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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

It's time to reinvent the general aviation airplane

Current designs for general aviation airplanes have become obsolete, and avenues for major redesign must be considered. New designs should incorporate recent advances in electronics, aerodynamics, structures, materials, and propulsion. Future airplanes should be optimized to operate satisfactorily in a positive air traffic control environment, to afford safety and comfort for point-to-point transportation, and to take advantage of automated manufacturing techniques and high production rates. These requirements have broad implications for airplane design and flying qualities, leading to a concept for the Modern Equipment General Aviation (MEGA) airplane. Synergistic improvements in design, production, and operation can provide a much needed fresh start for the general aviation industry and the traveling public. In this investigation a small four place airplane is taken as the reference, although the proposed philosophy applies across the entire spectrum of general aviation.

Stengel, Robert F.↗
NASA NTRS1989

Minimizing distortion and internal forces in truss structures by simulated annealing

Inaccuracies in the length of members and the diameters of joints of large truss reflector backup structures may produce unacceptable levels of surface distortion and member forces. However, if the member lengths and joint diameters can be measured accurately it is possible to configure the members and joints so that root-mean-square (rms) surface error and/or rms member forces is minimized. Following Greene and Haftka (1989) it is assumed that the force vector f is linearly proportional to the member length errors e(sub M) of dimension NMEMB (the number of members) and joint errors e(sub J) of dimension NJOINT (the number of joints), and that the best-fit displacement vector d is a linear function of f. Let NNODES denote the number of positions on the surface of the truss where error influences are measured. The solution of the problem is discussed. To classify, this problem was compared to a similar combinatorial optimization problem. In particular, when only the member length errors are considered, minimizing d(sup 2)(sub rms) is equivalent to the quadratic assignment problem. The quadratic assignment problem is a well known NP-complete problem in operations research literature. Hence minimizing d(sup 2)(sub rms) is is also an NP-complete problem. The focus of the research is the development of a simulated annealing algorithm to reduce d(sup 2)(sub rms). The plausibility of this technique is its recent success on a variety of NP-complete combinatorial optimization problems including the quadratic assignment problem. A physical analogy for simulated annealing is the way liquids freeze and crystallize. All computational experiments were done on a MicroVAX. The two interchange heuristic is very fast but produces widely varying results. The two and three interchange heuristic provides less variability in the final objective function values but runs much more slowly. Simulated annealing produced the best objective function values for every starting configuration and was faster than the two and three interchange heuristic.

Kincaid, Rex K.↗
NASA NTRS2020

Progress on Gust Load Alleviation Wind Tunnel Experiment and Aeroservoelastic Model Validation for a Flexible Wing with Variable Camber Continuous Trailing Edge Flap System

This paper discusses a wind tunnel experiment of active gust load alleviation of a flexible wing which took place at University of Washington (UW) in 2019. The experiment performed under a NASA SBIR contract with Scientific Systems Company, Inc (SSCI). The objective of the experiment is to demonstrate active controls of the Variable Camber Continuous Trailing Edge Flap (VCCTEF) system for gust load alleviation and real-time drag optimization. The wind tunnel model is a 8.2% sub-scale Common Research Model (CRM) wing. The wing structure is designed to provide a substantial degree of flexibility to represent that of a modern high-aspect ratio wing. Eight active control surfaces are employed in the VCCTEF. A new gust generator system was designed and installed by UW under a sub-contract with SSCI. The first test entry started in July 2019 and ended in September 2019. During this test entry, many significant issues were found with the hardware and software. The significant issues with the servos prevented the test objective from being completed. A follow-up second test entry in 2020 is being planned. The wing system is being repaired by SSCI. This paper reports on the progress of this experimental effort and the aeroservoelastic (ASE) model validation which was conducted during the test entry.

Nguyen, Nhan↗
DOE OSTI2023

Mitigating Green's function Monte Carlo signal-to-noise problems using contour deformations

The Green's function Monte Carlo (GFMC) method provides accurate solutions to the nuclear many-body problem and predicts properties of light nuclei starting from realistic two- and three-body interactions. Controlling the GFMC fermion-sign problem is crucial, as the signal-to-noise ratio decreases exponentially with Euclidean time, requiring significant computing resources. Inspired by similar scenarios in lattice quantum field theory and spin systems, in this work, we employ integration contour deformations to improve the GFMC signal-to-noise ratio. Machine learning techniques are used to select optimal contours with minimal variance from parameterized families of deformations. As a proof of principle, we consider the deuteron binding energies and Euclidean density response functions. We only observe mild signal-to-noise improvement for the binding energy case. On the other hand, we achieve an order of magnitude reduction of the variance for Euclidean density response functions, paving the way for computing electron- and neutrino-nucleus cross-sections of larger nuclei.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Electronic structure and optical properties of halide double perovskites from a Wannier-localized optimally-tuned screened range-separated hybrid functional

Halide double perovskites are a chemically diverse and growing class of compound semiconductors that are promising for optoelectronic applications. However, the prediction of their fundamental gaps and optical properties with density functional theory (DFT) and ab initio many-body perturbation theory has been a significant challenge. Recently, a nonempirical Wannier-localized optimally tuned screened range-separated hybrid (WOT-SRSH) functional has been shown to accurately produce the fundamental band gaps of a wide set of semiconductors and insulators, including lead halide perovskites. Here, in this study, we apply the WOT-SRSH functional to five halide double perovskites and compare the results with those obtained from other known functionals and previous GW calculations. We also use the approach as a starting point for GW calculations and we compute the band structures and optical absorption spectrum for Cs 2 AgBiBr 6 , using both time-dependent DFT and the GW-Bethe-Salpeter equation approach. We show that the WOT-SRSH functional leads to accurate fundamental and optical band gaps, as well as optical absorption spectra, consistent with spectroscopic measurements, thereby establishing WOT-SRSH as a viable method for the accurate prediction of optoelectronic properties of halide double perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimizing Power Reclamation of Micro Hydro Turbines in WWTPs Aeration Basins

Abstract This study investigates the optimum operating conditions and design configurations that can optimize the power reclaimed by small hydro turbines derived by the rising water-bubble current. The rising current is generated by the compressed air introduced by the diffusers at the bottom of aeration basins of Wastewater Treatment Plants (WWTPs). While optimizing the power production, the standard oxygen transfer efficiency (SOTE) is monitored since it is a significant parameter that cannot be sacrificed in the operation of WWTPs. Using one set of turbine blades, it was found out that the highest velocity is obtained in the upper half of the water column (70% - 80%). In contrast, the lowest velocities were obtained just above the air diffuser and at the water surface. Testing started with using a single turbine (ST) to determine the location of the optimum power reclaimed at each tested airflow (1.18, 1.42, 1.65, and 1.89 L/s). Then using double turbine (DT) and triple turbine (TT) to compare their performance to the ST’s maximum power increased power reclamation. The maximum percentage of increase in power reclamation for DT is 19.59%, while it is 20.24% in the case of TT. At a commonly used airflow in WWTPs (1.42 L/s), the optimum configurations of DTs and TTs were selected to investigate the effect of having the proposed setup on the SOTE. For membrane diffusers, DTs and TTs limited the dispersion of the air bubbles in the tank, therefore, reducing the SOTE (8.3% for DT and 3.7% for the TT). The ceramic and sharp-nub diffusers were also tested versus rubber membrane ones to determine the effect of using the ceramic and sharp-nub diffusers on the power reclamation and SOTE. Ceramic diffusers neither achieve higher power reclamation than the membrane nor increases the SOTE. In contrast, sharp-nub diffusers increase the SOTE for all configurations compared to membranes, but this came into account of power reclamation, where sharp-nub diffusers cause a DT and a TT to produce less power than ST does.

Energy & Fuels↗
NASA NTRS1986

Evaluation of a hybrid hydrostatic bearing for cryogenic turbopump application

A hybrid hydrostatic bearing was designed to operate in liquid hydrogen at speeds to 80,000 rpm and radial loads to 440 n (100 lbf). The bearing assembly consisted of a pair of 20-mm angular-contact ball bearings encased in a journal, which was in turn supported by a fluid film of liquid hydrogen. The size and operating conditions of the bearing were selected to be compatible with the operating requirements of an advanced technology turbopump. Several test parameters were varied to characterize the bearing's steady-state operation. The rotation of the tester shaft was varied between 0 and 80,000 rpm. Bearing inlet fluid pressure was varied between 2.07 and 4.48 MPa (300 and 650 psia), while the fluid sump pressure was independently varied between 0.34 and 2.07 MPa (50 and 300 psia). The maximum radial load applied to the bearing was 440 N (110 lbf). Measured hybrid-hydrostatic-bearing stiffness was 1.5 times greater than predicted, while the fluid flow rate through the bearing was 35 to 65 percent less than predicted. Under two-phase fluid conditions, the stiffness was even greater and the flow rate was less. The optimal pressure ratio for the bearing should be between 0.2 and 0.55 depending on the balance desired between bearing efficiency and stiffness. Startup and shutdown cyclic tests were conducted to demonstrate the ability of the hybrid-hydrostatic-bearing assembly to survive at least a 300-firing-duty cycle. For a typical cycle, the shaft was accelerated to 50,000 rpm in 1.8 sec. The bearing operated for 337 start-stop cycles without failure.

Spica, P. W.↗
NASA NTRS2004

Real-Time Very High-Resolution Regional 4D Assimilation in Supporting CRYSTAL-FACE Experiment

To better understand tropical cirrus cloud physical properties and formation processes with a view toward the successful modeling of the Earth's climate, the CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment) field experiment took place over southern Florida from 1 July to 29 July 2002. During the entire field campaign, a very high-resolution numerical weather prediction (NWP) and assimilation system was performed in support of the mission with supercomputing resources provided by NASA Center for Computational Sciences (NCCS). By using NOAA NCEP Eta forecast for boundary conditions and as a first guess for initial conditions assimilated with all available observations, two nested 15/3 km grids are employed over the CRYSTAL-FACE experiment area. The 15-km grid covers the southeast US domain, and is run two times daily for a 36-hour forecast starting at 0000 UTC and 1200 UTC. The nested 3-km grid covering only southern Florida is used for 9-hour and 18-hour forecasts starting at 1500 and 0600 UTC, respectively. The forecasting system provided more accurate and higher spatial and temporal resolution forecasts of 4-D atmospheric fields over the experiment area than available from standard weather forecast models. These forecasts were essential for flight planning during both the afternoon prior to a flight day and the morning of a flight day. The forecasts were used to help decide takeoff times and the most optimal flight areas for accomplishing the mission objectives. See more detailed products on the web site http://asd-www.larc.nasa.gov/mode/crystal. The model/assimilation output gridded data are archived on the NASA Center for Computational Sciences (NCCS) UniTree system in the HDF format at 30-min intervals for real-time forecasts or 5-min intervals for the post-mission case studies. Particularly, the data set includes the 3-D cloud fields (cloud liquid water, rain water, cloud ice, snow and graupe/hail).

Wang, Donghai↗
NASA NTRS2014

Development Status of a CVD System to Deposit Tungsten onto UO2 Powder via the WCI6 Process

Nuclear Thermal Propulsion (NTP) is under development for deep space exploration. NTP's high specific impulse (> 850 second) enables a large range of destinations, shorter trip durations, and improved reliability. W-60vol%UO2 CERMET fuel development efforts emphasize fabrication, performance testing and process optimization to meet service life requirements. Fuel elements must be able to survive operation in excess of 2850 K, exposure to flowing hydrogen (H2), vibration, acoustic, and radiation conditions. CTE mismatch between W and UO2 result in high thermal stresses and lead to mechanical failure as a result UO2 reduction by hot hydrogen (H2) [1]. Improved powder metallurgy fabrication process control and mitigated fuel loss can be attained by coating UO2 starting powders within a layer of high density tungsten [2]. This paper discusses the advances of a fluidized bed chemical vapor deposition (CVD) system that utilizes the H2-WCl6 reduction process.

Mireles, O. R.↗
DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Deterministic Multivariate Clustering Method for Drive Cycle Generation from In-Use Vehicle Data

Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data. This paper explores the development and initial validation of a method of generating representative drive cycles from large collections of real-world vehicle data using a deterministic multivariate clustering approach. Starting with theory and diving into the methodology behind representative cycle generation, the paper aims to also present graphical and tabular results of initial validation via vehicle simulation and chassis dynamometer testing. Additional topics for further research and areas for ongoing development will also be presented.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

Patched Local Lunar Gravity Solutions using GRAIL Data

We present a method to determine local gravity fields for the Moon using Gravity Recovery and Interior Laboratory (GRAIL) data. We express gravity as gridded gravity anomalies on a sphere, and we estimate adjustments to a background global start model expressed in spherical harmonics. We processed GRAIL Ka-band range-rate data with a short-arc approach, using only data over the area of interest. We determine our gravity solutions using neighbor smoothing constraints. We divided the entire Moon into twelve regions and two polar caps, with a resolution of 0.15˚ x 0.15˚ (which is equivalent to degree and order 1199 in spherical harmonics), and determined the optimal smoothing parameter for each area by comparing localized correlations between gravity and topography for each solution set. Our selected areas share nodes with surrounding areas and they are overlapping. To mitigate boundary effects, we patch the solutions together by symmetrically omitting the boundary parts of overlapping solutions. Our new solution has been iterated, and it has improved correlations with topography when compared to a fully iterated global model. Our method requires fewer resources, and can easily handle regionally varying resolution or constraints. The smooth model describes small-scale features clearly, and can be used in local studies of the structure of the lunar crust.

Sander Goossens↗
DOE OSTI2025

Optimization of spray breakup model parameters for predicting fuel spray and film characteristics in gasoline direct injection engines

This study investigated the behavior of gasoline direct injection (GDI) sprays using computational fluid dynamics (CFD). The authors developed an approach to identify optimal spray breakup model parameters by evaluating an error function across numerous simulations, with the goal of minimizing discrepancies from experimental data. Using the optimal setup, the simulated spray matched well with projected liquid volume distributions, liquid penetration, and spray width measured in a constant-pressure continuous-flow chamber. To further validate the approach, the same setup was tested across various fuels, injectors, and operating conditions. Subsequently, the optimal setup, along with a recently developed spray-wall interaction model, were applied to a direct-injection spark-ignited engine under late-injection conditions to predict and evaluate fuel film formation and evolution at varying engine coolant temperatures. Here, with the centrally mounted injector directing the spray toward the piston, simulations indicated that the spray tends to impinge on the piston surface. The proposed simulation framework also accurately captured the aggregate film area on the piston surface, aligning with previously published experimental results. Moreover, simulations showed that increasing the coolant temperature from cold start conditions (333 K) to warm conditions (363 K) reduced the fuel mass deposited on the piston by roughly 50%. Furthermore, for the spray-guided engine configuration studied in this work, the CFD model predicted minimal film deposition on the spark plug electrodes regardless of the coolant temperatures due to a relatively weak in-cylinder flow during the compression phase.

Computational fluid dynamics (CFD)↗
DOE OSTI2024

Interpenetrated Structures for Enhancing Ion Diffusion Kinetics in Electrochemical Energy Storage Devices

The architectural design of electrodes offers new opportunities for next-generation electrochemical energy storage devices (EESDs) by increasing surface area, thickness, and active materials mass loading while maintaining good ion diffusion through optimized electrode tortuosity. However, conventional thick electrodes increase ion diffusion length and cause larger ion concentration gradients, limiting reaction kinetics. We demonstrate a strategy for building interpenetrated structures that shortens ion diffusion length and reduces ion concentration inhomogeneity. This free-standing device structure also avoids short-circuiting without needing a separator. The feature size and number of interpenetrated units can be adjusted during printing to balance surface area and ion diffusion. Starting with a 3D-printed interpenetrated polymer substrate, we metallize it to make it conductive. This substrate has two individually addressable electrodes, allowing selective electrodeposition of energy storage materials. Using a Zn//MnO 2 battery as a model system, the interpenetrated device outperforms conventional separate electrode configurations, improving volumetric energy density by 221% and exhibiting a higher capacity retention rate of 49% compared to 35% at temperatures from 20 to 0 °C. Our study introduces a new EESD architecture applicable to Li-ion, Na-ion batteries, supercapacitors, etc.

25 ENERGY STORAGE↗
DOE OSTI2021

Selective Oxidative Coupling of Amines Using Mesoporous MoO x Catalysts

In this paper, we report a synthesis method for highly porous molybdenum oxide via molybdenum-oxo cluster formation under acidic conditions providing extraordinary stability. Synthesized materials indicate higher valences of molybdenum as compared to the commercial standards as verified through X-ray photoelectron spectroscopy, electron paramagnetic resonance spectroscopy, and ultraviolet–visible spectroscopy. The formation of a 91% orthorhombic molybdenum oxide bulk structure was verified through powder X-ray diffraction analysis. The effect of the hydrogen peroxide solvent system was optimized to obtain pore diameters as big as 17.4 nm and pore volumes as high as 0.168 cm 3 /g. These materials serve as great catalysts providing excellent yields of imine via amine coupling, having first-order kinetics with a turnover number as good as 27.93 with a slight decrease to 22.04 even after the fourth cycles. Surface hydroxyl species on the catalyst aid in the solid acid catalysis to jump-start the reaction.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Configuration-shape-size optimization of space structures by material redistribution

This project investigates the configuration-shape-size optimization (CSSO) of orbiting and planetary space structures. The project embodies three phases. In the first one the material-removal CSSO method introduced by Kikuchi and Bendsoe (KB) is further developed to gain understanding of finite element homogenization techniques as well as associated constrained optimization algorithms that must carry along a very large number (thousands) of design variables. In the CSSO-KB method an optimal structure is 'carved out' of a design domain initially filled with finite elements, by allowing perforations (microholes) to develop, grow and merge. The second phase involves 'materialization' of space structures from the void, thus reversing the carving process. The third phase involves analysis of these structures for construction and operational constraints, with emphasis in packaging and deployment. The present paper describes progress in selected areas of the first project phase and the start of the second one.

Vandenbelt, D. N.↗
NASA NTRS1993

Extended ecosystem signatures with application to Eos synergism requirements

The primary objective is to define the advantages of synergistically combining optical and microwave remote sensing measurements for the determination of biophysical properties important in ecosystem modeling. This objective was approached in a stepwise fashion starting with ground-based observations of controlled agricultural and orchard canopies and progressing to airborne observations of more natural forest ecosystems. This observational program is complemented by a parallel effort to model the visible reflectance and microwave scattering properties of composite vegetation canopies. The goals of the modeling studies are to verify our basic understanding of the sensor-scene interaction physics and to provide the basis for development of inverse models optimized for retrieval of key biophysical properties. These retrieval algorithms can then be used to simulate the expected performance of various aspects of Eos including the need for simultaneous SAR and HIRIS observations or justification for other (non-synchronous) relative timing constraints and the frequency, polarization, and angle of incidence requirements for accurate biophysical parameter extractions. This program completed a very successful series of truck-mounted experiments, made remarkable progress in development and validation of optical reflectance and microwave scattering models for vegetation, extended the scattering models to accommodate discontinuous and periodic canopies, developed inversion approaches for surface and canopy properties, and disseminated these results widely through symposia and journal publications. In addition, the third generation of the computer code for the microwave scattering models was provided to a number of other US, Canadian, Australian, and European investigators who are currently presenting and publishing results using the MIMICS research code.

Ulaby, Fawwaz T.↗