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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗
NASA NTRS1985

MAGSAT scalar anomaly map of South America

A scalar magnetic anomaly map was prepared for South America and adjacent marine areas directly from original MAGSAT orbits. The preparation of the map poses special problems, notably in the separation of external field and crustal anomalies, and in the reduction of data to a common altitude. External fields are manifested in a long-wavelength ring current effect, a medium-wavelength equatorial electrojet, and short-wavelength noise. The noise is reduced by selecting profiles from quiet periods, and since the electrojet is confined primarily to dusk profiles, its effect is minimized by drawing the data set from dawn profiles only. The ring current is corrected through the use of the standard ring current equation, augmented by further filtering with a Butterworth bandpass filter. Under the assumption that the time-variant ring current is best removed when a replication of redundant profiles is achieved, a test set of 25 groups of 3 nearly coincident orbits per group is set up for filtering with a range of long-wavelength cutoffs to determine which cutoff best replicates the residual profiles. Altitude differences are then normalized by an inversion of the profile data onto a grid of equivalent point dipoles, and recalculated at an altitude of 350 km. The resulting map, when compared to the 2 deg averaged map, shows more coherent anomalies, with notable differences in the region affected by the electrojet.

Ridgway, J. R.↗
DOE OSTI2016

Effects of downscaled high-resolution meteorological data on the PSCF identification of emission sources

The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizes (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

QUOTAS: A New Research Platform for the Data-driven Discovery of Black Holes

We present QUOTAS, a novel research platform for the data-driven investigation of supermassive black hole (SMBH) populations. While SMBH data—observations and simulations—have grown in complexity and abundance, our computational environments and tools have not matured commensurately to exhaust opportunities for discovery. To explore the BH, host galaxy, and parent dark matter halo connection—in this pilot version—we assemble and colocate the high-redshift, z > 3 quasar population alongside simulated data at the same cosmic epochs. As a first demonstration of the utility of QUOTAS, we investigate correlations between observed Sloan Digital Sky Survey (SDSS) quasars and their hosts with those derived from simulations. Leveraging machine-learning algorithms (ML), to expand simulation volumes, we show that halo properties extracted from smaller dark-matter-only simulation boxes successfully replicate halo populations in larger boxes. Next, using the Illustris-TNG300 simulation that includes baryonic physics as the training set, we populate the larger LEGACY Expanse dark-matter-only box with quasars, and show that observed SDSS quasar occupation statistics are accurately replicated. First science results from QUOTAS comparing colocated observational and ML-trained simulated data at z3 are presented. QUOTAS demonstrates the power of ML, in analyzing and exploring large data sets, while also offering a unique opportunity to interrogate theoretical assumptions that underpin accretion and feedback models. QUOTAS and all related materials are publicly available at the Google Kaggle platform. (The full data set—observational data and simulation data—are available at: https://www.kaggle.com/ and the codes are available at:https://www.kaggle.com/datasets/quotasplatform/quotas)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
NASA NTRS1994

Surface roughness measurements

The Optics Division is currently in the research phase of producing grazing-incidence mirrors to be used in x-ray detector applications. The traditional method of construction involves labor-intensive glass grinding. This also culminates in a relatively heavy mirror. For lower resolution applications, the mirrors may be of a replicated design which involves milling a mandrel as a negative of the final shape and electroplating the cylindrical mirror onto it. The mirror is then separated from the mandrel by cooling. The mandrel will shrink more than the 'shell' (mirror) allowing it to be pulled from the mandrel. Ulmer (2) describes this technique and its variations in more detail. To date, several mirrors have been tested at MSFC by the Optical Fabrication Branch by focusing x-ray energy onto a detector with limited success. Little is known about the surface roughness of the actual mirror. Hence, the attempt to gather data on these surfaces. The test involves profiling the surface of a sample, replicating the surface as described above, and then profiling the replicated surface.

Howard, Thomas G.↗
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Replicates, read numbers, and other important experimental design considerations for microbial RNA-seq identified using Bacillus thuringiensis datasets

RNA-seq is being used increasingly for gene expression studies and it is revolutionizing the fields of genomics and transcriptomics. However, the field of RNA-seq analysis is still evolving. Therefore, we specifically designed this study to contain large numbers of reads and four biological replicates per condition so we could alter these parameters and assess their impact on differential expression results. Bacillus thuringiensis strains ATCC10792 and CT43 were grown in two Luria broth medium lots on four dates and transcriptomics data were generated using one lane of sequence output from an Illumina HiSeq2000 instrument for each of the 32 samples, which were then analyzed using DESeq2. Genome coverages across samples ranged from 87 to 465X with medium lots and culture dates identified as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected for cultures grown using different medium lots and between different dates. The highly differentially expressed iron acquisition and metabolism genes, were a likely consequence of differing amounts of iron in the two media lots. Indeed, in this study RNA-seq was a tool for predictive biology since we hypothesized and confirmed the two LB medium lots had different iron contents (~two-fold difference). Furthermore, this study shows that the noise in data can be controlled and minimized with appropriate experimental design and by having the appropriate number of replicates and reads for the system being studied. We outline parameters for an efficient and cost effective microbial transcriptomics study.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗
NASA NTRS2005

Initial Development of a Metric to Describe the Level of Safety Associated with Piloting an Aircraft with Synthetic Vision Systems (SVS) Displays

Synthetic Vision Systems (SVS) displays provide pilots with a continuous view of terrain combined with integrated guidance symbology in an effort to increase situation awareness (SA) and decrease workload during operations in Instrument Meteorological Conditions (IMC). It is hypothesized that SVS displays can replicate the safety and operational flexibility of flight in Visual Meteorological Conditions (VMC), regardless of actual out-the-window (OTW) visibility or time of day. Significant progress has been made towards evolving SVS displays as well as demonstrating their ability to increase SA compared to conventional avionics in a variety of conditions. While a substantial amount of data has been accumulated demonstrating the capabilities of SVS displays, the ability of SVS to replicate the safety and operational flexibility of VMC flight performance in all visibility conditions is unknown to any specific degree. In order to more fully quantify the relationship of flight operations in IMC with SVS displays to conventional operations conducted in VMC, a fundamental comparison to current day general aviation (GA) flight instruments was warranted. Such a comparison could begin to establish the extent to which SVS display concepts are capable of maintaining an "equivalent level of safety" with the round dials they could one day replace, for both current and future operations. A combination of subjective and objective data measures were used to quantify the relationship between selected components of safety that are associated with flying an approach. Four information display methods ranging from a "round dials" baseline through a fully integrated SVS package that includes terrain, pathway based guidance, and a strategic navigation display, were investigated in this high fidelity simulation experiment. In addition, a broad spectrum of pilots, representative of the GA population, were employed for testing in an attempt to enable greater application of the results and determine if "equivalent levels of safety" are achievable through the incorporation of SVS technology regardless of a pilot's flight experience.

Bartolone, Anthony P.↗
DOE OSTI2022

Semi-empirical simulation of in-motion radiation detection systems

The Replicative Assessment of Spectroscopic Equipment (RASE) is an open-source software that uses experimental data as the basis to simulate the response of commercial radiation detectors to sources in various situations, particularly in the context of nuclear security and safeguards applications. Dynamic RASE introduces the capability to simulate scenarios where sources and detector are in relative motion. Position-dependent experimentally acquired gamma spectra are ingested by Dynamic RASE to build maps that describe the detector response over all space. These response maps are used to replicate the time-dependent energy spectra collected as sources move on a path near the detector. Here, a Gaussian process is used to build each map, incorporating a novel kernel adapted to the special case of radiation detection. The approach has been validated against experimental data acquired using a NaI-based detector for 137 Cs and 54 Mn sources. The capability to create accurate simulations using either long-dwell static measurements or dynamic pass-by measurements as source data has been demonstrated. Quantitative relative performance, benefits, and shortcomings are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Integrated Structural Analysis and Test Program

An integrated structural-analysis and structure-testing computer program is being developed in order to: Automate repetitive processes in testing and analysis; Accelerate pre-test analysis; Accelerate reporting of tests; Facilitate planning of tests; Improve execution of tests; Create a vibration, acoustics, and shock test database; and Integrate analysis and test data. The software package includes modules pertaining to sinusoidal and random vibration, shock and time replication, acoustics, base-driven modal survey, and mass properties and static/dynamic balance. The program is commanded by use of ActiveX controls. There is minimal need to generate command lines. Analysis or test files are selected by opening a Windows Explorer display. After selecting the desired input file, the program goes to a so-called analysis data process or test data process, depending on the type of input data. The status of the process is given by a Windows status bar, and when processing is complete, the data are reported in graphical, tubular, and matrix form.

Kaufman, Daniel↗
DOE OSTI2018

Structure of the HIV-1 Full-Length Capsid Protein in a Conformationally Trapped Unassembled State Induced by Small-Molecule Binding

The capsid (CA) protein plays crucial roles in HIV infection and replication, essential to viral maturation. The absence of high-resolution structural data on unassembled CA hinders the development of antivirals effective in inhibiting assembly. Unlike enzymes that have targetable, functional substrate-binding sites, the CA does not have a known site that affects catalytic or other innate activity, which can be more readily targeted in drug development efforts. We report the crystal structure of the HIV-1 CA, revealing the domain organization in the context of the wild-type full-length (FL) unassembled CA. The FL CA adopts an antiparallel dimer configuration, exhibiting a domain organization sterically incompatible with capsid assembly. A small compound, generated in situ during crystallization, is bound tightly at a hinge site ('H site'), indicating that binding at this interdomain region stabilizes the ADP conformation. Electron microscopy studies on nascent crystals reveal both dimeric and hexameric lattices coexisting within a single condition, in agreement with the interconvertibility of oligomeric forms and supporting the feasibility of promoting assembly-incompetent dimeric states. Solution characterization in the presence of the H-site ligand shows predominantly unassembled dimeric CA, even under conditions that promote assembly. Our structure elucidation of the HIV-1 FL CA and characterization of a potential allosteric binding site provides three-dimensional views of an assembly-defective conformation, a state targeted in, and thus directly relevant to, inhibitor development. Based on our findings, we propose an unprecedented means of preventing CA assembly, by 'conformationally trapping' CA in assembly-incompetent conformational states induced by H-site binding.

Du, Shoucheng↗
DOE OSTI2025

Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER

Global Storm-Resolving Models (GSRMs) are becoming increasingly vital for advancing climate modeling and improving the prediction of extreme weather events. Houston, a coastal region frequently affected by deep convective storms, offers an ideal setting to evaluate the ability of GSRMs to simulate deep convection. This study assesses the performance of the Doubly Periodic Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere Model (DP-SCREAM) using observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. DP-SCREAM effectively reproduces the diurnal cycles of clouds and precipitation, demonstrating much greater skill than the E3SM single column model. The DP-SCREAM is demonstrated to be applicable to coastal regions, partially due to the forcing data sets already capturing the influence of breezes. DP-SCREAM also replicates biases persistent in the global version of SCREAM: the underrepresentation of boundary layer shallow clouds, a lack of mid-level congestus clouds, and the popcorn convection, characterized by small and disorganized convective cells generating the strongest precipitation. To investigate these issues, two sensitivity experiments were conducted: increasing the mixing length and scaling up the buoyancy flux within the Simplified Higher Order Closure scheme. Increasing the mixing length improved mid-level congestus representation and reduced unrealistic early morning fog occurrence. Enhancing buoyancy flux only marginally improved the bias of underproduced big convective cells. In conclusion, an additional resolution sensitivity test at 0.5 km grid spacing demonstrated that a refined horizontal resolution alone is insufficient to resolve these biases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A cancer-associated polymorphism in ESCRT-III disrupts the abscission checkpoint and promotes genome instability

Cytokinetic abscission facilitates the irreversible separation of daughter cells. This process requires the endosomal-sorting complexes required for transport (ESCRT) machinery and is tightly regulated by charged multivesicular body protein 4C (CHMP4C), an ESCRT-III subunit that engages the abscission checkpoint (NoCut) in response to mitotic problems such as persisting chromatin bridges within the midbody. Importantly, a human polymorphism in CHMP4C (rs35094336, CHMP4C T232 ) increases cancer susceptibility. Here, we explain the structural and functional basis for this cancer association: The CHMP4C T232 allele unwinds the C-terminal helix of CHMP4C, impairs binding to the early-acting ESCRT factor ALIX, and disrupts the abscission checkpoint. Cells expressing CHMP4C T232 exhibit increased levels of DNA damage and are sensitized to several conditions that increase chromosome missegregation, including DNA replication stress, inhibition of the mitotic checkpoint, and loss of p53. Our data demonstrate the biological importance of the abscission checkpoint and suggest that dysregulation of abscission by CHMP4C T232 may synergize with oncogene-induced mitotic stress to promote genomic instability and tumorigenesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Distributed-Memory Sparse Deep Neural Network Inference Using Global Arrays

Partitioned Global Address Space (PGAS) models exhibit tremendous promise in developing efficient and productive distributed-memory parallel applications. They have been used extensively in scientific computations due to conveniently offering a ``shared-memory''-like model and convenient interfaces that separate communication with synchronization. Traditionally, PGAS communication models have been applied to dense/contiguously distributed data, but most modern applications depict varied levels of sparsity. Existing PGAS models require certain adaptations to support distributed sparse computations, since associated computations often require matrix arithmetic, in addition to data movement. The Global Arrays toolkit from Pacific Northwest National Laboratory (PNNL) is one of the earliest PGAS models to combine one-sided data communication and distributed matrix operations and is still used in the popular NWChem quantum chemistry suite. Recently, we have expanded the Global Arrays toolkit to support common sparse operations, like sparse matrix-dense matrix multiplies (SpMM), sparse matrix-sparse matrix multiplication (SpGEMM) and Sampled Dense-Dense Matrix Multiplication (SDDMM). As it turns out, these operations are the bedrock of sparse Deep Learning (DL); sparse deep neural networks and Graph Neural Networks (GNNs) have gained increasing attention recently in achieving speedups on training and inference with reduced memory footprints. Unlike scientific applications in High Performance Computing (HPC), modern (distributed-memory capable) DL toolkits often rely on non-standardized and closed-source vendor software optimizations, creating challenges in software-hardware co-design at scale. Our goal is to support a variety of distributed-memory sparse matrix operations and helper functions in the newly created Sparse Global Arrays (SGA), such that it is possible to build portable and productive Machine Learning scenarios for algorithm/software and hardware codesign purposes. Contemporary data-parallel schemes for training/inference are undergoing a major overhaul since model replication limits scalability and causes resource inefficiencies. As such, we have adopted tensor parallelism in decomposing the model and inputs, to mitigate memory issues. Current implementation is built on top of MPI and uses CPUs to maximize the portability across the platforms.

Distributed computing, machine learning↗
DOE OSTI2016

Battery Capacity Fading Estimation Using a Force-Based Incremental Capacity Analysis

Traditionally health monitoring techniques in lithium-ion batteries rely on voltage and current measurements. A novel method of using a mechanical rather than electrical signal in the incremental capacity analysis (ICA) method is introduced in this paper. This method derives the incremental capacity curves based onmeasured force (ICF) instead of voltage (ICV). The force ismeasured on the surface of a cell under compression in a fixture that replicates a battery pack assembly and preloading. The analysis is performed on data collected from cycling encased prismatic Lithium-ion Nickel-Manganese-Cobalt Oxide (NMC) cells. For the NMC chemistry, the ICF method can complement or replace the ICV method for the following reasons. The identified ICV peaks are centered around 40% of state of charge (SOC) while the peaks of the ICF method are centered around 70% of SOC indicating that the ICF can be used more often because it is more likely that an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV) will traverse the 70% SOC range than the 40% SOC. In addition the Signal to Noise ratio (SNR) of the force signal is four times larger than the voltage signal using laboratory grade sensors. The proposed ICF method is shown to achieve 0.42% accuracy in capacity estimation during a low C-rate constant current discharge. Future work will investigate the application of the capacity estimation technique under charging and operation under high C-rates by addressing the transient behavior of force so that an online methodology for capacity estimation is developed.

25 ENERGY STORAGE↗