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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Methodologies and Tools for Tuning Parallel Programs: 80% Art, 20% Science, and 10% Luck

The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessors. However, without effective means to monitor (and analyze) program execution, tuning the performance of parallel programs becomes exponentially difficult as program complexity and machine size increase. In the past few years, the ubiquitous introduction of performance tuning tools from various supercomputer vendors (Intel's ParAide, TMC's PRISM, CRI's Apprentice, and Convex's CXtrace) seems to indicate the maturity of performance instrumentation/monitor/tuning technologies and vendors'/customers' recognition of their importance. However, a few important questions remain: What kind of performance bottlenecks can these tools detect (or correct)? How time consuming is the performance tuning process? What are some important technical issues that remain to be tackled in this area? This workshop reviews the fundamental concepts involved in analyzing and improving the performance of parallel and heterogeneous message-passing programs. Several alternative strategies will be contrasted, and for each we will describe how currently available tuning tools (e.g. AIMS, ParAide, PRISM, Apprentice, CXtrace, ATExpert, Pablo, IPS-2) can be used to facilitate the process. We will characterize the effectiveness of the tools and methodologies based on actual user experiences at NASA Ames Research Center. Finally, we will discuss their limitations and outline recent approaches taken by vendors and the research community to address them.

Yan, Jerry C.↗
NASA NTRS2001

Science Autonomy in Robotic Exploration

Historical mission operations have involved: (1) return of scientific data; (2) evaluation of these data by scientists; (3) recommendations for future mission activity by scientists; (4) commands for these transmitted to the craft; and (5) the activity being undertaken. This cycle is repeated throughout the mission with command opportunities once or twice per day. For a rover, this historical cycle is not amenable to rapid long range traverses or rapid response to any novel or unexpected situations. In addition to real-time response issues, imaging and/or spectroscopic devices can produce tremendous data volumes during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios suggest enabling some science decisions to be made on-board the robots. These decisions involve automating various aspects of scientific discovery instead of the electromechanical control, health, and navigation issues associated with robotic operations. The robot retains access to the full data fidelity obtained by its scientific sensors, and is in the best position to implement actions based upon these data. Such an approach would eventually enable the robot to alter observations and assure only the highest quality data is obtained for analysis. Additionally, the robot can begin to understand what is scientifically interesting and implement alternative observing sequences, because the observed data deviate from expectations based upon current theories/models of planetary processes. Such interesting data and/or conclusions can then be prioritized and selectively transmitted to Earth; reducing memory and communications demands. Results of Ames' current work in this area will be presented.

Roush, Ted L.↗
NASA NTRS2001

Robotic Exploration: The Role of Science Autonomy

Historical mission operations have involved: (1) return of scientific data; (2) evaluation of these data by scientists; (3) recommendations for future mission activity by scientists; (4) commands for these transmitted to the craft; and (5) the activity being, undertaken. This cycle is repeated throughout the mission with command opportunities once or twice per day. For a rover, this historical cycle is not amenable to rapid long range traverses or rapid response to any novel or unexpected situations. In addition to real-time response issues, imaging and/or spectroscopic devices can produce tremendous data volumes during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios suggest enabling some science decisions to be made on-board the robots. These decisions involve automating various aspects of scientific discovery instead of the electromechanical control, health, and navigation issues associated with robotic operations. The robot retains access to the full data fidelity obtained by its scientific sensors, and is in the best position to implement actions based upon these data. Such an approach would eventually enable the robot to alter observations and assure only the highest quality data is obtained for analysis. Additionally, the robot can begin to understand what is scientifically interesting and implement alternative observing sequences, because the observed data deviate from expectations based upon current theories/models of planetary processes. Such interesting data and/or conclusions can then be prioritized and selectively transmitted to Earth; reducing memory and communications demands. Results of Ames' current work in this area will be presented.

Roush, Ted L.↗
NASA NTRS2005

HyperPASS, a New Aeroassist Tool

A new software tool designed to perform aeroassist studies has been developed by Global Aerospace Corporation (GAC). The Hypersonic Planetary Aeroassist Simulation System (HyperPASS) [1] enables users to perform guided aerocapture, guided ballute aerocapture, aerobraking, orbit decay, or unguided entry simulations at any of six target bodies (Venus, Earth, Mars, Jupiter, Titan, or Neptune). HyperPASS is currently being used for trade studies to investigate (1) aerocapture performance with alternate aeroshell types, varying flight path angle and entry velocity, different gload and heating limits, and angle of attack and angle of bank variations; (2) variable, attached ballute geometry; (3) railgun launched projectile trajectories, and (4) preliminary orbit decay evolution. After completing a simulation, there are numerous visualization options in which data can be plotted, saved, or exported to various formats. Several analysis examples will be described.

Gates, Kristin↗
NASA NTRS2007

Hydrogen Migration and Vinylidene Pathway for Formation of Methane in the 193 nm Photodissociation of Propene: CH3CH=CH2 and CD3CD=CD2

Photodissociation channels and the final product yields from the 193 nm photolysis of propene-h6 (CH2=CHCH3) and propene-d6 (CD2=CDCD3) have been investigated, employing gas chromatography, mass spectroscopy, and flame ionization (GC/MS/FID) detection methods. The yields of methane as well as butadiene relative to ethane show considerable variations when propene-h6 or propene-d6 are photolyzed. This suggests significant variances in the relative importance of primary photolytic processes and/or secondary radical reactions, occurring subsequent to the photolysis. Theoretical calculations suggest the potential occurrence of an intramolecular dissociation through a mechanism involving vinylidene formation, accompanied by an ethylenic H-migration through the pi-orbitals. This process affects the final yields of methane-h4 versus methane-d4 with respect to other products. The product yields from previous studies of the 193 nm photolysis of methyl vinyl ketone-h6 and -d6 (CH2=CHCOCH3, CD2=CDCOCD3), alternative precursors for generating methyl and vinyl radicals, are compared with the current results for propene.

Zhao, Yi-Lei↗
NASA NTRS2009

Precision Cleaning of Oxygen Systems and Components

Currently, NASA uses Dichloropentafluoropropane (HCFC-225), a Class II ozone depleting substance (ODs), to clean contaminated oxygen systems. Starting in 20 15, the Montreal Protocols and Clean Air Act prohibit the production and importation of all hydrochlorofluorocarbons (HCFC), except for limited use in refrigeration applications. Thus, a new non-ozone depleting solvent needs to be developed for use in cleaning. Optimally, such a solvent should also be environmentally benign or green to avoid needing to replace the new solvent with yet another solvent in the future due to other environmental concerns. Work for the first year consisted of two parts. The first part was developing a method of testing the cleaning efficiency of potential solvents. Stainless steel coupons were contaminated with a known weight of various contaminants and contaminant combinations and then immersed in solvent for ten minutes. The coupons were then removed and dried in an oven until all solvent had evaporated. Once dry, the coupons were weighed and the mass of the non-volatile residue (NVR) left on the coupon was determined. The cleaning efficiency of the solvents is reported as percent cleaning, with 100% cleaning being zero NVR left on the test coupon. The second half of the first goal was to use the develop method to perform baseline testing on current solvents. The second part of the work was to begin exploring alternative cleaning solvents. A variety of hydrofluorocarbons (HFCs) were tested. Preliminary testing was also performed with ionic liquids and aqueous surfactant solutions. Once potential solvents were identified, an analysis of the performance and environmental characteristics of each was to be conducted. Four contaminants were specified for use in testing. These are Mil-Spec-H-5606 (5606), a hydraulic fluid, Mil-H-83282B (83282), another hydraulic fluid, diethylhexyl sebacate (Sebacate), and WD-40. The structures of these contaminants are all similar, with long aliphatic hydrocarbon chains of lengths between fifteen and fifty. Contaminants were tested both individually and in combination. All combinations were done with equal weights of the constituent contaminants.

McLaughlin, Russell↗
NASA NTRS2013

Comparison of Failure Modes in 2-D and 3-D Woven Carbon Phenolic Systems

NASA Ames Research Center is developing Woven Thermal Protection System (WTPS) materials as a new class of heatshields for entry vehicles (Stackpoole). Currently, there are few options for ablative entry heatshield materials, none of which is ideally suited to the planetary probe missions currently of interest to NASA. While carbon phenolic was successfully used for the missions Pioneer Venus and Galileo (to Jupiter), the heritage constituents are no longer available. An alternate carbon phenolic would need to be qualified for probe missions, which is most efficient at heat fluxes greater than those currently of interest. Additional TPS materials such as Avcoat and PICA are not sufficiently robust for the heat fluxes required. As a result, there is a large TPS gap between the materials efficient at very high conditions (carbon phenolic) and those that are effective at low-moderate conditions (all others). Development of 3D Woven TPS is intended to fill this gap, targeting mid-density weaves that could with withstand mid-range heat fluxes between 1100 W/sq cm and 8000 W/sq cm (Venkatapathy (2012). Preliminary experimental studies have been performed to show the feasibility of WTPS as a future mid-range TPS material. One study performed in the mARC Jet Facility at NASA Ames Research Center characterized the performance of a 3D Woven TPS sample and compared it to 2D carbon phenolic samples at ply angles of 0deg, 23.5deg, and 90deg. Each sample contained similar compositions of phenolic and carbon fiber volume fractions for experimental consistency. The goal of this study was to compare the performance of the TPS materials by evaluating resulting recession and failure modes. After exposing both samples to similar heat flux and pressure conditions, the 2D carbon phenolic laminate was shown to experience significant delamination between layers and further pocketing underneath separated layers. The 3D Woven TPS sample did not experience the delamination or pocketing failure modes because z-fibers in the through-thickness direction provided extra reinforcement to hold material layers together. Therefore, the benefit of using a 3D weave architecture was shown to alleviate failure modes experienced by a 2D laminate sample of similar material composition. In summary this poster reviews the thermal response performance comparisons drawn between a 3D Woven TPS sample and 2D Carbon Phenolic samples after performing rigorous heating experiments in the mARC facility at NASA Ames. Although the mARC Facility is still in its developmental stages, researchers expect similar trends in failure modes observed from large scale arc jet facilities. This work helps demonstrate the viability of 3D Woven TPSs as a new TPS option for future atmospheric entry missions.

Rossman, Grant A.↗
NASA NTRS2016

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Li, Yonghong↗
NASA NTRS2017

Design Solutions for the Treatment of DMSD in the ISS Water Recovery System

Dimethylsilanediol (DMSD) has been identified as a problematic organic on ISS. This contaminant was initially identified in the Water Processor Assembly (WPA) product water in 2010 by the Total Organic Carbon Analyzer (TOCA). DMSD is not a crew health hazard at the levels observed in the product water, but it may degrade the performance of the Oxygen Generation System (OGS) which uses the WPA product water for electrolysis and does impact the effective operation of the WPA catalytic reactor. To mitigate these impacts, early replacement of the Multifiltration Beds in the WPA is required. An investigation has determined that the decomposition of atmospheric polydimethylsiloxanes (PDMSs) is the primary source of DMSD in the condensate. PDMSs are prevalent on ISS from a variety of sources, including crew hygiene products, adhesives, caulks, lubricants, and various nonmetallics. These PDMSs also contribute to degradation of the CHX hydrophilic coating, rendering it hydrophobic and therefore affecting its ability to transmit water to the condensate bus. In addition, literature research has determined that PDMSs are likely oxidized to DMSD in the atmosphere when exposed to hydroxyl radicals in the ISS atmosphere. To address these mechanisms, filters have been developed for removal of PDMSs from the ISS atmosphere. However, ongoing analysis indicates a significant reduction in atmospheric PDMSs is required to achieve a measurable reduction of DMSD in the condensate. As a result, additional measures are being pursued to mitigate this issue. First, credible sources are being investigated to quantity to the extent possible the significant sources of PDMSs and identify sources that can be reasonably removed from ISS. Second, a Reverse Osmosis technology is being investigated as an alternate means for removing DMSD from the condensate. This paper summarizes the current status of the overall effort to mitigate DMSD in the US condensate.

Perry, Jay↗
NASA NTRS2018

C++ Resource Intelligent Compilation for GPU Enabled Applications

We are nearing the limits of Moore's Law with current computing technology. As industries push for more performance from smaller systems, alternate methods of computation such as Graphics Processing Units (GPUs) should be considered. Many of these systems utilize the Compute Unified Device Architecture (CUDA) to give programmers access to individual compute elements of the GPU for general purpose computing tasks. Direct access to the GPU's parallel multi-core architecture enables highly efficient computation and can drastically reduce the time required for complex algorithms or data analysis. Of course not all systems have a CUDA-enabled device to leverage, and so applications must consider optional support for users with these devices. Resource Intelligent Compilation (RIC) addresses this situation by enabling GPU-based acceleration of existing applications without affecting users without GPUs. Resource Intelligent Compilation (RIC) creates C/C++ modules that can be compiled to create a standard CPU version or GPU accelerated version of a program, depending on hardware availability. This is accomplished through a toolbox of programming strategies based on features of the CUDA API. Using this toolbox, existing applications can be modified with ease to support GPU acceleration, and new applications can be generated with just a few simple modifications. All of this culminates in an accelerated application for users with the appropriate hardware, with no performance impact to standard systems. This memorandum presents all the important features involved in supporting and implementing RIC and an example of using RIC to accelerate an existing mathematical model, without removing support for standard users. Through this memorandum, NASA engineers can acquire a set of guidelines to follow for RIC-compliant development, seamlessly accelerating C/C++ applications.

GPU↗
NASA NTRS2017

Shape Memory Alloys (SMAs) for Non-Pneumatic Tires

Conventional mobility elements, such as pneumatic tires, suffer from a number of issues related to reliability. Two of the more prevalent problems are the high likelihood of single point failure owing to puncture (i.e. flat tire), and loss of efficiency due to reduction in tire pressure over time. In order to overcome these limitations, alternative compliant tire designs not requiring pneumatics have been developed. However, although current designs have significantly reduced the aforementioned issues, they tend to have their own set of limitations. First, non-pneumatic tires designed for high load applications often have restricted envelopment capability, making their performance less than optimal, especially on uneven terrain. Second, tires designed with larger envelopment capability tend to suffer from large amounts of plasticity (permanent deformation) or failure (rupture). Both of these limitations are the direct result of the choice of material being used for the design; conventional metals undergo plastic deformation at low strain while elastomer based designs are often too rigid for the localized deformations needed for high envelopment. Recent advancements at the NASA Glenn research center in a unique class of metals know as shape memory alloys (SMAs) has opened the design space for non-pneumatic compliant tire technologies allowing designs to incorporate orders of magnitude more deformation without damage. The work presented herein highlights the advantages of using SMAs as compared to conventional metals. Additionally, the development of a unique SMA compliant tire design capable of carrying up to 8.9 kN (2000 lbf) with reversible, local deformations on the order of the side wall height will be presented.

Padula, Santo↗
NASA NTRS2020

Scheduling NASA's Deep Space Network: Priorities, Preferences, and Optimization

NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40\% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process --- oversubsubscription and how to "fairly'" reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗
NASA NTRS2021

User Preference Optimization for Oversubscribed Scheduling of NASA’s Deep Space Network

NASA’s Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process — oversubsubscription and how to “fairly” reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗
NASA NTRS2023

Establishing a Pathway to Greener Aviation

The burning and production of jet fuel in both commercial and regional planes at a high volume releases extreme levels of carbon emission as of its current state. This paper analyzes the implementation and benefits of three sustainable alternatives to traditional jet fuel: sustainable aviation fuel (SAF), hydrogen fuel cells, and electric batteries. A roadmap to show progress in reducing the carbon footprint of aviation is then proposed. The first phase of the roadmap involves the evolution of technology, validation, and testing of SAF-powered planes and the preliminary development of hydrogen production and propulsion and battery technology and the development of electric propulsion technologies. The second phase illustrates the widespread implementation of all three fuel sources where electric aviation will be enforced in short-range travel (30 min-3 hrs), medium-range aircraft (3-6 hrs) will use hydrogen fuel cells, and long-range (6+ hrs) airliners will utilize SAF. The third and final phase will enact the use of SAF and electric batteries for long-range applications while hydrogen fuel cells will dominate short- and medium-range aircraft. This roadmap, in combination with proper legislative action and corporate cooperation paired with public awareness, can help eliminate the usage of jet fuel in the aviation industry and replace it with three more sustainable and clean fuel sources.

green aviation↗
DOE OSTI2017

The U.S. Gas Flooding Experience: CO2 Injection Strategies and Impact on Ultimate Recovery

The Permian Basin in West Texas and southwestern New Mexico has seen 45 years of oil reserve growth through CO2 enhanced oil recovery (CO2 EOR). More than 60 CO2 EOR projects are currently active in the region’s limestone, sandstone and dolomite reservoirs. Water alternating gas (WAG) has been the development strategy of choice in the Permian for several technical and economic reasons. More recently, the technology started to get implemented in the much more porous and permeable clastic depositional systems of the onshore U.S. Gulf Coast. Continued CO2 injection (CGI), as opposed to WAG, was selected as the injection strategy to develop Gulf Coast oil fields, where CO2 injection volumes are significantly larger (up to 6 times larger) than those of the Permian. We conducted a compositional simulation based study with the objective of comparing the CO2 utilization ratios (volume of CO2 injected to produce a barrel of oil) of 4 conventional and novel CO2 injection strategies: (1) continuous gas injection (CGI), (2) water alternating gas (WAG), (3) water curtain injection (WCI), and (4) WAG and WCI combination. These injection scenarios were simulated using the GEM module from the Computer Modeling Group (CMG). GEM is an advanced general equation-of-state compositional simulator, which includes equation of state, CO2 miscible flood, CO2/brine interactions, and complex phase behavior. The simulator is set up to model three fluid phases including water, oil, and gas. Our study demonstrates how the selected field development strategy has a significant impact on the ultimate recovery of CO2-EOR projects, with GCI injection providing maximum oil recovery in absolute volume terms, but with WAG offering a more balanced technical-economical approach.

02 PETROLEUM↗
DOE OSTI2019

Exploring Molecular Mechanisms of Cosolvent Enhanced Biomass Deconstruction: An Overview of Recent Progress

In this chapter, we explore the mechanisms driving efficient thermochemical deconstruction and fractionation of lignocellulosic biomass in cosolvent mixtures for the production of biofuels and bioproducts. New approaches that combine molecular dynamics simulations with experimental characterization highlight the important role of cosolvents and their influence on molecular processes relevant to overcoming the natural recalcitrance of lignocellulose. From localized phase behavior on cellulose fibers to changes in lignin conformation, insights into cosolvent effects on biomass deconstruction involve understanding complex interactions between the solvent–solvent, solvent–substrate, and solvent–catalyst. Recently coordinated research efforts at multiple scales using computational tools, nano-scale imaging, and kinetic models have significantly advanced identification of high-performance cosolvents, shedding light on the mechanisms behind solvent-biomass interactions. Specifically, multifunctional cosolvents have been employed in leading biomass “solvolysis” technologies that favorably coordinate with dilute acids to solubilize and depolymerize all three primary biomass fractions of biomass: cellulose, hemicellulose, and lignin. As a result, recent work in studying solvent effects of multifunctional cosolvents has led to a paradigm shift toward the use of first principles to design biomass deconstruction techniques with the aim of maximizing total carbon utilization in biomass. The synergistic pairing of cosolvents with biomass deconstruction will lead scientists and engineers to overcome key technical and economic barriers of biomass processing, enabling a successful transition of the current energy landscape toward a future bioeconomy based on biomass as an alternative to petroleum.

Mostofian, Barmak↗
DOE OSTI2024

Towards Precision Photometric Type ia Supernova Cosmology With Machine Learning

The revolutionary discovery of dark energy and accelerating cosmic expansion was made with just 42 type Ia supernovae (SNe Ia) in 1999. Since then, large synoptic surveys, e.g., Dark Energy Survey (DES), have observed thousands more SNe Ia and the upcoming Rubin Legacy Survey of Space and Time (LSST) and Roman Space Telescope promise to deliver millions in the next decade. This unprecedented data volume can produce the required precision to unambiguously test concordance cosmology which could represent a monumental shift in our understanding of dark energy and its role in cosmic history. However, extracting a pure SN Ia sample with accurate redshifts for such a large dataset will be a challenge. Specifically, spectroscopic classification will not be possible for the vast majority of discovered objects, and only ~25% will have spectroscopic redshifts. This thesis presents a series of observational and methodological studies designed to address the questions associated with this new era of photometric SN Ia cosmology. First, we present a machine learning method for photometric classification of SNe, Supernova Classification with a COnvolutional Neural Network (SCONE). Photometric classification enables SNe with no spectroscopic information to be confidently categorized, and is a critical component of current and future analysis pipelines. SCONE achieves >99% accuracy distinguishing simulated SNe Ia from non-Ia SNe, and has been integrated into DES, LSST, and Roman analysis pipelines. We also demonstrate the efficacy of SCONE on early-time photometric classification, which will be vital for optimal allocation of spectroscopic resources. We show that SCONE can distinguish between 6 SN types with 75% accuracy on the night of initial discovery, comparable to results in the literature for full-phase SNe. Next, we study current methods for estimating SN Ia redshifts and propose a machine learning alternative that uses SN photometry alone to extract redshift information. Most SNe Ia inherit redshift information from their host galaxy, but the process of matching SNe to the correct host galaxy can be challenging. We systematically analyze the impact of incorrect redshifts from host galaxy mismatch on 5 years of DES SN data, and conclude that improved host matching or redshift estimation methods can reduce our systematic errors by ~10%. In response to this finding, we present a SN photometry-only method for estimating redshifts independent of host galaxy information, Photo-zSNthesis. We show that Photo-zSNthesis redshift estimates are accurate to within 2% across the full redshift range of LSST, a first in the literature. Finally, we focus on the robustness of machine learning (ML) algorithms for real-world and scientific applications. ML models generalize poorly beyond their training set and often experience severe performance degradation when deployed on new data. We demonstrate a general method for improving robustness that achieves new state-of-the-art results on astronomical object classification, wildlife identification, and tumor detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Sustainable Ammonia Synthesis – Exploring the scientific challenges associated with discovering alternative, sustainable processes for ammonia production

Ammonia (NH 3 ) is essential to all life on our planet. Until about 100 years ago, NH 3 produced by reduction of dinitrogen (N 2 ) in air came almost exclusively from bacteria containing the enzyme nitrogenase.. DOE convened a roundtable of experts on February 18, 2016. Participants in the Roundtable discussions concluded that the scientific basis for sustainable processes for ammonia synthesis is currently lacking, and it needs to be enhanced substantially before it can form the foundation for alternative processes. The Roundtable Panel identified an overarching grand challenge and several additional scientific grand challenges and research opportunities: -Discovery of active, selective, scalable, long-lived catalysts for sustainable ammonia synthesis. -Development of relatively low pressure (<10 atm) and relatively low temperature (<200 C) thermal processes. -Integration of knowledge from nature (enzyme catalysis), molecular/homogeneous and heterogeneous catalysis. -Development of electrochemical and photochemical routes for N 2 reduction based on proton and electron transfer -Development of biochemical routes to N 2 reduction -Development of chemical looping (solar thermochemical) approaches -Identification of descriptors of catalytic activity using a combination of theory and experiments -Characterization of surface adsorbates and catalyst structures (chemical, physical and electronic) under conditions relevant to ammonia synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗