomistic models, such as MACE-MP-0, that accurately predict equilibrium structures but struggle with phonon properties of MOFs. In this work, we developed a workflow for computing phonons in MOFs within the quasi-harmonic approximation with a fine-tuned MACE model, MACE-MP-MOF0. The model was trained on a curated dataset of 127 representative and diverse MOFs. The fine-tuned MACE-MP-MOF0 improves the accuracy of phonon density of states and corrects the imaginary phonon modes of MACE-MP-0, enabling high-throughput phonon calculations with state-of-the-art precision. The model successfully predicts thermal expansion and bulk moduli in agreement with DFT and experimental data for several well-known MOFs. These results highlight the potential of MACE-MP-MOF0 in guiding MOF design for applications in energy storage and thermoelectrics.

Elena, Alin Marin↗
NASA NTRS2006

Optical Spectroscopy of Stardust Samples

The Stardust spacecraft collected dust samples of the Kuiper belt comet 81P Wild-2 in aerogel and returned them to Earth January 15, 2006. Preliminary examination (PE) of the collected dust includes teams focused on mineralogy, chemical composition, isotopic measurements, organic analysis, cratering and spectroscopic properties. The main PE science goals are to provide an initial characterization of the returned samples with an emphasis on the capture process and its effects on the samples, a comparison of Stardust samples to other meteoritic materials, and the abundance of presolar materials in the Stardust samples. The science objectives of the Spectroscopy team are to obtain spectroscopic data on Stardust particles through infrared (IR), UV/Vis and Raman measurements of particles in aerogel, extracted particles, keystones, and microtome thin sections. These data will be used to answer fundamental science questions about the nature of the samples, but will also serve as preliminary mineralogical data to guide follow-on measurements that will be performed in the other preliminary examination teams. The IR characteristics of Stardust particles are measured to determine: 1) the nature of the indigenous 3.4 micron organic feature, is it detected and can it be differentiated/deconvolved from the contaminated aerogel? How does it compare to features observed in interplanetary dust particles (IDPs) and to astronomical measurements of comets and interstellar dust? 2) the shape and fine structure within the 10 micron silicate feature. Overlap with the strong Si-O stretching vibration from the aerogel complicates this analysis, but we hope to determine if the feature is dominated by amorphous silicates such as those observed in IDPs and comets and whether or not crystalline silicates (e.g. olivine, pyroxene, clays) are present, 3) the presence of secondary (alteration) phases. Deep Impact results suggest that IR observations of Stardust particles should be evaluated for the presence of hydrated materials (water bands at 3 and 6 microns) and carbonates (6.8 microns and other resonances) and 4) the detection of crystalline features in the far-IR (20-100 microns) region where crystalline silicates and other minerals have strong bands that can be used both for phase analysis and phase chemistry. It has been demonstrated that these far-IR measurements can be obtained in situ on particles in aerogel keystones.

Keller, Lindsay P.↗
DOE OSTI2020

SPRUCE High-Resolution Minirhizotrons in an Experimentally-Warmed Peatland Provide an Unprecedented Glimpse at Fine Roots and their Fungal Partners: Supporting Data

Images were collected using first of their kind, non-destructive, high-resolution automated minirhizotrons (RhizoSystems, LLC) to assess the response of plant fine-root and fungal mycelium dynamics to elevated temperatures after 4-6 years of whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (e[CO2]) in a peat bog where the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment is located. We focused on two SPRUCE experimental plots: Plot 10 has elevated temperature (+9°C) and plot 19 is a control (+0°C). Both have elevated carbon dioxide (e[CO2]). Changes in root and fungal abundance with warming were estimated from a timeseries of landscape-level mosaiced images for each plot by measuring the proportional abundance of five belowground classes: fine roots of vascular plants, ectomycorrhizas, fungal hyphae, fungal rhizomorphs, and fungal sporocarps. To examine root and fungal phenology responses to warming, the length per individual root or fungal structure (except fungal hyphae that did not grow linearly but rather increased in areal coverage) were measured per image area of a set of timeseries patch-level mosaiced images for each plot. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This ecosystem, which is located at the southern margin of the boreal forest, is considered especially vulnerable to climate change and anticipated to be near its tipping point. These data were used in analyses published in Defrenne et al (2021). This dataset contains 5 data files in comma-separate values (*.csv) format and a compressed folder (*.zip) containing 383 JPEG (*.jpg) images. Data files contain landscape-level assessment of belowground class abundance, patch-level growth phenology, and environmental variables (originally published in Hanson et al., 2016 and Hanson et al 2020). Images were collected with automated minirhizotrons and analyzed for phenology. Additional metadata are provided: 5 data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Guide to using lunar soil and simulants for experimentation

It is pointed out that lunar soil can be described as well-graded silty sands or sandy silts with an average particle size by weight in the range from 0.040 to 0.130 mm. The density of in situ bulk lunar soil is typically 1.4 to 1.9 g/cu cm. Changes in soil from moon to laboratory are considered along with some critical differences between simulants and lunar soil. Attention is given to agglutinates, iron metal distributed throughout the agglutinatic glass, solar wind hydrogen, and major lunar minerals (anorthite, pyroxene, ilmenite, olivine). The use of lunar fines as experimental samples is discussed, and the characteristics of simulants for experiments are examined, taking into account grain size distribution, particle type distribution, a highlands simulant, and a high titanium mare simulant. Simulants for testing equipment and structures are also described.

Allton, J. H.↗
NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗
NASA NTRS1977

Basic coaxial mass driver construction and testing

A basic coaxial mass driver has been constructed by a group of students to verify performance predictions in the acceleration range envisaged for the first lunar device. The bucket is guided by four copper tubes which also supply direct current excitation for its single aluminum coil, and is accelerated by twenty coaxial coils along a 2 m track, followed by a deceleration section. The coils are individually energized by electrolytic photoflash capacitors triggered by solid state switches on the basis of bucket position.

Fine, K.↗