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At least 1,783 records · Page 99

Space Shuttle processing - A case study in artificial intelligence

A scheduling system incorporating AI is described and applied to the automated processing of the Space Shuttle. The unique problem of addressing the temporal, resource, and orbiter-configuration requirements of shuttle processing is described with comparisons to traditional project management for manufacturing processes. The present scheduling system is developed to handle the late inputs and complex programs that characterize shuttle processing by incorporating fixed preemptive scheduling, constraint-based simulated annealing, and the characteristics of an 'anytime' algorithm. The Space-Shuttle processing environment is modeled with 500 activities broken down into 4000 subtasks and with 1600 temporal constraints, 8000 resource constraints, and 3900 state requirements. The algorithm is shown to scale to very large problems and maintain anytime characteristics suggesting that an automated scheduling process is achievable and potentially cost-effective.

Mollikarimi, Cindy↗

Uncertainties in the Thermal and Mechanical Properties of Particulate Composites Quantified

Particle-reinforced composites are candidate materials for a wide variety of aerospace and nonaerospace applications. The high costs and technical difficulties involved with the use of many fiber-reinforced composites often limit their use in many applications. Consequently, particulate composites have emerged as viable alternatives to conventional fiber-reinforced composites. Particulate composites can be processed to near net shapepotentially reducing the manufacturing costs. They are candidate materials where shock or impact properties are important. For example, particle-reinforced metal matrix composites have shown great potential for many automotive applications. Typically, these materials are aluminum matrix reinforced with SiC or TiC particles. Reinforced concrete can also be thought of as a particle-reinforced composite. In situ ceramics can be modeled as particulate composites and are candidate materials for many high-temperature applications. The characterization of these materials is fundamental to their reliable use. It has been observed that the overall properties of these composites exhibit scatter because of the uncertainty in the constituent material properties, and fabrication-related parameters.

Murthy, Pappu L. N.↗

Pulse Detonation Engine Test Bed Developed

A detonation is a supersonic combustion wave. A Pulse Detonation Engine (PDE) repetitively creates a series of detonation waves to take advantage of rapid burning and high peak pressures to efficiently produce thrust. NASA Glenn Research Center's Combustion Branch has developed a PDE test bed that can reproduce the operating conditions that might be encountered in an actual engine. It allows the rapid and cost-efficient evaluation of the technical issues and technologies associated with these engines. The test bed is modular in design. It consists of various length sections of both 2- and 2.6- in. internal-diameter combustor tubes. These tubes can be bolted together to create a variety of combustor configurations. A series of bosses allow instrumentation to be inserted on the tubes. Dynamic pressure sensors and heat flux gauges have been used to characterize the performance of the test bed. The PDE test bed is designed to utilize an existing calorimeter (for heat load measurement) and windowed (for optical access) combustor sections. It uses hydrogen as the fuel, and oxygen and nitrogen are mixed to simulate air. An electronic controller is used to open the hydrogen and air valves (or a continuous flow of air is used) and to fire the spark at the appropriate times. Scheduled tests on the test bed include an evaluation of the pumping ability of the train of detonation waves for use in an ejector and an evaluation of the pollutants formed in a PDE combustor. Glenn's Combustion Branch uses the National Combustor Code (NCC) to perform numerical analyses of PDE's as well as to evaluate alternative detonative combustion devices. Pulse Detonation Engine testbed.

Breisacher, Kevin J.↗

The Search for Habitable Worlds. 1. The Viability of a Starshade Mission

As part of NASA's mission to explore habitable planets orbiting nearby stars, this article explores the detection and characterization capabilities of a 4 m space telescope plus 50 m starshade located at the Earth-Sun L2 point, known as the New Worlds Observer (NWO). Our calculations include the true spectral types and distribution of stars on the sky, an iterative target selection protocol designed to maximize efficiency based on prior detections, and realistic mission constraints. We conduct simulated observing runs for a wide range in exozodiacal background levels (epsilon = 1-100 times the local zodi brightness) and overall prevalence of Earth-like terrestrial planets (eta(sub solar halo))0.1-1). We find that even without any return visits, the NWO baseline architecture (IWA = 65 mas, limiting FPB = 4 x 10(exp -11) can achieve a 95% probability of detecting and spectrally characterizing at least one habitable Earth-like planet and an expectation value of approximately 3 planets found, within the mission lifetime and delta V budgets, even in the worst-case scenario (eta(sub solar halo) = 0.1 and = epsilon = 100 zodis for every target). This achievement requires about 1 yr of integration time spread over the 5 yr mission, leaving the remainder of the telescope time for UV-NIR general astrophysics. Cost and technical feasibility considerations point to a "sweet spot" in starshade design near a 50 m starshade effective diameter. with 12 or 16 petals, at a distance of 70,000-100,000 km from the telescope.

Turnbull, Margaret C.↗

Development of a Quasi-monoenergetic 6 MeV Gamma Facility at NASA Goddard Space Flight Center

The 6 MeV Gamma Facility has been developed at NASA Goddard Space Flight Center (GSFC) to allow in-house characterization and testing of a wide range of gamma-ray instruments such as pixelated CdZnTe detectors for planetary science and Compton and pair-production imaging telescopes for astrophysics. The 6 MeV Gamma Facility utilizes a circulating flow of water irradiated by 14 MeV neutrons to produce gamma rays via neutron capture on oxygen (O-16(n,p)N-16 yields O-16* yields O-16 + gamma). The facility provides a low cost, in-house source of 2.742, 6.129 and 7.117 MeV gamma rays, near the lower energy range of most accelerators and well above the 2.614 MeV line from the Th-228 decay chain, the highest energy gamma ray available from a natural radionuclide. The 7.13 s half-life of the N-16 decay allows the water to be irradiated on one side of a large granite block and pumped to the opposite side to decay. Separating the irradiation and decay regions allows for shielding material, the granite block, to be placed between them, thus reducing the low-energy gamma-ray continuum. Comparison between high purity germanium (HPGe) spectra from the facility and a manufactured source, Pu-238/C-13, shows that the low-energy continuum from the facility is reduced by a factor approx. 30 and the gamma-ray rate is approx.100 times higher at 6.129 MeV.

NASA↗

Laser Calibration of an Impact Disdrometer

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

calibration↗

Implementation and experimental validation of nonlocal damage in a large-strain elasto-viscoplastic FFT-based framework for predicting ductile fracture in 3D polycrystalline materials

Ductile materials, such as metal alloys, can undergo substantial deformation before failure. Additionally, these materials are usually of polycrystalline composition and exhibit strongly anisotropic behavior at small length scales. Previously developed fast Fourier transform (FFT)-based models can model ductile fracture of isotropic materials or the elastic–plastic behavior of anisotropic polycrystalline materials; however, there remains a need to couple both capabilities. This work extends a large-strain FFT-based crystal plasticity model to simulate ductile fracture of polycrystalline materials. In this work, a triaxiality-based continuum damage mechanics (CDM) formulation is incorporated into a large-strain elasto-viscoplastic FFT (LS-EVPFFT) framework. The CDM formulation is augmented with an integral-based nonlocal regularization approach that correctly handles gas-phase material necessary to model unconstrained surfaces. To validate the damage-enabled LS-EVPFFT framework, mesoscale copper tensile coupons were machined using microwire electrical discharge machining and experimentally characterized using electron backscatter diffraction. In-situ optical digital image correlation was performed during uniaxial testing to provide a side-by-side comparison of the experimental and computational strain fields and stress–strain responses. The damage-enabled LS-EVPFFT framework can simulate the complete macroscopic stress–strain response of ductile polycrystals to failure. The model reproduces necking behavior that qualitatively agrees with experimental observations. By leveraging the relatively low computational cost of the damage-enabled LS-EVPFFT framework, the framework presented here allows the ductile fracture response of 3D polycrystalline materials to be tractably predicted.

36 MATERIALS SCIENCE↗

Supported and coordinated single metal site electrocatalysts

The ever-increasing global environmental and energy crisis issues necessitates technological innovation, especially in the development of renewable energy-related devices, such as electrochemical energy conversion and storage technologies, including fuel cells, water electrolyzers, and CO 2 electrolyzers. Reliable and sustainable energy conversion devices are highly dependent on engineering of electrocatalysts. Furthermore, state-of-the-art electrocatalysts for these electrochemical conversion systems are usually platinum group metal (PGM)-based nanoparticles with high cost, which has sparked intensive research on atomically dispersed single metal site electrocatalysts for decreasing metal loadings and boosting catalytic efficiencies by taking advantage of their inherent electronic effects, quantum size effects, and metal-support interactions. In this review, we first introduced the intrinsic active site identification and stabilization, followed by addressing the mutual metal-support interactions, and most important, their correlations with catalytic properties. Next, the advances in synthetic strategies and characterization techniques for single metal site electrocatalysts are highlighted. Additionally, recent advances in single metal site electrocatalysts designs for applications in electrochemical conversion reactions are also presented. Finally, remaining challenges and a forward-looking perspective on this field of research are provided.

25 ENERGY STORAGE↗

Radiation hard Ga 2 O 3 detectors for high energy physics

In this project, we explore the use of ultra-wide bandgap Ga 2 O 3 materials for fabricating next-generation radiation hard solid-state detectors for high energy physics (HEP) applications. As an emerging semiconductor, Ga 2 O 3 has ultra-wide bandgap (4.5-4.9 eV), high breakdown electric field (8 MV/cm) and much lower production cost compared with radiation hard diamond detectors, all of which make Ga 2 O 3 a great candidate material working in harsh radiation environment of future HEP experiments. The recent breakthrough of growth technologies of Ga 2 O 3 significantly improves the availability of large area single crystalline Ga 2 O 3 . We focus on an early proof-of-principle demonstration of Ga 2 O 3 detectors and conduct comprehensive material and detector characterization to evaluate the potential of the emerging Ga 2 O 3 as a new radiation-hard detector material. Our endeavors directly support the instrumentation development and update need of HEP experiments and fits very well into the DOE HEP “Detector R&D” research subprogram.

36 MATERIALS SCIENCE↗

Contrastive Machine Learning with Gamma Spectroscopy Data Augmentations for Detecting Shielded Radiological Material Transfers

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High Power Laser Diode Arrays for 2-Micron Solid State Coherent Lidars Applications

Laser diode arrays are critical components of any diode-pumped solid state laser systems, constraining their performance and reliability. Laser diode arrays (LDAs) are used as the pump source for energizing the solid state lasing media to generate an intense coherent laser beam with a high spatial and spectral quality. The solid state laser design and the characteristics of its lasing materials define the operating wavelength, pulse duration, and power of the laser diodes. The pump requirements for high pulse energy 2-micron solid state lasers are substantially different from those of more widely used 1-micron lasers and in many aspects more challenging [1]. Furthermore, the reliability and lifetime demanded by many coherent lidar applications, such as global wind profiling from space and long-range clear air turbulence detection from aircraft, are beyond the capability of currently available LDAs. In addition to the need for more reliable LDAs with longer lifetime, further improvement in the operational parameters of high power quasi-cw LDAs, such as electrical efficiency, brightness, and duty cycle, are also necessary for developing cost-effective 2-micron coherent lidar systems for applications that impose stringent size, heat dissipation, and power constraints. Global wind sounding from space is one of such applications, which is the main driver for this work as part of NASA s Laser Risk Reduction Program. This paper discusses the current state of the 792 nm LDA technology and the technology areas being pursued toward improving their performance. The design and development of a unique characterization facility for addressing the specific issues associated with the LDAs for pumping 2-micron coherent lidar transmitters and identifying areas of technological improvement will be described. Finally, the results of measurements to date on various standard laser diode packages, as well as custom-designed packages with potentially longer lifetime, will be reported.

Amzajerdian, Farzin↗

Exo-C: A Space Mission for Direct Imaging and Spectroscopy of Extrasolar Planetary Systems

Exo-C is NASAs first community study of a modest aperture space telescope designed for high contrast observations of exoplanetary systems. The mission will be capable of taking optical spectra of nearby exoplanets in reflected light, discovering previously undetected planets, and imaging structure in a large sample of circumstellar disks. It will obtain unique science results on planets down to super-Earth sizes and serve as a technology pathfinder toward an eventual flagship-class mission to find and characterize habitable Earth-like exoplanets. We present the mission/payload design and highlight steps to reduce mission cost/risk relative to previous mission concepts. Key elements are an unobscured telescope aperture, an internal coronagraph with deformable mirrors for precise wavefront control, and an orbit and observatory design chosen for high thermal stability. Exo-C has a similar telescope aperture, orbit, lifetime, and spacecraft bus requirements to the highly successful Kepler mission (which is our cost reference). The needed technology development is on-course for a possible mission start in 2017. This paper summarizes the study final report completed in January 2015. During 2015 NASA will make a decision on its potential development.

high contrast observations↗

A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height

A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

John E. Yorks↗

Characterization of a selective, zero power sensor for distributed sensing of hydrogen in energy applications

The use of hydrogen as a clean and renewable energy source is increasing rapidly for both vehicle and stationary applications. There are safety concerns for the locations in which hydrogen is made, used, and transported (i.e., pipelines and tanker trucks). Sensors are needed to comply with safety regulations and to enable a smooth and safe rollout of hydrogen as an alternative energy. However, hydrogen sensors do not yet exist that have the combined features of small size and low power for easy deployment coupled with high-volume manufacturability and low cost. This is necessary to accommodate the emerging fixed and mobile markets while retaining critical metrological metrics, including measurement range, detection limits, selectivity, fast response, stability, and long lifetime. An amperometric gas sensor for hydrogen (AGS) has been developed using an innovative manufacturing method. The sensor was designed using scalable fabrication strategies based on “Printed Electronics” (PE) methodology which are compatible with large-scale production. Prototype sensors were batch fabricated with multiple individual elements on a substrate compatible in size with a standard 8-inch wafer to enable high-volume, low-cost manufacturing, thereby leveraging PE and semiconductor fabrication infrastructure. This novel AGS was instrumented with control circuitry and evaluated for hydrogen detection in the range of 0–5000 ppmv H2 in air. Specific performance evaluations included assessment of the sensor measurement range, repeatability, and selectivity.

08 HYDROGEN↗

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Asynchronous quadratic control for constrained hidden markov jump linear systems with incomplete MTPM and MOCPM

Abstract This paper investigates the quadratic optimal control problem for constrained Markov jump linear systems with incomplete mode transition probability matrix (MTPM). Considering original system mode is not accessible, observed mode is utilized for asynchronous controller design where mode observation conditional probability matrix (MOCPM), which characterizes the emission between original modes and observed modes is assumed to be partially known. An LMI optimization problem is formulated for such constrained hidden Markov jump linear systems with incomplete MTPM and MOCPM. Based on this, a feasible state-feedback controller can be designed with the application of free-connection weighting matrix method. The desired controller, dependent on observed mode, is an asynchronous one which can minimize the upper bound of quadratic cost and satisfy restrictions on system states and control variables. Furthermore, clustering observation where observed modes recast into several clusters, is explored for simplifying the computational complexity. Numerical examples are provided to illustrate the validity.

Zhu, Jin↗

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗