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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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This paper reports on JPL's on-going research into MEMS gyroscopes. This paper will describe the gyroscope's fabrication-methods, a new 8-electrode layout developed to improve performance, and performance statistics of a batch of six gyroscopes recently rate tested.
The Crew Exploration Vehicle Parachute Assembly System (CPAS) project conducts computer simulations to verify that flight performance requirements on parachute loads and terminal rate of descent are met. Design of Experiments (DoE) provides a systematic method for variation of simulation input parameters. When implemented and interpreted correctly, a DoE study of parachute simulation tools indicates values and combinations of parameters that may cause requirement limits to be violated. This paper describes one implementation of DoE that is currently being developed by CPAS, explains how DoE results can be interpreted, and presents the results of several preliminary studies. The potential uses of DoE to validate parachute simulation models and verify requirements are also explored.
Time division multiplexing (TDM) is being developed as the readout technology of the X-ray integral field unit (X-IFU), a 3,168-pixel X-ray transition-edge sensor (TES) imaging spectrometer that is part of the European Space Agency's Athena satellite mission. Recent improvements in the low X-ray event count rate performance of TDM have been driven by increases in multiplexer bandwidth and the mitigation of settling transients. These methods and design changes have improved the 32-row multiplexed resolution of a NASA LPA 2.5a array from an initial (2.73 ± 0.03) eV to (1.97 ± 0.01) eV resolution at 5.9 keV. We discuss these recent advances in TDM readout, which have been implemented in an 8-column × 32-row spectrometer that will be deployed at the Lawrence Livermore National Laboratory electron beam ion trap (EBIT) facility, and present a model that will inform the design of future systems.
Smart inverters (SI) have huge potential in providing grid services which has not been fully realized yet. One of these grid services, distribution network voltage regulation by SI, can improve the network voltage by regulating the SI reactive and active power output. Voltage regulation by SI is much faster compared to traditional voltage regulating devices, e.g. tap changing transformer, capacitor banks. However, there is gap in available published literature on the characteristics of SIs when the SI is controlled by local controller or external control signal. This paper presents the experimental study to characterize SI reactive power regulation response to two different control methods: autonomous control method and remote dispatch method. It was found that IS reactive power regulation response could be significantly different in terms of delay, and ramp rate for these two methods. Finally, Power-Hardware-in-The-Loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL tests results show that SI response characteristics for autonomous control method and remote dispatch method need to be considered during planning for distribution network voltage regulation using SI.
The computation of dense matrix-matrix products (GEMMs) is central to many modeling and simulation workloads as well as AI/ML deep learning campaigns. In fact, millions of dollars are spent annually on computing GEMMs, and large model training demands are increasing exponentially. Specialized processors such as GPUs are designed to perform well for these operations. However, the performance of GEMMs on GPUs can exhibit complex behaviors depending on many factors, making it challenging to optimize the performance of GEMMs on these processors. In this study we undertake an examination of GEMM performance on several leading GPU models taken from product lines of GPUs to be deployed in forthcoming exascale computing systems. We show results to illustrate the many factors that can affect performance of GEMMs on GPUs. We then present data collected from a large number of test runs for an example GEMM operation to show the dependence behaviors of GEMM rate on matrix dimensions. Finally, we show results from machine learning-based performance models using novel feature engineering methods to fit the measured performance, providing a potential basis for GEMM performance tuning and autotuning methods for GPUs. Recommendations are also given for how to achieve high GEMM performance on modern GPUs.
Superconducting nanowire single photon detectors are capable of single-photon detection across a large spectral range, with near unity detection efficiency, picosecond timing jitter, and sub-10 µm position resolution at rates as high as 10 9 counts/s. In an effort to bring this technology into nuclear physics experiments, we fabricate Niobium Nitride nanowire detectors using novel material preparation methods and test their performance in strong magnetic fields. Furthermore, we demonstrate that these devices are capable of detection of 400 nm wavelength photons with saturated internal quantum efficiency at liquid helium temperatures and in magnetic fields potentially up to 8 T at high rates and with nearly zero dark counts.
High-performance networks provisioning 10/40-Gbps dedicated channels have been rapidly developed andincreasingly deployed to support big data transfers on the order of terabytes or petabytes in large-scale network-intensiveapplications. However, end users have not seen corresponding increase in application throughput mainly because traditional end-to-end transport methods are not optimized for such connections. New congestion or flow control mechanisms are desirable to meet the challenges brought to transport protocol design by dedicated connections. The advent and proliferation of multi-core processors make it now possible to improve application throughput by providing multiple processing and network resources to a single data transfer. Based on the existing PLUT method, we proposed a new dynamic buffer management scheme and an automatic parallelism tuning mechanism to achieve the maximal bottleneck rate. The performance superiority of PLUT is justified by the experimental results collected over a local 10Gbps dedicated connection.
Purpose: To implement a 3D dose verification procedure of Model-Based Dose Calculation Algorithms (MBDCAs) for {sup 192}Ir HDR brachytherapy, based on a novel Ferrous Xylenol-orange gel (FXG) and optical CT read-out. Methods: The TruView gel was employed for absolute dosimetry in conjunction with cone-beam optical CT read-out with the VISTA scanner (both from Modus Medical Inc, London, ON, Canada). A multi-catheter skin flap was attached to a cylindrical PETE jar (d=9.6cm, h=16cm) filled with FXG, which served as both the dosimeter and the water equivalent phantom of bounded dimensions. X- ray CT image series of the jar with flap attached was imported to Oncentra Brachy v.4.5. A treatment plan consisting of 8 catheters and 56 dwell positions was generated, and Oncentra-ACE MBDCA as well as TG43 dose results were exported for further evaluation. The irradiation was carried out with a microSelecton v2 source. The FXG dose-response, measured via an electron irradiation of a second dosimeter from the same batch, was linear (R2>0.999) at least up to 12Gy. A MCNP6 input file was prepared from the DICOM-RT plan data using BrachyGuide to facilitate Monte Carlo (MC) simulation dosimetry in the actual experimental geometry. Agreement between experimental (reference) and calculated dose distributions was evaluated using the 3D gamma index (GI) method with criteria (5%-2mm applied locally) determined from uncertainty analysis. Results: The TG-43 GI failed, as expected, in the majority of voxels away from the flap (pass rate 59% for D>0.8Gy, corresponding to 10% of prescribed dose). ACE performed significantly better (corresponding pass rate 92%). The GI evaluation for the MC data (corresponding pass rate 97%) failed mainly at low dose points of increased uncertainty. Conclusion: FXG gel/optical CT is an efficient method for level-2 commissioning of brachytherapy MBDCAs. Target dosimetry is not affected from uncertainty introduced by TG43 assumptions in 192Ir skin brachytherapy. Research co-financed by the ESF and Greek funds through the Operational Program Education and Lifelong Learning Investing in Knowledge Society of the NSRF. Research Funding Program: Aristeia. Modus Medical Devices Inc. provided a TruView dosimeter batch and Nucletron, and Elekta company, provided access to Oncentra Brachy v4.5, for research purposes.
Piperazine is a promising second-generation solvent for amine scrubbing in post-combustion CO2 capture. However, the oxidative degradation of PZ can cause environmental problems and economic loss. This work presents the effects of two mitigation methods: carbon treating and N2 sparging, on the PZ oxidation in long-term operations. The species and their respective quantities adsorbed by the activated carbon were tested in a bench-scale device. The carbon was then tested in the High Temperature Oxidation Reactor (HTOR), where the solvent oxidizes at a reasonably fast rate. Pilot plant campaigns were also performed at the UT Austin SRP and the National Carbon Capture Center (NCCC) and the effects were verified. When dissolved Fe is removed by carbon treating or other methods, available soluble Fe in the system dissolves and replaces the dissolved Fe. Therefore, all available Fe and ligands need to be removed for the mitigation to be effective. The sources of soluble Fe include fly ash and the corrosion of stainless steel, and the ligands are degradation products. 8 All PZ degraded solvents have two absorbance peaks at 320 nm and 538 nm. The 320 nm peak is caused by dissolved metals, especially Fe, complexed by degradation products. The 320 nm peak is related to the amine degradation level and can be used as a simple and efficient method to estimate the amine degradation rate. The pilot plant data suggest that NO2 can oxidize PZ significantly, possibly through radical reactions. 0.01 mmol/kg-hr absorption of NO2 increased the PZ oxidation rate from 1.2 mmol/kg-hr to 2.5 mmol/kg-hr.
As production of fuel cell vehicles and power systems increases there is a need to understand the process science of fuel cell manufacturing. Industrial production of polymer electrolyte membrane fuel cell (PEMFC) electrodes will rely on continuous roll-to-roll (R2R) coating methods to meet the rates needed for mass production. There are a variety of coating methods that could be used to coat catalyst layers. The different physics of each method may result in different morphologies and performance. Here we present the results of a study comparing fuel cell catalyst layers coated using two R2R coating methods: slot-die and gravure. These two methods were selected because the physics of applying the liquid to the substrate is very different between the two cases. Pt/C catalysts layers were coated directly onto carbon-fiber gas diffusion media to create gas diffusion electrodes (GDEs), without the use of a decal transfer process. These GDEs were assembled into membrane electrode assemblies (MEAs) by hot pressing to Nafion membranes. In situ performance and other electrochemical diagnostics were used to determine the influence of coating method on catalyst layer electrochemical properties. Electron microscopy was utilized to understand the influence of coating method on electrode morphology and its influence on electrochemical properties. We also explored the influence of solvent ratio to understand the potential coupling between ink formulation and coating methodology.
Forensic evidentiary backlogs are indicative of the growing need for cost-effective, high-throughput instrumental methods. One such emerging technology that shows high promise in meeting this demand while also allowing on-site forensic investigation is portable mass spectrometric (MS) instrumentation, particularly that which enables the coupling to ambient ionization techniques. While the benefits of rapid, on-site screening of contraband can be anticipated, the inherent legal implications of field-collected data necessitates that the analytical performance of technology employed be commensurate with accepted techniques. To this end, comprehensive analytical validation studies are required before broad incorporation by forensic practitioners can be considered, and are the focus of this work. Pertinent performance characteristics such as throughput, selectivity, accuracy/precision, method robustness, and ruggedness have been investigated. Reliability in the form of false positive/negative response rates is also assessed, examining the effect of variables such as user training and experience level. To provide flexibility toward broad chemical evidence analysis, a suite of rapidly-interchangeable ion sources has been developed and characterized through the analysis of common illicit chemicals and emerging threats like substituted phenethylamines. .
Distributed object storage architectures have become the de facto standard for high-performance storage in big data, cloud, and HPC computing. Object storage deployments using commodity hardware to reduce costs often employ object replication as a method to achieve data resilience. Repairing object replicas after failure is a daunting task for systems with thousands of servers and billions of objects, however, and it is increasingly difficult to evaluate such scenarios at scale on realworld systems. Resilience and availability are both compromised if objects are not repaired in a timely manner. In this work we leverage a high-fidelity discrete-event simulation model to investigate replica reconstruction on large-scale object storage systems with thousands of servers, billions of objects, and petabytes of data. We evaluate the behavior of CRUSH, a well-known object placement algorithm, and identify configuration scenarios in which aggregate rebuild performance is constrained by object placement policies. After determining the root cause of this bottleneck, we then propose enhancements to CRUSH and the usage policies atop it to enable scalable replica reconstruction. We use these methods to demonstrate a simulated aggregate rebuild rate of 410 GiB/s (within 5% of projected ideal linear scaling) on a 1,024-node commodity storage system. We also uncover an unexpected phenomenon in rebuild performance based on the characteristics of the data stored on the system.
Background: The recent observation of a neutron-star merger finally confirmed one astrophysical location of the rapid neutron-capture process (r-process). Evidence of the production of A < 140 nuclei was seen, but there is still little detailed information about how those lighter elements are produced in such an environment. Many of the questions surrounding the A ≈ 80 nuclei are likely to be answered only when the nuclear physics involved in the production of r-process nuclei is well understood. Neutron-capture reactions are an important component of the r-process, and neutron-capture cross sections of r-process nuclei, which are very neutron rich, have large uncertainties. Purpose: Indirectly determine the neutron-capture cross section and reaction rate of 73 Zn(n,γ ) 74 Zn. Methods: The nuclear level density (NLD) and γ-ray strength function (γSF) of 74 Zn were determined following a total absorption spectroscopy (TAS) experiment focused on the β decay of 74 Cu into 74 Zn performed at the National Superconducting Cyclotron Laboratory. The NLD and γSF were used as inputs in a Hauser-Feshbach statistical model to calculate the neutron-capture cross section and reaction rate. Results: The NLD and γSF of 74 Zn were experimentally constrained for the first time using β-delayed γ rays measured with TAS and the β-Oslo method. The NLD and γSF were then used to constrain the neutron-capture cross section and reaction rate for the 73 Zn(n, γ ) 74 Zn reaction. In Conclusion, the uncertainty in the neutron-capture cross section and reaction rate of 73 Zn(n, γ ) 74 Zn calculated in TALYS was reduced to under a factor of 2 from a factor of 5 in the cross section and a factor of 11 in the reaction rate using the experimentally obtained NLD and γSF.
Manganese oxides are regarded as one of the most promising cathode materials in rechargeable aqueous Zn-ion batteries (ZIBs) because of the low price and high security. However, the practical application of Mn 2 O 3 in ZIBs is still plagued by the low specific capacity and poor rate capability. Herein, highly crystalline Mn 2 O 3 materials with interconnected mesostructures and controllable pore sizes are obtained via a ligand-assisted self-assembly process and used as high-performance electrode materials for reversible aqueous ZIBs. The coordination degree between Mn 2+ and citric acid ligand plays a crucial role in the formation of the mesostructure, and the pore sizes can be easily tuned from 3.2 to 7.3 nm. Ascribed to the unique feature of nanoporous architectures, excellent zinc-storage performance can be achieved in ZIBs during charge/discharge processes. The Mn 2 O 3 electrode exhibits high reversible capacity (233 mAh g -1 at 0.3 A g -1 ), superior rate capability (162 mAh g -1 retains at 3.08 A g -1 ) and remarkable cycling durability over 3000 cycles at a high current rate of 3.08 A g -1 . Moreover, the corresponding electrode reaction mechanism is studied in depth according to a series of analytical methods. These results suggest that rational design of the nanoporous architecture for electrode materials can effectively improve the battery performance.
Developing a fundamental understanding of the effects of varying ligand chemistries on mass transport rates is key to designing membranes with solute-specific selectivity. While permeation cells offer a robust method to characterize membrane performance, they are limited to assessing a single membrane chemistry or salt solution per test. As a result, investigating the effects of varying ligand chemistries on membrane performance can be a tedious process, involving both the preparation of multiple samples and numerous, time-consuming permeation tests. This study uses digital light processing (DLP) 3D printing to fabricate a millifluidic flow-based permeation device made from a hydrogel active ester network that can be easily functionalized with ion-selective ligands. Without the need for bonding or assembly steps, ligands can be introduced and tested in the permeation device by simply injecting a small volume of a ligand solution. Various salt concentrations and molecular species can be cycled through a single device by switching the solution feeding into the salt reservoir, thereby reducing the number of samples needed for permeability and selectivity screenings. This research sets the groundwork for formulation development and postprocessing methods to 3D-print functional millifluidic devices capable of assessing solute selectivity in membranes and polymer adsorbents for aqueous separations. In this work, comparable salt permeability trends were observed with both 3D-printed devices and traditional assays. Devices were functionalized with an imidazole ligand to investigate salt permeability and selectivity of monovalent and divalent salts. Measurements showed increasing permeability for monovalent salts (NaCl) relative to divalent salts (MgCl 2 , CuCl 2 ) in functionalized membranes, with higher monovalent/divalent selectivity at increasing imidazole grafting densities. Here, the methods and findings described here represent a step toward developing higher-throughput methods with 3D-printed devices for screening the effects of ligand chemistry on mass transport rates in membrane materials.
The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.
A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.
Performance Assessment models often require inputs representing specific hydrologic processes and properties such as infiltration, water content, groundwater flow rate, streamflow, and sediment flux. This paper details the development of a process-level infiltration model and its use in a Probabilistic Performance Assessment (PPA) model for the West Valley Site in western New York. Additionally, this paper demonstrates a method for obtaining distributions of the long-term average hydrologic processes and properties for a PA model. For this PPA, an infiltration model was developed using HELP (Hydrologic Evaluation of Landfill Performance) to evaluate the rates of infiltration, percolation, and drainage through several site soil and proposed decommissioning cover systems, as well as the volumetric water contents of each of the unsaturated layers in a modeled soil column. A particular challenge of probabilistic modeling over long periods of time is scaling parameters appropriately so that outcomes are not grossly over- or underestimated. For these models, distributions of climatic parameters such as average precipitation rate, temperature, wind speed, humidity, and solar radiation were scaled to 1000-year averages and were used to force steady-state models that predict 1000-year average infiltration rates, drainage rates, and water contents. For the HELP model, distributions were developed for the physical and hydrologic properties of each material in a given soil column or cover system, and these properties were allowed to vary stochastically along with climatic inputs. The HELP model was run 5000 times for each of seven different soil and cover systems representing various existing and proposed conditions (i.e. native soil, backfill, existing covers, and a proposed close-in-place cover). The results of the HELP model provide ranges of 1000-year average infiltration rates, drainage rates, and water contents through and within the various layers of each of the different soil and cover conditions. The model outcomes also demonstrate the effectiveness of a proposed close-in-place cover, which essentially eliminates infiltration during its operational lifetime. Following model simulation, a sensitivity analysis was performed to establish the relative importance of each stochastic input with respect to each output. The outcomes of the model simulations and the sensitivity analysis were implemented into a system-level GoldSim model via a novel sensitivity-informed nearest neighbor approach. These infiltration rates, drainage rates, and water contents are used to parameterize mixing cells within the GoldSim Contaminant Transport module, which is the primary system-level model used in the PPA. The infiltration rates are also used as boundary conditions for a stochastic groundwater flow model that is also utilized in the PPA, but not discussed in this paper. (authors)