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NASA NTRS2017

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗

NASA NTRS2019

Improvements to Ozone Analyses Using Hyperspectral Sounders in the 9.6 μm Band

Previously, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System Atmospheric Data Assimilation System (GEOS-ADAS) were limited to assimilating temperature and moisture. The ozone sensitive 9.6 m region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 m region have been operational at ECMWF for several years (Dragani and McNally, 2013; Eresmaa et al., 2017). With this study, similar improvements using the GEOS-ADAS are presented. Channels were selected from available operational subsets evaluating information content and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered in developing the study. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). Inclusion of inter-channel correlation error to the selected ozone channels are expected to improve ozone analyses further along with improve analyses overall. It is anticipated that inclusion of these ozone sensitive channels will be used to improve NASA GMAO products in the near future.

GEOS-ADAS↗

NASA NTRS2018

Improving the S/X Celestial Reference Frame in the South

We believe that the S/X celestial reference frame(CRF) can be improved in the far-south by a factor of 2 in density and a factor of 2.5 in precision. We have started a collaboration to meet these goals. We have increased the data rates on existing IV Sastrometric sessions in the south from 256 Mbps to 1 Gbps. We will use this sensitivity to detect weaker sources and to improve the precision of sources in the southern S/X CRF, while simultaneously increasing the number of sources, in particular the overlap with other frames such as K-and Ka-band in the radio and the Gaia frame in the optical. VLBI observations in the southern celestial hemisphere have always been more difﬁcult both because there are fewer radio telescopes in the south than in the north, and because there are fewer known reference sources in the south. There have been many efforts in recent years to increase the number of known reference sources in the south, in particular the LBA calibrator Survey (LCS), which has already produced a signiﬁcant improvement at X-band. The ICRF-3 is expected to make signiﬁcant improvements in the south, however the south has not yet reached parity with the north and much work remains to be done. Therefore dedicated astrometric and imaging observations have already begun to improve the southern CRF at S/Xbands.

Basu, Sayan↗

NASA NTRS2022

Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+

To date, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, and harvesting). The SWAT+ (Soil and Water Assessment Tool) model represents agricultural land by default in a generic way, where the start of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and subtropical regions such as sub-Saharan Africa, where crop growth dynamics are mainly controlled by rainfall rather than temperature. In this study, we present an approach on how to incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a regional SWAT+ model for northeastern Africa. We evaluate the influence of the crop phenology representation on simulations of leaf area index (LAI) and evapotranspiration (ET) using LAI remote sensing data from Copernicus Global Land Service (CGLS) and WaPOR (Water Productivity through Open access of Remotely sensed derived data) ET data, respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations, especially for regions with a single cropping cycle. However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. In addition, the improvement of the cropping season also helps to improve soil erosion estimates, as the timing of crop cover controls erosion rates in the model. With more realistic growing seasons, soil erosion is largely reduced for most agricultural hydrologic response units (HRUs), which can be considered as a move towards substantial improvements over previous estimates. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in areas where they occur using regional to global hydrological models.

crop phenology↗

NASA NTRS2022

Evaluation and Improvement of System-of-Systems Resilience in a Simulation of Wildfire Emergency Response

Because of the increasing threat that wildfires pose, there is interest in leveraging new technologies to improve firefighting. Specifically, Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) promise to improve firefighters’ situational awareness, coordination, communications, safety, and strategy. While these technologies could be beneficial, there has been little formal investigation into how much benefit would occur and whether these benefits would outweigh hazards introduced by these systems. To better understand the impacts of these technologies, this paper presents a high-level dynamic simulation for evaluating wildfire response performance and resilience incorporating fire propagation, surveillance and communication, response planning, and the resulting mitigation actions. This simulation is then used to study the impact of communications and surveillance improvement, considering (1) the effect on fire containment and ground crew injuries and (2) the effect of introduced and existing disruptive fault scenarios. Simulating this model over a large number of scenarios finds that these changes can improve containment and reduce ground crew injuries. While these improvements generalize over both existing and introduced single-fault scenarios and thus result in a more resilient system, they could be negated if the introduced communications infrastructure is prone to full-scale outages.

modeling↗

NASA NTRS2021

Improvements to the Search for Cosmic Dawn Using the Long Wavelength Array

We present recent improvements to the search for the global Cosmic Dawn signature using the Long Wavelength Array station located on the Sevilleta National Wildlife Refuge in New Mexico, USA (LWA{SV). These improvements are both in the methodology of the experiment and the hardware of the station. An improved observing strategy along with more sophisticated temperature calibration and foreground modelling schemes have led to improved residual RMS limits. A large improvement over previous work using LWA{SV is the use of a novel achromatic beamforming technique which has been developed for LWA{SV. We present results from an observing campaign which contains 29 days of observations between March 10th, 2021 and April 10th 2021. The reported residual RMS limits are 6 times above the amplitude of the potential signal reported by the Experiment to Detect the Global EoR Signature (EDGES) collaboration.

Christopher Dilullo↗

NASA NTRSDate not supplied

Astrobee: Improving Capabilities for Free Flying Robotic Technology Demonstrations

The Astrobee Project has completed three years operating inside the ISS. Three Astrobee Free Flyers reached the ISS in April 2019 and are currently hosting a variety of users. During this time, Astrobee has advanced the state of the art in free-flying robots on ISS, operated over 100 sessions, logged over 750 hours of free-flyer operation, and made several capability improvements. Astrobee’s primary objective is to provide a highly flexible and capable free-flying robotic research platform to enable future guest scientist investigations. However, Astrobee is also demonstrating the feasibility of intra-vehicular robots (IVR) for performing key caretaking functions within exploration vehicles as part of NASA’s Moon-to-Mars exploration strategy. IVR capabilities will be especially vital during uncrewed mission phases. For example, current plans call for the lunar Gateway to be uncrewed >85% of the time. Astrobee’s baseline implementation supports free-flying camera and sensor survey use cases. Astrobee guest scientists can deploy software updates and hardware payloads to extend its capabilities. Astrobee is continuously improving its navigation robustness, general flight software maturity, and ISS interior maps, both through the baseline Astrobee operations and with the help of the ISAAC project. Astrobee began with mapping, localization, and operations in the Japanese Experiment Module (JEM), and has expanded to mapping in Node 2 and the US Lab. Astrobee has improved localization and operational robustness through improved mapping processes, algorithm updates (Soussan 2022) that reduce the occurrences of lost localization as well as developed recovery techniques to return to a good localization fix when loss of localization does occur. Future guest science experiments currently in development could demonstrate cargo transfer, fault isolation, free flyer and stationary robot collaboration, microgravity fluid transfer, and new docking mechanisms, among others. This presentation will focus on 1) Astrobee technical capabilities 2) What Astrobee can provide to a guest science experiment 3) Astrobee’s recent improvements 4) Possibilities for using Astrobee for future investigations. Soussan, R., Kumar, V., Coltin, B. and Smith, T. (2022) AstroLoc: An Efficient and Robust Localizer for a Free-flying Robot, Proc. Int. Conf. Rob. Autom. (ICRA) [to appear]

Astrobee↗

NASA NTRS2023

Improving the MODIS LAI Compositing Using Prior Time-Series Information

The Moderate Resolution Imaging Spectroradiometer (MODIS) long-term leaf area index (LAI) products have significantly contributed to global energy fluxes, climate change, and biogeochemistry research. However, the maximum fraction of photosynthetically active radiation absorbed by vegetation (Max-FPAR) compositing strategy of the Collection 6 (C6) products dictates that the main or backup algorithm is always triggered by observations of different quality, which indirectly causes the observed instability in the LAI time-series. Based on MODIS daily LAI retrievals, this study develops a prior knowledge time-series compositing algorithm (PKA) using a linear kernel driven (LKD) model. Our results show that the newly proposed PKA can significantly improve the LAI composites compared to the Max-FPAR strategy using ground-based observations for validation. We found that the PKA performs better than Max-FPAR in various aspects (different sites, seasons, and retrieval index (RI) ranges), with R2 increasing from 0.69 to 0.76 and root means square error (RMSE) decreasing from 1.01 to 0.84 compared to GBOV ground truth. The same improvement was shown for the ground truth LAIs measured at the Honghe and Hailun sites in northeastern China, with R2 increasing from 0.23 to 0.41 and RMSE decreasing from 1.27 to 1.25. In addition, three newly proposed temporal uncertainty metrics (time-series stability, TSS and time-series anomaly, TSA and reconstruction error metric, RE (the proximity to the main RT-based retrievals)) were applied to compare the stability of LAI time-series before and after PKA implementation. We found that the time series stability of PKA LAI was improved, the time series anomalies were reduced, and the retrieval rates of the main algorithm were also greatly enhanced compared to Max-FPAR LAI. A case intercomparison for Max-FPAR-MODIS, Max-FPAR-VIIRS (Visible Infrared Imager Radiometer Suite), and PKA-MODIS LAIs in the Amazon Forest region showed that the PKA is also effective in improving the LAI retrieval over large regions with few qualified observations due to poor atmospheric conditions (RE decreased from 2.37/2.35 (Max-FPAR-MODIS/Max-FPAR-VIIRS) to 2.25 (PKA-MODIS) and RI increased from 61.94%/59.62% to 66.88%). The same improvement was seen in the BELMANIP 2.1 sites for almost all biomes except deciduous broadleaf forest, where the RE decreased from 1.85/2.13 to 1.15 overall. We note that the PKA has the potential to be easily implemented in the operational algorithms of subsequent MODIS and MODIS-like LAI Collections.

MODIS↗

DOE OSTI2022

Demonstrate Improved Ag Diffusion and Describe the Basis for Pd Penetration Modeling in SiC

In past work, an effective diffusivity coefficient was determined for Ag transport through the silicon carbide layer of a tristructural isotropic fuel particle. The effective diffusivity coefficient accounts for the microstructure of the silicon carbide and includes both bulk diffusion and grain boundary diffusion of Ag. In this report, the model has been improved by accounting for the enhanced concentration of vacancies in the bulk due to irradiation, which substantially influence bulk diffusivity at low temperatures. To improve the BISON model and make it fission rate dependent, effective diffusivity calculations have been performed that incorporate the radiation modified bulk diffusivity. The microstructure and irradiation-dependent effective diffusivity has also been implemented into BISON, and its predictions for Ag release from tristructural isotropic fuel have been successfully compared to AGR-1 post irradiation measurements. Moreover, a new feature has been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) to account for different grain boundary types. The Ag diffusivity in 5 (210)/[001] grain boundaries has been computed and was found to be greater than in random high-angle grain boundaries. The presence of the fission product Pd can also have an important effect on the properties of the silicon carbide layer in tristructural isotropic particles. The penetration of Pd into the silicon carbide layer causes a corrosion reaction that can lead to the failure of the silicon carbide layer; however, this corrosion reaction is not well understood. To enable an improved understanding of the mechanism, ab-initio molecular dynamics simulations of Pd interaction with bulk silicon carbide have been performed. The improved understanding of the reaction will form a basis for future improvements to the BISON’s Pd penetration failure model

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations (Final progress report)

This is the final technical report for the DOE Atmospheric System Research funded project entitled "Collaborative Proposal: Improving Understanding of the Internal Structure and Dynamics of Deep Convection Using ARM Observations and Large Eddy Simulations". This project addressed several science questions related to the structure and behavior of deep convective clouds in the atmosphere. It applied knowledge gained from this work to improve the deep cumulus convection parameterization in the Community Earth System Model (CESM). Specific outcomes related to the project include an improved understanding of: (1) how convective cloud environments regulate the size of thermals reaching the upper troposphere, and hence the shallow-to-deep convective transition; (2) the role of dynamic pressure forcing in thermal and convective cloud evolution; and (3) the role of vertical wind shear on the behavior of moist thermals and the transition from shallow to deep convection. Although the primary motivation of this project was to improve basic understanding of thermal dynamics in atmospheric convection, an important component of this work was using this improved understanding to modify the representation of entrainment and vertical velocity profiles in the Zhang-McFarlane cumulus parameterization used in CESM. This work also had a strong observational component, with analyses of Atmospheric Radiation Measurement (ARM) observations to characterize thermal characteristics and behavior. Observations collected during the ARM-supported CACTI field project were used with high-resolution simulations to explore environmental controls on deep convection initiation. Data from the ARM-supported MC3E field project were also used to evaluate the representation of updraft vertical velocities in the Zhang-McFarlane cumulus parameterization. This project directly supported the training of two post-doctoral researchers and led to 16 peer-reviewed published papers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

SAS4A/SASSYS-1 Modeling Improvements for the Transition to Natural Circulation

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. In recent years, SAS has undergone a number of improvements to enable improved safety analyses that meet end users’ modernized needs while complying with the current regulatory environment. Improvements made in versions 5.6 and 5.7 released within the last year include the development of anisotropic Reynolds number dependent loss coefficients throughout the core and heat transport systems, the ability to distinguish the transition friction factor from the fully developed laminar and turbulent friction factors, and timedependent direct coolant and wall heating for pipe-like elements in the heat transport systems. While it was possible to capture loss coefficients, friction factors, and heat transfer from an element to a heat sink within SAS in previous versions of the code, users were required to end the simulation and restart it to adjust the input to account for any significant changes to the values during the transient. With these improvements, users can better capture flow reversal, pump heating, and the transition from forced to natural circulation without being limited to constant orifice coefficients, constant heat sinks, or the need to restart the simulation and modify input. In order to demonstrate the application of these improvements, a loss of flow transient is simulated for the Advanced Burner Test Reactor (ABTR).

SAS4A/SASSYS-1↗

DOE OSTI2024

Improvement of Coal Power Plant Dry Cooling Technology through Application of Cold Thermal Energy Storage

The U.S. power infrastructure is currently heavily reliant on water cooling. The power plants in the U.S. account for approximately 40% of freshwater withdrawals, with 90% of it used in condenser cooling. The most used cooling technology in coal-fired power plants is a once-through condenser; however, this cooling method requires high water withdrawal rates and results in thermal pollution of the water source. Wet WCTs offer an alternative to once-through condensers due to much lower water withdrawals. However, these systems suffer from water consumption through evaporation making them undesirable options in areas subject to droughts and in arid areas. The direct dry cooled condensers (ACCs) and dry cooling towers (DCT) account for 1.8%, hybrid cooling (ACC + WCT) accounts for 0.5%, while other cooling technologies represent the rest (0.7%). The ACC/DCTs represent an attractive alternative for power plants; however, this technology has not been widely adopted in the US (less than 2% of power plants) due to its negative impact on plant performance. As a rule of thumb, dry cooling results in performance penalty equivalent to approximately 2%-point efficiency loss compared to wet cooling, although the actual magnitude varies with ambient dry bulb temperature, DBT which may vary considerably during the day. As DBT increases, the plant power output decreases, reaching a minimum at the hottest period of the day, which usually coincides with the highest electricity demand for air condition load. Therefore, performance of power plants using DCT/ACC cooling technology is the lowest during the summer mid-day when ambient temperature is the highest. For example, the decrease of the inlet air temperature to the DCT/ACC by 2 Deg C could generate up to 5% additional power at peak demand. It is, therefore, important to improve dry cooling technology to maintain the viability of coal-fired power plants in a carbon constrained future. The method for reducing the cooling air temperature and keeping it constant would mitigate this problem significantly. Objectives of this project were to develop, design, evaluate, and demonstrate a cost-effective system for improving performance of a DCT or ACC for thermal (coal-fired) power plant applications using a low-cost heat storage materials, such as pervious concrete (PC) and phase change material (PCM). Thus, the study focused on development of the system(s) that could be used to alleviate the difficulties in operating DCT/ACC during the summer months by storing cold energy during the nighttime in inexpensive materials PC and PCM and using it during the hottest period(s) of the day. Since very large quantities of cold energy need to be stored to make an impact on performance of a large power plant, it is essential that the storage materials and associated cold energy storage design(s) are inexpensive and the system is simple to build, maintain and operate. To achieve the project objectives, a comprehensive approach, including material development and characterization, component and system modeling, and laboratory- and prototype-scale experiments, was employed including modeling of the system components and of the entire system, development (engineering) of the materials for the heat storage modules of the Cold Thermal Energy Storage System (CTESS) and determination of their properties, design, manufacturing and setup of the laboratory- and prototype-scale test facility and testing, design, manufacturing and setup of the prototype-scale test facility. A modular design of CTESS was employed, where representative modules were designed as the integrated direct contact heat exchanger and thermal energy storage (TES) system. CTESS modules were manufactured and tested. Two prototype-scale designs of the CTESS modules were developed and tested. The use of CTESS increases plant generation increases since it lowers air temperature entering ACC/DCT and keeps it constant during the hottest time of the day. For a PCM-based CTESS, the ambient air temperature is lowered close to the PCM phase change temperature. The duration of the cooling effect depends on the latent heat and mass of PCM in the CTESS. For this project, commercial grade CaCl2 hexahydrate (CaCl2·6H2O or CC6) PCM with phase change temperature of 25 Deg. C was used due to its low cost. For practical reasons, the CTESS was designed to maintain the cooling effect for four hours. The low phase change temperature associated with the commercial grade PCM used in CTESS results in considerably higher improvement in net generation compared to the laboratory (pure) grade. The resistance to heat transfer results in lower net generation compared to the ideal case where resistance to heat transfer is zero. The results demonstrate that CTESS is effective in improving the performance of a dry cooling system. However, its effectiveness depends on the relationship between the ambient air conditions and PCM phase change temperature. As is the case with the heat rejection system, for the best performance, the PCM used in CTESS would need to be matched to the ambient air conditions. The results obtained in this report for selected geographical locations are valid for CC6 and demonstrate that the level of performance to be achieved by the technology will be location-dependent, as is the case with the air cooled condensers. The methodology for engineering of PC-PCM-based heat storage medium is applicable to other PCMs that may need to be used for other ambient air conditions and geographical locations.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Process Improvement For Pu-238 Production at Idaho National Laboratory

Idaho National Laboratory (INL) has supported the production of Pu-238 for future NASA deep space missions since 2017. Over this time, INL has worked to improve the qualification process of Pu-238 production targets as well as improve processes related to the shipping, storage, irradiation, and storage of Pu-238 production targets. Qualification of Pu-238 production targets began with flux measurements and scoping analysis to provide fundamental data to confirm the impacts on the operation of the Advanced Test Reactor (ATR), Fig1. Later, initial production targets were irradiated in ATR’s I-7 position, and then the South Flux Trap (SFT). A modified target design was then implemented which would use the full length of the ATR core and increase Pu-238 production. While working to improve and streamline the qualification of the Pu-238 production targets, INL worked to improve multiple operational aspects of the Pu-238 production process. These changes include updating procedures to streamline operations, supporting modification of shipping containers to contain five rather than one production target, reviewing target receipt procedures and changing work flow to provide flexibility in target receipt, and designing and fabricating support equipment for the storage and internal transfer of production targets

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Process Improvements For Pu-238 Production at Idaho National Laboratory

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2023

Reliability Improvement and Effective Switching Layer Model of Thin-Film MoS 2 Memristors

2D memristors have demonstrated attractive resistive switching characteristics recently but also suffer from the reliability issue, which limits practical applications. Previous efforts on 2D memristors have primarily focused on exploring new material systems, while damage from the metallization step remains a practical concern for the reliability of 2D memristors. Here, the impact of metallization conditions and the thickness of MoS 2 films on the reliability and other device metrics of MoS 2 -based memristors is carefully studied. The statistical electrical measurements show that the reliability can be improved to 92% for yield and improved by ≈16× for average DC cycling endurance in the devices by reducing the top electrode (TE) deposition rate and increasing the thickness of MoS 2 films. Intriguing convergence of switching voltages and resistance ratio is revealed by the statistical analysis of experimental switching cycles. An “effective switching layer” model compatible with both monolayer and few-layer MoS 2 , is proposed to understand the reliability improvement related to the optimization of fabrication configuration and the convergence of switching metrics. In conclusion, the Monte Carlo simulations help illustrate the underlying physics of endurance failure associated with cluster formation and provide additional insight into endurance improvement with device fabrication optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Improving vertical detail in simulated temperature and humidity data using machine learning

Atmospheric models used for weather forecasting and climate predictions discretise the atmosphere onto a vertical grid. There are however atmospheric phenomena that occur on scales smaller than the thickness of those model layers. The formation of low-level clouds due to temperature inversions is an example. This leads to atmospheric models underestimating, or even missing, these clouds and their radiative effects. Using radiosonde observations as training data, a machine learning model is used to improve the vertical detail of modelled profiles of temperature and specific humidity. In addition, a physics-informed machine learning model is developed and compared to the traditional approach; showing improvements in the cloud fraction profiles calculated from its predictions. The vertically enhanced profiles also improve the representation of layers of convective inhibition and anomalous refractivity gradients. This work facilitates targeted improvements to the representation of certain atmospheric processes without the burden of increased memory and computational cost from increasing vertical resolution throughout the whole model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Abstract Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree‐/rule‐based ML methods to cope with the bias‐variance tradeoff and result in more accurate models. We use the datasets collected for two parallel cancer deep learning CANDLE benchmarks, NT3 and P1B2, to build performance and power models based on hardware performance counters using single‐object and multiple‐objects ensemble learning to identify the most important counters for improvement on the Cray XC40 Theta at Argonne National Laboratory. Based on the insights from these models, we improve the performance and energy of P1B2 and NT3 by optimizing the deep learning environments TensorFlow, Keras, Horovod, and Python under the huge page size of 8 MB. Experimental results show that ensemble learning not only produces more accurate models but also provides more robust performance counter ranking. We achieve up to 61.15% performance improvement and up to 62.58% energy saving for P1B2 and up to 55.81% performance improvement and up to 52.60% energy saving for NT3 on up to 24,576 cores.

Wu, Xingfu↗

DOE OSTI2021

Impact of improved energy resolution on DUNE sensitivity to neutrino non-standard interactions

The full physics potential of the next-generation Deep Underground Neutrino Experiment (DUNE) is still being explored. In particular, there have been some recent studies on the possibility of improving DUNE’s neutrino energy reconstruction. The main motivation is that a better determination of the neutrino energy in an event-by-event basis will translate into an improved measurement of the Dirac C P phase and other neutrino oscillation parameters. To further motivate studies and improvements on the neutrino energy reconstruction, we evaluate the impact of energy resolution at DUNE on an illustrative new physics scenario, viz. non-standard interactions (NSI) of neutrinos with matter. We show that a better energy resolution in comparison to the ones given in the DUNE conceptual and technical design reports may significantly enhance the experimental sensitivity to NSI, particularly when degeneracies are present. While a better reconstruction of the first oscillation peak helps disentangling standard C P effects from those coming from NSIs, we find that the second oscillation peak also plays a nontrivial role in improving DUNE’s sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗